started condition trainings
This commit is contained in:
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config = dict()
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# DON'T FORGET TO RESET SSIM LOSS USAGE
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# DON'T FORGET TO CHECK MODEL LOADING
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# DON'T FORGET TO CHECK IF STORE IN MEMORY
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# DON'T FORGET TO CHECK REG LOSS COEFF
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# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
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# DON'T FORGET TO CHECK AVG GARMENT USED
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config['use_skinning'] = True # and deshaping
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config['remove_global_orientation'] = True
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config['use_curvature'] = True
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config['use_extra_losses'] = True # edge, collision, 3d mesh
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config['use_offsets'] = True
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config['use_norm_loss'] = False
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ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
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assert ablation_count == 1 or ablation_count == 0
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config['gpu'] = '1'
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config['name'] = 'abl_10p'
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config['notes'] = ''
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config['avg_garment_path'] = 'custom_data/train_no_shape_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
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if config['use_skinning']:
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assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
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config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
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config['batch_size'] = 4
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config['resolution'] = 512
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config['is_skirt'] = False
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config['dataset_in_memory'] = False
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config['is_cape'] = False
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config['train_dir'] = '/home/workspace/local-data/train'
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config['valid_dir'] = '/home/workspace/local-data/valid'
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config['test_dir'] = '/home/workspace/data/dataset/test_ready'
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config['frames_file'] = 'frames_10p.txt'
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config['static_model'] = 'checkpoints/static_1'
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config['body_model'] = 'checkpoints/body_1'
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config['curvature_model'] = 'checkpoints/curv_1'
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config['smpl_res'] = 14475
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if config['is_cape']:
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config['smpl_res'] = 3638
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config['latent_dim'] = 128
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config['pretrained_model'] = ''
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###############
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config['lr'] = 0.0001# 0.0001
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###############
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config['starting_balancing_coeff'] = 0.0001
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config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
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'pose_shape': (72 + 11,),
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'uv_body_posed': (512, 256, 3),
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'mesh_body_posed': (14475, 3,),
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'mesh_posed': (14475, 3,),
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'uv_curvature': (512, 256, 7),
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}
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config['signature_static'] = { 'uv_static': (512, 256, 3),
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'mesh_mask': (14475,),
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'uv_mask': (512, 256,),
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}
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if config['use_skinning']:
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config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
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config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
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else:
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config['signature_dynamic']['uv_posed'] = (512, 256, 3)
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config['upscale_enhancer'] = ''
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config['freeze_encoders'] = True
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config['use_one_hot'] = False
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config['cvae'] = dict()
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config['cvae']['is_label'] = False
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config['cvae']['latent_dim'] = config['latent_dim']
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config['cvae']['add_noise'] = True
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config['cvae']['noise_amount'] = 0.025
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config['cvae']['kernel_size'] = 7
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config['cvae']['encoder_depths'] = [3, 3, 9, 3]
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config['cvae']['encoder_dims'] = [32, 64, 128, 256]
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config['cvae']['decoder_input'] = (16, 8, 80)
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config['cvae']['decoder_depths'] = [3, 3, 9, 3]
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config['cvae']['decoder_dims'] = [256, 128, 64, 16]
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config['cond_ae'] = dict()
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config['cond_ae']['is_label'] = False
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config['cond_ae']['upscale_output'] = False
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config['cond_ae']['latent_dim'] = config['latent_dim']
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config['cond_ae']['kernel_size'] = 7
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config['cond_ae']['bottleneck_size'] = 64
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config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
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config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
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config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
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config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
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config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
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config['cond_ae_body'] = dict()
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config['cond_ae_body']['latent_dim'] = config['latent_dim']
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config['cond_ae_body']['kernel_size'] = 7
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config['cond_ae_body']['upscale_output'] = True
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config['cond_ae_body']['bottleneck_size'] = 512
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config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
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config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
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config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
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config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
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config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
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@@ -0,0 +1,118 @@
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config = dict()
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# DON'T FORGET TO RESET SSIM LOSS USAGE
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# DON'T FORGET TO CHECK MODEL LOADING
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||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
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# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
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# DON'T FORGET TO CHECK AVG GARMENT USED
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config['use_skinning'] = False # and deshaping
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config['remove_global_orientation'] = True
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config['use_curvature'] = True
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config['use_extra_losses'] = True # edge, collision, 3d mesh
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config['use_offsets'] = True
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config['use_norm_loss'] = False
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ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
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assert ablation_count == 1 or ablation_count == 0
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config['gpu'] = '4'
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config['name'] = 'abl_10p_skin'
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config['notes'] = ''
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config['avg_garment_path'] = '' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
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if config['use_skinning']:
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assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
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config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
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config['batch_size'] = 4
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config['resolution'] = 512
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config['is_skirt'] = False
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config['dataset_in_memory'] = False
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config['is_cape'] = False
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config['train_dir'] = '/home/workspace/local-data/train'
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config['valid_dir'] = '/home/workspace/local-data/valid'
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config['test_dir'] = '/home/workspace/data/dataset/test_ready'
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config['frames_file'] = 'frames_10p.txt'
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config['static_model'] = 'checkpoints/static_1'
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config['body_model'] = 'checkpoints/body_1'
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config['curvature_model'] = 'checkpoints/curv_1'
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config['smpl_res'] = 14475
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if config['is_cape']:
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config['smpl_res'] = 3638
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config['latent_dim'] = 128
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config['pretrained_model'] = ''
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###############
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config['lr'] = 0.0001# 0.0001
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###############
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config['starting_balancing_coeff'] = 0.0001
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config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
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'pose_shape': (72 + 11,),
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'uv_body_posed': (512, 256, 3),
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'mesh_body_posed': (14475, 3,),
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'mesh_posed': (14475, 3,),
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'uv_curvature': (512, 256, 7),
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}
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config['signature_static'] = { 'uv_static': (512, 256, 3),
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'mesh_mask': (14475,),
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'uv_mask': (512, 256,),
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}
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if config['use_skinning']:
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config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
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config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
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else:
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config['signature_dynamic']['uv_posed'] = (512, 256, 3)
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config['upscale_enhancer'] = ''
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config['freeze_encoders'] = True
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config['use_one_hot'] = False
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config['cvae'] = dict()
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config['cvae']['is_label'] = False
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config['cvae']['latent_dim'] = config['latent_dim']
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config['cvae']['add_noise'] = True
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config['cvae']['noise_amount'] = 0.025
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config['cvae']['kernel_size'] = 7
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config['cvae']['encoder_depths'] = [3, 3, 9, 3]
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config['cvae']['encoder_dims'] = [32, 64, 128, 256]
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config['cvae']['decoder_input'] = (16, 8, 80)
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config['cvae']['decoder_depths'] = [3, 3, 9, 3]
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config['cvae']['decoder_dims'] = [256, 128, 64, 16]
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config['cond_ae'] = dict()
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config['cond_ae']['is_label'] = False
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config['cond_ae']['upscale_output'] = False
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config['cond_ae']['latent_dim'] = config['latent_dim']
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config['cond_ae']['kernel_size'] = 7
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config['cond_ae']['bottleneck_size'] = 64
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config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
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config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
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config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
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config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
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config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
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config['cond_ae_body'] = dict()
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config['cond_ae_body']['latent_dim'] = config['latent_dim']
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config['cond_ae_body']['kernel_size'] = 7
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config['cond_ae_body']['upscale_output'] = True
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config['cond_ae_body']['bottleneck_size'] = 512
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config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
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config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
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config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
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config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
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config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
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@@ -0,0 +1,118 @@
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config = dict()
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# DON'T FORGET TO RESET SSIM LOSS USAGE
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||||
# DON'T FORGET TO CHECK MODEL LOADING
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||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
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||||
# DON'T FORGET TO CHECK AVG GARMENT USED
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||||
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config['use_skinning'] = True # and deshaping
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config['remove_global_orientation'] = True
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config['use_curvature'] = True
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config['use_extra_losses'] = True # edge, collision, 3d mesh
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config['use_offsets'] = True
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config['use_norm_loss'] = False
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ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
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assert ablation_count == 1 or ablation_count == 0
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config['gpu'] = '3'
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config['name'] = 'abl_25p'
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config['notes'] = ''
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config['avg_garment_path'] = 'custom_data/train_no_shape_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
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if config['use_skinning']:
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assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
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config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
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config['batch_size'] = 4
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config['resolution'] = 512
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config['is_skirt'] = False
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config['dataset_in_memory'] = False
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config['is_cape'] = False
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config['train_dir'] = '/home/workspace/local-data/train'
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config['valid_dir'] = '/home/workspace/local-data/valid'
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config['test_dir'] = '/home/workspace/data/dataset/test_ready'
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config['frames_file'] = 'frames_25p.txt'
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config['static_model'] = 'checkpoints/static_1'
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config['body_model'] = 'checkpoints/body_1'
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config['curvature_model'] = 'checkpoints/curv_1'
|
||||
|
||||
|
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config['smpl_res'] = 14475
|
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if config['is_cape']:
|
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config['smpl_res'] = 3638
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||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,118 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = False # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '1'
|
||||
config['name'] = 'abl_25p_skin'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = '' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
config['frames_file'] = 'frames_25p.txt'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1'
|
||||
config['body_model'] = 'checkpoints/body_1'
|
||||
config['curvature_model'] = 'checkpoints/curv_1'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,185 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '6'
|
||||
config['name'] = 'abl_2_pyr_32'
|
||||
config['notes'] = 'fixed noise handling'
|
||||
config['tags'] = ['pyr_non_skirt_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = 'checkpoints/pyr_abl_32_430k'
|
||||
config['pretrained_model_iteration'] = '430000'
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32]
|
||||
config['pyramid']['pretrained_pyramid'] = ''
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/32_512_4'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1'
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,185 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '6'
|
||||
config['name'] = 'abl_2_pyr_32_64'
|
||||
config['notes'] = 'fixed noise handling'
|
||||
config['tags'] = ['pyr_non_skirt_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
config['pretrained_model_iteration'] = ''
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32, 64]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/abl_2_pyr_32'
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/32_512_4'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1'
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/32_512_4'#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,186 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '6'
|
||||
config['name'] = 'abl_2_pyr_32_64_128'
|
||||
config['notes'] = 'fixed noise handling'
|
||||
config['tags'] = ['pyr_non_skirt_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
config['pretrained_model_iteration'] = ''
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32, 64, 128]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/abl_2_pyr_32_64'
|
||||
config['pyramid']['pretrained_pyramid_iteration'] = '100000'
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/128_512_3'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1'
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/64_512_2'#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/32_512_4'#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,186 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '6'
|
||||
config['name'] = 'abl_2_pyr_32_64_128_256'
|
||||
config['notes'] = 'fixed noise handling'
|
||||
config['tags'] = ['pyr_non_skirt_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
config['pretrained_model_iteration'] = ''
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32, 64, 128, 256]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/abl_2_pyr_32_64_128'
|
||||
config['pyramid']['pretrained_pyramid_iteration'] = '80000'
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/256_512'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1'
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/128_512_3'#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/64_512_2'#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/32_512_4'#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,191 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '6'
|
||||
config['name'] = 'abl_2_pyr_32_64_128_256_512'
|
||||
config['notes'] = 'fixed noise handling'
|
||||
config['tags'] = ['pyr_non_skirt_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = 'checkpoints/abl_2_pyr_32_64_128_256_512'
|
||||
config['pretrained_model_iteration'] = '50000'
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32, 64, 128, 256, 512]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/abl_2_pyr_32_64_128_256'
|
||||
config['pyramid']['pretrained_pyramid_iteration'] = '70000'
|
||||
config['pyramid']['final_upscale_enhancer'] = ''
|
||||
config['pyramid']['upscale_enhancer_kernel_size'] = 3
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1'
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/256_512'#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
level['upscale_enhancer_kernel_size'] = 3
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/128_512_3'#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
level['upscale_enhancer_kernel_size'] = 3
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/64_512_2'#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
level['upscale_enhancer_kernel_size'] = 3
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/32_512_4'#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
level['upscale_enhancer_kernel_size'] = 3
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,186 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '6'
|
||||
config['name'] = 'abl_2_pyr_32_64_128_256_512_norm'
|
||||
config['notes'] = 'fixed noise handling'
|
||||
config['tags'] = ['pyr_non_skirt_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
config['use_norm_loss'] = True
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
config['pretrained_model_iteration'] = ''
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32, 64, 128, 256, 512]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/abl_2_pyr_32_64_128_256'
|
||||
config['pyramid']['pretrained_pyramid_iteration'] = '70000'
|
||||
config['pyramid']['final_upscale_enhancer'] = ''
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 1.0 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1'
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/256_512'#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/128_512_3'#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/64_512_2'#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/32_512_4'#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,189 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '5'
|
||||
config['name'] = 'abl_2_pyr_32_64_128_256_512_skirt'
|
||||
config['notes'] = ''
|
||||
config['tags'] = ['pyr_skirt_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
config['pretrained_model_iteration'] = ''
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32, 64, 128, 256, 512]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/abl_2_pyr_32_64_128_256_skirt'
|
||||
config['pyramid']['pretrained_pyramid_iteration'] = '70000'
|
||||
config['pyramid']['final_upscale_enhancer'] = ''
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid_skirt'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = True
|
||||
config['is_cape'] = False
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_skirt'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_skirt_2_2'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_skirt'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/256_512_skirt'#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/128_512_skirt'#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/64_512_skirt'#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/32_512_skirt'#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,190 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '4'
|
||||
config['name'] = 'abl_2_pyr_32_64_128_256_512_test'
|
||||
config['notes'] = 'fixed noise handling'
|
||||
config['tags'] = ['pyr_non_skirt_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
config['pretrained_model_iteration'] = ''
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [256]
|
||||
config['pyramid']['pretrained_pyramid'] = ''
|
||||
config['pyramid']['pretrained_pyramid_iteration'] = ''
|
||||
config['pyramid']['final_upscale_enhancer'] = 'x'
|
||||
|
||||
config['frames_file'] = 'frames_00761_0.txt'
|
||||
config['frames_file_valid'] = 'frames_00761_0.txt'
|
||||
config['frames_file_test'] = 'frames_00761_0.txt'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/train'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['dataset_in_memory'] = True
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1'
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,189 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '4'
|
||||
config['name'] = 'abl_2_pyr_32_64_128_256_skirt'
|
||||
config['notes'] = ''
|
||||
config['tags'] = ['pyr_skirt_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
config['pretrained_model_iteration'] = ''
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32, 64, 128, 256]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/abl_2_pyr_32_64_128_skirt'
|
||||
config['pyramid']['pretrained_pyramid_iteration'] = '80000'
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/256_512_skirt'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid_skirt'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = True
|
||||
config['is_cape'] = False
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_skirt'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_skirt_2_2'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_skirt'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/128_512_skirt'#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/64_512_skirt'#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/32_512_skirt'#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,189 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '5'
|
||||
config['name'] = 'abl_2_pyr_32_64_128_skirt'
|
||||
config['notes'] = ''
|
||||
config['tags'] = ['pyr_skirt_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
config['pretrained_model_iteration'] = ''
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32, 64, 128]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/abl_2_pyr_32_64_skirt'
|
||||
config['pyramid']['pretrained_pyramid_iteration'] = ''
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/128_512_skirt'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid_skirt'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = True
|
||||
config['is_cape'] = False
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_skirt'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_skirt_2_2'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_skirt'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/64_512_skirt'#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/32_512_skirt'#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,185 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '0'
|
||||
config['name'] = 'abl_2_pyr_32_64_2'
|
||||
config['notes'] = 'fixed noise handling, don\'t divide output by 100'
|
||||
config['tags'] = ['pyr_non_skirt_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
config['pretrained_model_iteration'] = ''
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32, 64]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/abl_2_pyr_32'
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/32_512_4'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1'
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/32_512_4'#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,189 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '6'
|
||||
config['name'] = 'abl_2_pyr_32_64_skirt'
|
||||
config['notes'] = ''
|
||||
config['tags'] = ['pyr_skirt_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
config['pretrained_model_iteration'] = ''
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32, 64]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/abl_2_pyr_32_skirt'
|
||||
config['pyramid']['pretrained_pyramid_iteration'] = ''
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/64_512_skirt'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid_skirt'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = True
|
||||
config['is_cape'] = False
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_skirt'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_skirt_2_2'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_skirt'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/32_512_skirt'#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,191 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '3'
|
||||
config['name'] = 'abl_2_pyr_32_skin'
|
||||
config['notes'] = 'fixed noise handling'
|
||||
config['tags'] = ['pyr_non_skirt_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = False # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = 'checkpoints/pyr_abl_32_skin'
|
||||
config['pretrained_model_iteration'] = '250000'
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32]
|
||||
config['pyramid']['pretrained_pyramid'] = ''
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/32_512_4'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (config['smpl_res'], 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1'
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,191 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '5'
|
||||
config['name'] = 'abl_2_pyr_32_skin_2'
|
||||
config['notes'] = 'fixed noise handling'
|
||||
config['tags'] = ['pyr_non_skirt_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = False # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = 'checkpoints/pyr_abl_32_430k'
|
||||
config['pretrained_model_iteration'] = '430000'
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32]
|
||||
config['pyramid']['pretrained_pyramid'] = ''
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/32_512_4'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (config['smpl_res'], 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1'
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,191 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '4'
|
||||
config['name'] = 'abl_2_pyr_32_skin_norm'
|
||||
config['notes'] = 'fixed noise handling'
|
||||
config['tags'] = ['pyr_non_skirt_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = False # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
config['use_norm_loss'] = True
|
||||
|
||||
config['pretrained_model'] = 'checkpoints/pyr_abl_32_skin'
|
||||
config['pretrained_model_iteration'] = '250000'
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32]
|
||||
config['pyramid']['pretrained_pyramid'] = ''
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/32_512_4'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (config['smpl_res'], 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1'
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,189 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '6'
|
||||
config['name'] = 'abl_2_pyr_32_skirt'
|
||||
config['notes'] = ''
|
||||
config['tags'] = ['pyr_skirt_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = 'checkpoints/pyr_abl_32_skirt_2'
|
||||
config['pretrained_model_iteration'] = '130000'
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32]
|
||||
config['pyramid']['pretrained_pyramid'] = ''
|
||||
config['pyramid']['pretrained_pyramid_iteration'] = ''
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/32_512_skirt'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid_skirt'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = True
|
||||
config['is_cape'] = False
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_skirt'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_skirt_2_2'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_skirt'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,189 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '4'
|
||||
config['name'] = 'abl_2_pyr_32_skirt_extra_loss'
|
||||
config['notes'] = ''
|
||||
config['tags'] = ['pyr_skirt_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = False # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = 'checkpoints/pyr_abl_32_extra_loss_skirt'
|
||||
config['pretrained_model_iteration'] = '130000'
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32]
|
||||
config['pyramid']['pretrained_pyramid'] = ''
|
||||
config['pyramid']['pretrained_pyramid_iteration'] = ''
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/32_512_skirt'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid_skirt'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = True
|
||||
config['is_cape'] = False
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_skirt'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_skirt_2_2'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_skirt'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,191 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '2'
|
||||
config['name'] = 'abl_2_pyr_64_128_256_512_cape_f'
|
||||
config['notes'] = ''
|
||||
config['tags'] = ['cape_f_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
config['pretrained_model_iteration'] = ''
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [64, 128, 256, 512]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/abl_2_pyr_64_128_256_cape_f'
|
||||
config['pyramid']['pretrained_pyramid_iteration'] = '40000'
|
||||
config['pyramid']['final_upscale_enhancer'] = ''
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/female'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_cape_f'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_cape_f'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_cape_f'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = None # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/256_512_cape_f'#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
level['upscale_enhancer_kernel_size'] = 3
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/128_512_cape_f'#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
level['upscale_enhancer_kernel_size'] = 3
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/64_512_cape_f'#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
level['upscale_enhancer_kernel_size'] = 3
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,188 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '5'
|
||||
config['name'] = 'abl_2_pyr_64_128_256_512_cape_m'
|
||||
config['notes'] = ''
|
||||
config['tags'] = ['cape_m_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
config['pretrained_model_iteration'] = ''
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [64, 128, 256, 512]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/abl_2_pyr_64_128_256_cape_m'
|
||||
config['pyramid']['pretrained_pyramid_iteration'] = '40000'
|
||||
config['pyramid']['final_upscale_enhancer'] = ''
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/male'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/test/male'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/test/male'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_cape_m'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_cape_m'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_cape_m'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = None # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/256_512_cape_m'#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/128_512_cape_m'#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/64_512_cape_m'#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,188 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '6'
|
||||
config['name'] = 'abl_2_pyr_64_128_256_cape_f'
|
||||
config['notes'] = ''
|
||||
config['tags'] = ['cape_f_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
config['pretrained_model_iteration'] = ''
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [64, 128, 256]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/abl_2_pyr_64_128_cape_f'
|
||||
config['pyramid']['pretrained_pyramid_iteration'] = '40000'
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/256_512_cape_f'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/female'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_cape_f'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_cape_f'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_cape_f'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = None # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/128_512_cape_f'#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/64_512_cape_f'#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,187 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '5'
|
||||
config['name'] = 'abl_2_pyr_64_128_256_cape_m'
|
||||
config['notes'] = 'abl_2_pyr_64_128_cape_m at 40k'
|
||||
config['tags'] = ['cape_m_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
config['pretrained_model_iteration'] = ''
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [64, 128, 256]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/abl_2_pyr_64_128_cape_m'
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/256_512_cape_m'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/male'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/test/male'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/test/male'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_cape_m'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_cape_m'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_cape_m'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = None # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/128_512_cape_m'#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/64_512_cape_m'#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,190 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '4'
|
||||
config['name'] = 'abl_2_pyr_64_128_256_cape_m_00032_SL'
|
||||
config['notes'] = ''
|
||||
config['tags'] = ['cape_m_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
config['pretrained_model_iteration'] = ''
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [64, 128, 256]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/abl_2_pyr_64_128_cape_m_00032_SL'
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/256_512_cape_m'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/male'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/train/male'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/train/male'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['frames_file'] = 'frames_00032_SL_train.txt'
|
||||
config['frames_file_valid'] = 'frames_00032_SL_test.txt'
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_cape_m'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_cape_m'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_cape_m'
|
||||
|
||||
config['dataset_in_memory'] = True
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = None # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/128_512_cape_m'#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/64_512_cape_m'#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,188 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '6'
|
||||
config['name'] = 'abl_2_pyr_64_128_cape_f'
|
||||
config['notes'] = ''
|
||||
config['tags'] = ['cape_f_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
config['pretrained_model_iteration'] = ''
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [64, 128]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/abl_2_pyr_64_cape_f'
|
||||
config['pyramid']['pretrained_pyramid_iteration'] = '70000'
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/128_512_cape_f'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/female'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_cape_f'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_cape_f'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_cape_f'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = None # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/64_512_cape_f'#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,187 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '6'
|
||||
config['name'] = 'abl_2_pyr_64_128_cape_m'
|
||||
config['notes'] = ''
|
||||
config['tags'] = ['cape_m_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
config['pretrained_model_iteration'] = ''
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [64, 128]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/abl_2_pyr_64_cape_m'
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/128_512_cape_m'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/male'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/test/male'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/test/male'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_cape_m'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_cape_m'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_cape_m'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = None # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/64_512_cape_m'#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,190 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '2'
|
||||
config['name'] = 'abl_2_pyr_64_128_cape_m_00032_SL'
|
||||
config['notes'] = ''
|
||||
config['tags'] = ['cape_m_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
config['pretrained_model_iteration'] = ''
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [64, 128]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/abl_2_pyr_64_cape_m_00032_SL'
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/128_512_cape_m'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/male'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/train/male'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/train/male'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['frames_file'] = 'frames_00032_SL_train.txt'
|
||||
config['frames_file_valid'] = 'frames_00032_SL_test.txt'
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_cape_m'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_cape_m'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_cape_m'
|
||||
|
||||
config['dataset_in_memory'] = True
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = None # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/64_512_cape_m'#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,187 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '6'
|
||||
config['name'] = 'abl_2_pyr_64_cape_f'
|
||||
config['notes'] = ''
|
||||
config['tags'] = ['cape_f_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = 'checkpoints/pyr_abl_64_cape_f'
|
||||
config['pretrained_model_iteration'] = '170000'
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [64]
|
||||
config['pyramid']['pretrained_pyramid'] = ''
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/64_512_cape_f'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/female'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_cape_f'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_cape_f'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_cape_f'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = None # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,190 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '1'
|
||||
config['name'] = 'abl_2_pyr_64_cape_f_03223_SS'
|
||||
config['notes'] = ''
|
||||
config['tags'] = ['cape_f_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
config['pretrained_model_iteration'] = ''
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [64]
|
||||
config['pyramid']['pretrained_pyramid'] = ''
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/64_512_cape_f'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/female'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['frames_file'] = 'frames_03223_SS.txt'
|
||||
config['frames_file_valid'] = 'frames_03223_SS.txt'
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_cape_f'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_cape_f'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_cape_f'
|
||||
|
||||
config['dataset_in_memory'] = True
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = None # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,187 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '6'
|
||||
config['name'] = 'abl_2_pyr_64_cape_m'
|
||||
config['notes'] = ''
|
||||
config['tags'] = ['cape_m_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = 'checkpoints/pyr_abl_64_cape_m'
|
||||
config['pretrained_model_iteration'] = '170000'
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [64]
|
||||
config['pyramid']['pretrained_pyramid'] = ''
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/64_512_cape_m'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/male'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/test/male'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/test/male'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_cape_m'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_cape_m'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_cape_m'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = None # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,190 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '2'
|
||||
config['name'] = 'abl_2_pyr_64_cape_m_00032_SL'
|
||||
config['notes'] = ''
|
||||
config['tags'] = ['cape_m_2']
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
config['pretrained_model_iteration'] = ''
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [64]
|
||||
config['pyramid']['pretrained_pyramid'] = ''
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/64_512_cape_m'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/male'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/train/male'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/train/male'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['frames_file'] = 'frames_00032_SL_train.txt'
|
||||
config['frames_file_valid'] = 'frames_00032_SL_test.txt'
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_cape_m'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_cape_m'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_cape_m'
|
||||
|
||||
config['dataset_in_memory'] = True
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = None # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.001
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,118 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = False # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '6'
|
||||
config['name'] = 'abl_50p_skin'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = '' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
config['frames_file'] = 'frames_50p.txt'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1'
|
||||
config['body_model'] = 'checkpoints/body_1'
|
||||
config['curvature_model'] = 'checkpoints/curv_1'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,117 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '3'
|
||||
config['name'] = 'abl_abs'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = '' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1'
|
||||
config['body_model'] = 'checkpoints/body_1'
|
||||
config['curvature_model'] = 'checkpoints/curv_1'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,117 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '2'
|
||||
config['name'] = 'abl_abs_skirt'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = '' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = True
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid_skirt'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1_skirt'
|
||||
config['body_model'] = 'checkpoints/body_1_skirt_2_2'
|
||||
config['curvature_model'] = 'checkpoints/curv_1_skirt'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,117 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '0'
|
||||
config['name'] = 'abl_all'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_no_shape_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1'
|
||||
config['body_model'] = 'checkpoints/body_1'
|
||||
config['curvature_model'] = 'checkpoints/curv_1'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,117 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '0'
|
||||
config['name'] = 'abl_all'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_no_shape_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1'
|
||||
config['body_model'] = 'checkpoints/body_1'
|
||||
config['curvature_model'] = 'checkpoints/curv_1'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,126 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = True
|
||||
config['only_curvatures'] = False
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '4'
|
||||
config['name'] = 'al_all_post'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_no_shape_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
|
||||
# config['frames_file'] = 'frames_dress_30k.txt'
|
||||
# config['frames_file_valid'] = 'frames_dress_30k.txt'
|
||||
# config['frames_file_test'] = 'frames_dress_30k.txt'
|
||||
|
||||
config['static_model'] = 'checkpoints/post/static_post_2'
|
||||
config['body_model'] = 'checkpoints/post/body_post_2'
|
||||
config['curvature_model'] = 'checkpoints/post/curv_post_1'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (config['smpl_res'], 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.001
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256, 64]
|
||||
config['cvae']['decoder_depths'] = config['cvae']['encoder_depths']
|
||||
config['cvae']['decoder_dims'] = config['cvae']['encoder_dims']
|
||||
|
||||
|
||||
config['cond_ae_static'] = dict()
|
||||
config['cond_ae_static']['is_label'] = False
|
||||
config['cond_ae_static']['kernel_size'] = 7
|
||||
config['cond_ae_static']['bottleneck_size'] = 8
|
||||
config['cond_ae_static']['encoder_depths'] = [3, 3, 3, 9, 3]
|
||||
config['cond_ae_static']['encoder_dims'] = [16, 32, 64, 64, config['cond_ae_static']['bottleneck_size']]
|
||||
config['cond_ae_static']['decoder_depths'] = config['cond_ae_static']['encoder_depths']
|
||||
config['cond_ae_static']['decoder_dims'] = config['cond_ae_static']['encoder_dims']
|
||||
config['cond_ae_static']['activation'] = 'tanh'
|
||||
|
||||
config['cond_ae_curv'] = dict()
|
||||
config['cond_ae_curv']['is_label'] = True
|
||||
config['cond_ae_curv']['kernel_size'] = 7
|
||||
config['cond_ae_curv']['bottleneck_size'] = 40
|
||||
config['cond_ae_curv']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae_curv']['encoder_dims'] = [16, 32, 64, 128, config['cond_ae_curv']['bottleneck_size']]
|
||||
config['cond_ae_curv']['decoder_depths'] = config['cond_ae_curv']['encoder_depths']
|
||||
config['cond_ae_curv']['decoder_dims'] = config['cond_ae_curv']['encoder_dims']
|
||||
config['cond_ae_curv']['activation'] = 'tanh'
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['is_label'] = False
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['bottleneck_size'] = 16
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [16, 32, 64, 128, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_depths'] = config['cond_ae_body']['encoder_depths']
|
||||
config['cond_ae_body']['decoder_dims'] = config['cond_ae_body']['encoder_dims']
|
||||
config['cond_ae_body']['activation'] = 'tanh'
|
||||
@@ -0,0 +1,117 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '5'
|
||||
config['name'] = 'abl_all_skirt'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_no_shape_skirt_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = True
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid_skirt'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1_skirt'
|
||||
config['body_model'] = 'checkpoints/body_1_skirt_2_2'
|
||||
config['curvature_model'] = 'checkpoints/curv_1_skirt'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,117 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = False
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '5'
|
||||
config['name'] = 'abl_curv'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_no_shape_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1'
|
||||
config['body_model'] = 'checkpoints/body_1'
|
||||
config['curvature_model'] = 'checkpoints/curv_1'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,117 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = False
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '6'
|
||||
config['name'] = 'abl_curv_skirt'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_no_shape_skirt_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = True
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid_skirt'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1_skirt'
|
||||
config['body_model'] = 'checkpoints/body_1_skirt_2_2'
|
||||
config['curvature_model'] = 'checkpoints/curv_1_skirt'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,117 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = False # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '4'
|
||||
config['name'] = 'abl_extra_loss'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_no_shape_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1'
|
||||
config['body_model'] = 'checkpoints/body_1'
|
||||
config['curvature_model'] = 'checkpoints/curv_1'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,117 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = False # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '5'
|
||||
config['name'] = 'abl_extra_loss_skirt'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_no_shape_skirt_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = True
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid_skirt'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1_skirt'
|
||||
config['body_model'] = 'checkpoints/body_1_skirt_2_2'
|
||||
config['curvature_model'] = 'checkpoints/curv_1_skirt'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,118 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
config['block_collision_loss'] = True
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '0'
|
||||
config['name'] = 'abl_extra_loss_skirt_2'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_no_shape_skirt_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = True
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid_skirt'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1_skirt'
|
||||
config['body_model'] = 'checkpoints/body_1_skirt_2_2'
|
||||
config['curvature_model'] = 'checkpoints/curv_1_skirt'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,117 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = True
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '6'
|
||||
config['name'] = 'abl_norm'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_no_shape_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1'
|
||||
config['body_model'] = 'checkpoints/body_1'
|
||||
config['curvature_model'] = 'checkpoints/curv_1'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,117 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = True
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '4'
|
||||
config['name'] = 'abl_norm_skirt'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_no_shape_skirt_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = True
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid_skirt'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1_skirt'
|
||||
config['body_model'] = 'checkpoints/body_1_skirt_2_2'
|
||||
config['curvature_model'] = 'checkpoints/curv_1_skirt'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,116 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_one_hot'] = True
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '2'
|
||||
config['name'] = 'abl_one_hot_skirt'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_no_shape_skirt_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = True
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid_skirt'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1_skirt'
|
||||
config['body_model'] = 'checkpoints/body_1_skirt_2_2'
|
||||
config['curvature_model'] = 'checkpoints/curv_1_skirt'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,117 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = False
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '6'
|
||||
config['name'] = 'abl_orient'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_no_shape_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1'
|
||||
config['body_model'] = 'checkpoints/body_1'
|
||||
config['curvature_model'] = 'checkpoints/curv_1'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,117 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = False
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '1'
|
||||
config['name'] = 'abl_orient_skirt'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_no_shape_skirt_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = True
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid_skirt'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1_skirt'
|
||||
config['body_model'] = 'checkpoints/body_1_skirt_2_2'
|
||||
config['curvature_model'] = 'checkpoints/curv_1_skirt'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,121 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = True
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '0'
|
||||
config['name'] = 'abl_overfit'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_00761_no_shape_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = True
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/train'
|
||||
config['test_dir'] = '/home/workspace/local-data/train'
|
||||
|
||||
config['frames_file'] = 'frames_00761.txt'
|
||||
config['frames_file_valid'] = 'frames_00761.txt'
|
||||
config['frames_file_test'] = 'frames_00761.txt'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1'
|
||||
config['body_model'] = 'checkpoints/body_1'
|
||||
config['curvature_model'] = 'checkpoints/curv_1'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,122 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = True
|
||||
config['only_curvatures'] = True
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '4'
|
||||
config['name'] = 'abl_overfit_dress'
|
||||
config['notes'] = 'remove other conditions from input as well'
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_dress_30k_no_shape_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = True
|
||||
config['dataset_in_memory'] = True
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['valid_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['test_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
|
||||
config['frames_file'] = 'frames_dress_30k.txt'
|
||||
config['frames_file_valid'] = 'frames_dress_30k.txt'
|
||||
config['frames_file_test'] = 'frames_dress_30k.txt'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1_skirt'
|
||||
config['body_model'] = 'checkpoints/body_1_skirt_2_2'
|
||||
config['curvature_model'] = 'checkpoints/curv_1_skirt'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.01
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,123 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = True
|
||||
config['only_curvatures'] = True
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '0'
|
||||
config['name'] = 'abl_overfit_dress_var'
|
||||
config['notes'] = 'remove other conditions from input as well'
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_dress_30k_no_shape_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = True
|
||||
config['dataset_in_memory'] = True
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['valid_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['test_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
|
||||
config['frames_file'] = 'frames_dress_30k.txt'
|
||||
config['frames_file_valid'] = 'frames_dress_30k.txt'
|
||||
config['frames_file_test'] = 'frames_dress_30k.txt'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1_skirt'
|
||||
config['body_model'] = 'checkpoints/body_1_skirt_2_2'
|
||||
config['curvature_model'] = 'checkpoints/curv_1_skirt'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = 'checkpoints/abl_overfit_dress'
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 1.0
|
||||
config['balancing_activation_limit'] = 0.013
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,122 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = True
|
||||
config['only_curvatures'] = True
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '1'
|
||||
config['name'] = 'abl_overfit_dress_var_2'
|
||||
config['notes'] = 'remove other conditions from input as well, divide values by 1000 before tanh'
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_dress_30k_no_shape_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = True
|
||||
config['dataset_in_memory'] = True
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['valid_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['test_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
|
||||
config['frames_file'] = 'frames_dress_30k.txt'
|
||||
config['frames_file_valid'] = 'frames_dress_30k.txt'
|
||||
config['frames_file_test'] = 'frames_dress_30k.txt'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1_skirt'
|
||||
config['body_model'] = 'checkpoints/body_1_skirt_2_2'
|
||||
config['curvature_model'] = 'checkpoints/curv_1_skirt'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.1
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.001
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,122 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = True
|
||||
config['only_curvatures'] = True
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '1'
|
||||
config['name'] = 'abl_overfit_dress_var_3'
|
||||
config['notes'] = 'remove other conditions from input as well, divide values by 1000 before tanh, continued from abl_overfit_dress_var_2'
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_dress_30k_no_shape_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = True
|
||||
config['dataset_in_memory'] = True
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['valid_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['test_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
|
||||
config['frames_file'] = 'frames_dress_30k.txt'
|
||||
config['frames_file_valid'] = 'frames_dress_30k.txt'
|
||||
config['frames_file_test'] = 'frames_dress_30k.txt'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1_skirt'
|
||||
config['body_model'] = 'checkpoints/body_1_skirt_2_2'
|
||||
config['curvature_model'] = 'checkpoints/curv_1_skirt'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = 'checkpoints/abl_overfit_dress_var_2'
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 1.0
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.001
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,122 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = True
|
||||
config['only_curvatures'] = False
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '5'
|
||||
config['name'] = 'abl_overfit_jumpsuit'
|
||||
config['notes'] = 'remove other conditions from input as well'
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_jumpsuit_30k_no_shape_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = True
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/train'
|
||||
config['test_dir'] = '/home/workspace/local-data/train'
|
||||
|
||||
config['frames_file'] = 'frames_jumpsuit_30k.txt'
|
||||
config['frames_file_valid'] = 'frames_jumpsuit_30k.txt'
|
||||
config['frames_file_test'] = 'frames_jumpsuit_30k.txt'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1'
|
||||
config['body_model'] = 'checkpoints/body_1'
|
||||
config['curvature_model'] = 'checkpoints/curv_1'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.01
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,122 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = True
|
||||
config['only_curvatures'] = True
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '5'
|
||||
config['name'] = 'abl_overfit_jumpsuit_2'
|
||||
config['notes'] = 'remove other conditions from input as well'
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_jumpsuit_30k_no_shape_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = True
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/train'
|
||||
config['test_dir'] = '/home/workspace/local-data/train'
|
||||
|
||||
config['frames_file'] = 'frames_jumpsuit_30k.txt'
|
||||
config['frames_file_valid'] = 'frames_jumpsuit_30k.txt'
|
||||
config['frames_file_test'] = 'frames_jumpsuit_30k.txt'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1'
|
||||
config['body_model'] = 'checkpoints/body_1'
|
||||
config['curvature_model'] = 'checkpoints/curv_1'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.01
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,181 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '0'
|
||||
config['name'] = 'pyr_abl_32'
|
||||
config['notes'] = ''
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32]
|
||||
config['pyramid']['pretrained_pyramid'] = ''
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/32_512_4'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.025
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1'
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,182 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '2'
|
||||
config['name'] = 'pyr_abl_32_2'
|
||||
config['notes'] = 'fixed noise handling'
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32]
|
||||
config['pyramid']['pretrained_pyramid'] = ''
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/32_512_4'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.025
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1'
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,180 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '4'
|
||||
config['name'] = 'pyr_abl_32_64'
|
||||
config['notes'] = ''
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32, 64]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/pyr_abl_32_430k'
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/64_512_2'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1'
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/32_512_4'#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,180 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '0'
|
||||
config['name'] = 'pyr_abl_32_64_2'
|
||||
config['notes'] = 'dividing output by 100, not 10'
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32, 64]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/pyr_abl_32_430k'
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/64_512_2'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1'
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/32_512_4'#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,181 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '5'
|
||||
config['name'] = 'pyr_abl_32_64_skirt'
|
||||
config['notes'] = ''
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32, 64]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/pyr_abl_32_skirt_2'
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/64_512_skirt'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid_skirt'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = True
|
||||
config['is_cape'] = False
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_skirt'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_skirt_2_2'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_skirt'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/32_512_skirt'#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,181 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '5'
|
||||
config['name'] = 'pyr_abl_32_64_skirt_2'
|
||||
config['notes'] = 'dividing output by 100, not 10'
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32, 64]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/pyr_abl_32_skirt_2'
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/64_512_skirt'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid_skirt'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = True
|
||||
config['is_cape'] = False
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_skirt'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_skirt_2_2'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_skirt'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/32_512_skirt'#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,177 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '5'
|
||||
config['name'] = 'pyr_abl_32_cape_f'
|
||||
config['notes'] = ''
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32]
|
||||
config['pyramid']['pretrained_pyramid'] = ''
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/32_512_cape_f'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/female'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_cape_f'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_cape_f'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_cape_f'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = None # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,177 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '4'
|
||||
config['name'] = 'pyr_abl_32_cape_m'
|
||||
config['notes'] = ''
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32]
|
||||
config['pyramid']['pretrained_pyramid'] = ''
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/32_512_cape_m'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/male'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/test/male'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/test/male'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_cape_m'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_cape_m'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_cape_m'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = None # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,181 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '6'
|
||||
config['name'] = 'pyr_abl_32_extra_loss_skirt'
|
||||
config['notes'] = ''
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32]
|
||||
config['pyramid']['pretrained_pyramid'] = ''
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/32_512_skirt'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid_skirt'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = True
|
||||
config['is_cape'] = False
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_skirt'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_skirt_2_2'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_skirt'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,185 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '3'
|
||||
config['name'] = 'pyr_abl_32_skin'
|
||||
config['notes'] = ''
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = False # and deshaping
|
||||
config['use_offsets'] = False
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32]
|
||||
config['pyramid']['pretrained_pyramid'] = ''
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/32_512_4'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (config['smpl_res'], 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1'
|
||||
config['pyramid']['curvature_model'] = '' #checkpoints/curv_1
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,185 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '5'
|
||||
config['name'] = 'pyr_abl_32_skin_offset'
|
||||
config['notes'] = ''
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = False # and deshaping
|
||||
config['use_offsets'] = True
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32]
|
||||
config['pyramid']['pretrained_pyramid'] = ''
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/32_512_4'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (config['smpl_res'], 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1'
|
||||
config['pyramid']['curvature_model'] = '' #checkpoints/curv_1
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,181 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '3'
|
||||
config['name'] = 'pyr_abl_32_skirt_2'
|
||||
config['notes'] = 'continued from pyr_abl_32_skirt-180k'
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32]
|
||||
config['pyramid']['pretrained_pyramid'] = ''
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/32_512_skirt'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid_skirt'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = True
|
||||
config['is_cape'] = False
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_skirt'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_skirt_2_2'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_skirt'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,181 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '6'
|
||||
config['name'] = 'pyr_abl_64_128_256_512_cape_f'
|
||||
config['notes'] = 'removing activation from last layer and dividing output by 100, 30k pretrained prev level'
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [64, 128, 256, 512]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/pyr_abl_64_128_256_cape_f_2'
|
||||
config['pyramid']['final_upscale_enhancer'] = ''
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/female'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_cape_f'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_cape_f'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_cape_f'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = None # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/256_512_cape_f'#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/128_512_cape_f'#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/64_512_cape_f'#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,181 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '0'
|
||||
config['name'] = 'pyr_abl_64_128_256_512_cape_f_2'
|
||||
config['notes'] = 'removing activation from last layer and dividing output by 100, 80k pretrained prev level'
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [64, 128, 256, 512]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/pyr_abl_64_128_256_cape_f_2'
|
||||
config['pyramid']['final_upscale_enhancer'] = ''
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/female'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_cape_f'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_cape_f'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_cape_f'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = None # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/256_512_cape_f'#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/128_512_cape_f'#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/64_512_cape_f'#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,181 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '4'
|
||||
config['name'] = 'pyr_abl_64_128_256_cape_f_2'
|
||||
config['notes'] = 'removing activation from last layer and dividing output by 100'
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [64, 128, 256]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/pyr_abl_64_128_cape_f_2'
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/256_512_cape_f'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/female'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_cape_f'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_cape_f'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_cape_f'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = None # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/128_512_cape_f'#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/64_512_cape_f'#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,181 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '4'
|
||||
config['name'] = 'pyr_abl_64_128_cape_f_2'
|
||||
config['notes'] = 'removing activation from last layer and dividing output by 100'
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [64, 128]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/pyr_abl_64_cape_f'
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/128_512_cape_f'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/female'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_cape_f'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_cape_f'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_cape_f'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = None # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/64_512_cape_f'#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,183 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '1'
|
||||
config['name'] = 'pyr_abl_64_128_cape_m'
|
||||
config['notes'] = ''
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [64, 128]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/pyr_abl_64_cape_m'
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/128_512_cape_m'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/male'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/test/male'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/test/male'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_cape_m'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_cape_m'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_cape_m'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = None # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
config['pyramid']['noise_amount'] = 0.025
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = 'checkpoints/64_512_cape_m'#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,181 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '3'
|
||||
config['name'] = 'pyr_abl_64_cape_f'
|
||||
config['notes'] = ''
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [64]
|
||||
config['pyramid']['pretrained_pyramid'] = ''
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/64_512_cape_f'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/female'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_cape_f'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_cape_f'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_cape_f'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = None # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,182 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '3'
|
||||
config['name'] = 'pyr_abl_64_cape_m'
|
||||
config['notes'] = ''
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK IF SKIRT
|
||||
# DON'T FORGET TO CHECK IF CAPE
|
||||
# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
|
||||
# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = False
|
||||
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [64]
|
||||
config['pyramid']['pretrained_pyramid'] = ''
|
||||
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/64_512_cape_m'
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/male'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/test/male'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/test/male'
|
||||
config['batch_size'] = 4
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['pyramid']['static_model'] = 'checkpoints/static_1_cape_m'
|
||||
config['pyramid']['body_model'] = 'checkpoints/body_1_cape_m'
|
||||
config['pyramid']['curvature_model'] = 'checkpoints/curv_1_cape_m'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['resolution'] = None
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['lr'] = 0.0001
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['reg_loss_coeff'] = None # set to 0 if don't want to use edge+collision
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'mesh_unposed': (config['smpl_res'], 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
config['pyramid']['is_label'] = False
|
||||
config['pyramid']['latent_dim'] = config['latent_dim']
|
||||
config['pyramid']['add_noise'] = True
|
||||
|
||||
config['pyramid']['loss_weights'] = [1,1,1,1,1]
|
||||
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res != 512:
|
||||
res_modifier = '_' + str(res)
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
|
||||
config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
|
||||
|
||||
|
||||
|
||||
config['pyramid']['freeze_encoders'] = True
|
||||
|
||||
config['pyramid']['levels'] = []
|
||||
for res in config['pyramid']['resolutions']:
|
||||
if res == 512:
|
||||
level = dict()
|
||||
level['resolution'] = 512
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (16, 8, 80)
|
||||
level['decoder_depths'] = [3, 3, 9, 3]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 256:
|
||||
level = dict()
|
||||
level['resolution'] = 256
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 7
|
||||
level['encoder_depths'] = [9, 9, 9, 9]
|
||||
level['encoder_dims'] = [32, 64, 128, 256]
|
||||
level['decoder_input'] = (8, 4, 128)
|
||||
level['decoder_depths'] = [9, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64, 16]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 128:
|
||||
level = dict()
|
||||
level['resolution'] = 128
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [16, 9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 128)
|
||||
level['decoder_depths'] = [16, 9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 64:
|
||||
level = dict()
|
||||
level['resolution'] = 64
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 5
|
||||
level['encoder_depths'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [64, 128, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9, 9]
|
||||
level['decoder_dims'] = [256, 128, 64]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
|
||||
level['upscale_enhancer_freeze'] = False
|
||||
config['pyramid']['levels'].append(level)
|
||||
elif res == 32:
|
||||
level = dict()
|
||||
level['resolution'] = 32
|
||||
level['latent_dim'] = config['latent_dim']
|
||||
level['kernel_size'] = 3
|
||||
level['encoder_depths'] = [9, 9]
|
||||
level['encoder_dims'] = [256, 256]
|
||||
level['decoder_input'] = (4, 2, 256)
|
||||
level['decoder_depths'] = [9, 9]
|
||||
level['decoder_dims'] = [256, 256]
|
||||
level['avg_garment_path'] = ''
|
||||
level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
|
||||
level['upscale_enhancer_freeze'] = True
|
||||
config['pyramid']['levels'].append(level)
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,116 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = False # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
|
||||
config['gpu'] = '6'
|
||||
config['name'] = 'abl_skin'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = '' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1'
|
||||
config['body_model'] = 'checkpoints/body_1'
|
||||
config['curvature_model'] = 'checkpoints/curv_1'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,114 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = False # and deshaping
|
||||
config['remove_global_orientation'] = False
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
|
||||
config['gpu'] = '2'
|
||||
config['name'] = 'abl_skin_no_orient'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = '' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1'
|
||||
config['body_model'] = 'checkpoints/body_1'
|
||||
config['curvature_model'] = 'checkpoints/curv_1'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,116 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = False # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = True
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
|
||||
config['gpu'] = '3'
|
||||
config['name'] = 'abl_skin_norm'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = '' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1'
|
||||
config['body_model'] = 'checkpoints/body_1'
|
||||
config['curvature_model'] = 'checkpoints/curv_1'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,116 @@
|
||||
config_a = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config_a['use_skinning'] = False # and deshaping
|
||||
config_a['remove_global_orientation'] = True
|
||||
config_a['use_curvature'] = True
|
||||
config_a['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config_a['use_offsets'] = True
|
||||
|
||||
config_a['use_norm_loss'] = False
|
||||
|
||||
ablation_count = [config_a['use_skinning'], config_a['remove_global_orientation'], config_a['use_curvature'], config_a['use_extra_losses'], config_a['use_offsets']].count(False)
|
||||
|
||||
config_a['gpu'] = '4'
|
||||
config_a['name'] = 'abl_skin_skirt'
|
||||
config_a['notes'] = ''
|
||||
|
||||
config_a['avg_garment_path'] = '' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config_a['use_skinning']:
|
||||
assert (config_a['use_offsets'] and config_a['avg_garment_path'] != '') or (not config_a['use_offsets'] and config_a['avg_garment_path'] == '')
|
||||
|
||||
config_a['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config_a['batch_size'] = 4
|
||||
config_a['resolution'] = 512
|
||||
config_a['is_skirt'] = True
|
||||
config_a['dataset_in_memory'] = False
|
||||
config_a['is_cape'] = False
|
||||
|
||||
config_a['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config_a['valid_dir'] = '/home/workspace/local-data/valid_skirt'
|
||||
config_a['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
|
||||
|
||||
config_a['static_model'] = 'checkpoints/static_1_skirt'
|
||||
config_a['body_model'] = 'checkpoints/body_1_skirt_2_2'
|
||||
config_a['curvature_model'] = 'checkpoints/curv_1_skirt'
|
||||
|
||||
|
||||
config_a['smpl_res'] = 14475
|
||||
if config_a['is_cape']:
|
||||
config_a['smpl_res'] = 3638
|
||||
|
||||
config_a['latent_dim'] = 128
|
||||
|
||||
config_a['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config_a['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config_a['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config_a['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config_a['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config_a['use_skinning']:
|
||||
config_a['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config_a['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config_a['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config_a['upscale_enhancer'] = ''
|
||||
config_a['freeze_encoders'] = True
|
||||
config_a['use_one_hot'] = False
|
||||
|
||||
config_a['cvae'] = dict()
|
||||
config_a['cvae']['is_label'] = False
|
||||
config_a['cvae']['latent_dim'] = config_a['latent_dim']
|
||||
config_a['cvae']['add_noise'] = True
|
||||
config_a['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config_a['cvae']['kernel_size'] = 7
|
||||
config_a['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config_a['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config_a['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config_a['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config_a['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config_a['cond_ae'] = dict()
|
||||
config_a['cond_ae']['is_label'] = False
|
||||
config_a['cond_ae']['upscale_output'] = False
|
||||
config_a['cond_ae']['latent_dim'] = config_a['latent_dim']
|
||||
config_a['cond_ae']['kernel_size'] = 7
|
||||
config_a['cond_ae']['bottleneck_size'] = 64
|
||||
config_a['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config_a['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config_a['cond_ae']['bottleneck_size']]
|
||||
config_a['cond_ae']['decoder_input'] = (8, 4, config_a['cond_ae']['bottleneck_size'])
|
||||
config_a['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config_a['cond_ae']['decoder_dims'] = [config_a['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config_a['cond_ae_body'] = dict()
|
||||
config_a['cond_ae_body']['latent_dim'] = config_a['latent_dim']
|
||||
config_a['cond_ae_body']['kernel_size'] = 7
|
||||
config_a['cond_ae_body']['upscale_output'] = True
|
||||
config_a['cond_ae_body']['bottleneck_size'] = 512
|
||||
config_a['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config_a['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config_a['cond_ae_body']['bottleneck_size']]
|
||||
config_a['cond_ae_body']['decoder_input'] = (4, 2, config_a['cond_ae_body']['bottleneck_size'])
|
||||
config_a['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config_a['cond_ae_body']['decoder_dims'] = [config_a['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,116 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = False # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
|
||||
config['gpu'] = '2'
|
||||
config['name'] = 'abl_skin_var'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = '' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1'
|
||||
config['body_model'] = 'checkpoints/body_1'
|
||||
config['curvature_model'] = 'checkpoints/curv_1'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.01
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = False
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,116 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = False # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
|
||||
config['gpu'] = '3'
|
||||
config['name'] = 'abl_skin_var_2'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = '' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1'
|
||||
config['body_model'] = 'checkpoints/body_1'
|
||||
config['curvature_model'] = 'checkpoints/curv_1'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = 'checkpoints/abl_skin'
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.01
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = False
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,116 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = False # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
|
||||
config['gpu'] = '3'
|
||||
config['name'] = 'abl_skin_var_3'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = '' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1'
|
||||
config['body_model'] = 'checkpoints/body_1'
|
||||
config['curvature_model'] = 'checkpoints/curv_1'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = 'checkpoints/abl_skin'
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 1.0
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = False
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,117 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = False # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
|
||||
config['gpu'] = '2'
|
||||
config['name'] = 'abl_skin_var_4'
|
||||
config['notes'] = 'lower noise, don\'t increase balancing coeff'
|
||||
|
||||
config['avg_garment_path'] = '' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1'
|
||||
config['body_model'] = 'checkpoints/body_1'
|
||||
config['curvature_model'] = 'checkpoints/curv_1'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.01
|
||||
config['balancing_activation_limit'] = 0.0
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = False
|
||||
config['cvae']['noise_amount'] = 0.001
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,48 @@
|
||||
from configs.config_base import config
|
||||
|
||||
config['gpu'] = '2'
|
||||
config['lr'] = 0.0001
|
||||
config['name'] = 'body_1_skirt_2_2'
|
||||
|
||||
config['notes'] = 'convnext + convnext, add dense with tanh at the end of reverse convnext, | \
|
||||
flattened bottleneck with 128 latent_dim\ remove global orientation | \
|
||||
fixed gender issue with deoriented bodies, again, aaand again | \
|
||||
trained on 100 garments | \
|
||||
remove multiplications with garment uv mask | \
|
||||
larger bottleneck, low res output upscaled | \
|
||||
larger batch size, 32 instead of 4 | \
|
||||
calculate euclidean error on whole body, not just garment masked | \
|
||||
continued from body_1_skirt_2 | \
|
||||
'
|
||||
|
||||
config['dataset_in_memory'] = False
|
||||
config['batch_size'] = 32
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (3, 512, 256,),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
}
|
||||
config['signature_static'] = {
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
}
|
||||
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['upscale_output'] = True
|
||||
config['cond_ae']['bottleneck_size'] = 512
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (4, 2, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 128, 64, 16]
|
||||
# config['cond_ae_body'] = dict()
|
||||
# config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
# config['cond_ae_body']['kernel_size'] = 7
|
||||
# config['cond_ae_body']['upscale_output'] = True
|
||||
# config['cond_ae_body']['bottleneck_size'] = 512
|
||||
# config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
# config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
# config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
# config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
# config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,55 @@
|
||||
config = dict()
|
||||
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
config['use_filled'] = False
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
config['remove_global_orientation'] = True
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 16
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [16, 32, 64, 128, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_depths'] = config['cond_ae']['encoder_depths']
|
||||
config['cond_ae']['decoder_dims'] = config['cond_ae']['encoder_dims']
|
||||
config['cond_ae']['activation'] = 'tanh'
|
||||
|
||||
|
||||
config['gpu'] = '2'
|
||||
config['lr'] = 0.0001
|
||||
config['name'] = 'body_post_2'
|
||||
config['notes'] = 'convnext + convnext, | \
|
||||
\
|
||||
| \
|
||||
deeper model | \
|
||||
| \
|
||||
'
|
||||
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (3, 512, 256,),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
}
|
||||
config['signature_static'] = {
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
}
|
||||
@@ -0,0 +1,19 @@
|
||||
from configs.config_base import config
|
||||
|
||||
config['gpu'] = '5'
|
||||
config['lr'] = 0.001
|
||||
config['name'] = 'curv_1' #'ae_curv_9'
|
||||
config['notes'] = 'convnext + convnext, 16*8*32, ce loss. flattened latent dim of 128. trained on 100 garments. switched back to sparse CCE, normal one was giving NaN | \
|
||||
| \
|
||||
'
|
||||
|
||||
config['cond_ae']['is_label'] = True
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
'mesh_curvature': (config['smpl_res'])
|
||||
}
|
||||
config['signature_static'] = { 'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
@@ -0,0 +1,54 @@
|
||||
config = dict()
|
||||
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
config['use_filled'] = False
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
config['remove_global_orientation'] = True
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = True
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 40
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [16, 32, 64, 128, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_depths'] = config['cond_ae']['encoder_depths']
|
||||
config['cond_ae']['decoder_dims'] = config['cond_ae']['encoder_dims']
|
||||
config['cond_ae']['activation'] = 'tanh'
|
||||
|
||||
|
||||
config['gpu'] = '3'
|
||||
config['lr'] = 0.001
|
||||
config['name'] = 'curv_post_1'
|
||||
config['notes'] = 'convnext + convnext, | \
|
||||
\
|
||||
| \
|
||||
deeper model | \
|
||||
| \
|
||||
'
|
||||
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
'mesh_curvature': (config['smpl_res'])
|
||||
}
|
||||
config['signature_static'] = { 'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
@@ -0,0 +1,53 @@
|
||||
config = dict()
|
||||
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
config['use_filled'] = False
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = True
|
||||
config['is_cape'] = False
|
||||
config['remove_global_orientation'] = True
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 8
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 3, 27, 3]
|
||||
config['cond_ae']['encoder_dims'] = [8, 16, 32, 32, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_depths'] = config['cond_ae']['encoder_depths']
|
||||
config['cond_ae']['decoder_dims'] = config['cond_ae']['encoder_dims']
|
||||
config['cond_ae']['activation'] = 'linear'
|
||||
|
||||
|
||||
config['gpu'] = '5'
|
||||
config['lr'] = 0.0005
|
||||
config['name'] = 'static_post_4'
|
||||
config['notes'] = 'convnext + convnext, | \
|
||||
\
|
||||
| \
|
||||
deeper model | \
|
||||
linear activation| \
|
||||
'
|
||||
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (), }
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_static': (config['smpl_res'], 3,),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
@@ -0,0 +1,60 @@
|
||||
config = dict()
|
||||
|
||||
|
||||
config['batch_size'] = 4
|
||||
# config['train_dir'] = '/home/workspace/local-data/cape_processed/train/female'
|
||||
# config['valid_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
# config['test_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
# config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
# config['valid_dir'] = '/home/workspace/local-data/valid_skirt'
|
||||
# config['test_dir'] = '/home/workspace/local-data/test_skirt_ready'
|
||||
config['use_filled'] = False
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
# config['cond_ae'] = dict()
|
||||
# config['cond_ae']['is_label'] = False
|
||||
# config['cond_ae']['upscale_output'] = False
|
||||
# config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
# config['cond_ae']['kernel_size'] = 7
|
||||
# config['cond_ae']['bottleneck_size'] = 64
|
||||
# config['cond_ae']['encoder_depths'] = [3, 3, 3, 3, 3]
|
||||
# config['cond_ae']['encoder_dims'] = [16, 32, 128, 128, config['cond_ae']['bottleneck_size']]
|
||||
# config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
# config['cond_ae']['decoder_depths'] = [3, 3, 3, 3, 3]
|
||||
# config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 128, 128, 32, 8]
|
||||
|
||||
# config['cond_ae_body'] = config['cond_ae']
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,122 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = False # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '0'
|
||||
config['name'] = 'cape_f_03223_SL_2'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_cape_f_03223_SL_2_no_shape_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['dataset_in_memory'] = True
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/female'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/train/female'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/train/female'
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['frames_file'] = 'frames_03223_SL_train_2.txt'
|
||||
config['frames_file_valid'] = 'frames_03223_SL_test_2.txt'
|
||||
config['frames_file_test'] = 'frames_03223_SL_test_2.txt'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1_cape_f'
|
||||
config['body_model'] = 'checkpoints/body_1_cape_f'
|
||||
config['curvature_model'] = 'checkpoints/curv_1_cape_f'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['balancing_activation_limit'] = 0.005
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (config['smpl_res'], 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,120 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = False # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '4'
|
||||
config['name'] = 'cape_f_03223_SS'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_cape_f_03223_SS_no_shape_skirt_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['dataset_in_memory'] = True
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/female'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/test/female'
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['frames_file'] = 'frames_03223_SS.txt'
|
||||
config['frames_file_valid'] = 'frames_03223_SS.txt'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1_cape_f'
|
||||
config['body_model'] = 'checkpoints/body_1_cape_f'
|
||||
config['curvature_model'] = 'checkpoints/curv_1_cape_f'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (config['smpl_res'], 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,122 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = False # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '0'
|
||||
config['name'] = 'cape_f_03223_SS_2'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_cape_f_03223_SS_2_no_shape_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['dataset_in_memory'] = True
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/female'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/train/female'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/train/female'
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['frames_file'] = 'frames_03223_SS_train_2.txt'
|
||||
config['frames_file_valid'] = 'frames_03223_SS_test_2.txt'
|
||||
config['frames_file_test'] = 'frames_03223_SS_test_2.txt'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1_cape_f'
|
||||
config['body_model'] = 'checkpoints/body_1_cape_f'
|
||||
config['curvature_model'] = 'checkpoints/curv_1_cape_f'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['balancing_activation_limit'] = 0.005
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (config['smpl_res'], 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,121 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = False # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '1'
|
||||
config['name'] = 'cape_m_00032_SL'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_cape_m_00032_SL_no_shape_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['dataset_in_memory'] = True
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/male'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/train/male'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/train/male'
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['frames_file'] = 'frames_00032_SL_train.txt'
|
||||
config['frames_file_valid'] = 'frames_00032_SL_test.txt'
|
||||
config['frames_file_test'] = 'frames_00032_SL_test.txt'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1_cape_m'
|
||||
config['body_model'] = 'checkpoints/body_1_cape_m'
|
||||
config['curvature_model'] = 'checkpoints/curv_1_cape_m'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (config['smpl_res'], 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,122 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = True # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = False # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
config['use_norm_loss'] = False
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '0'
|
||||
config['name'] = 'cape_m_00032_SL_2'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = 'custom_data/train_cape_m_00032_SL_2_no_shape_avg_uv.npy' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['dataset_in_memory'] = True
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/cape_processed/train/male'
|
||||
config['valid_dir'] = '/home/workspace/local-data/cape_processed/train/male'
|
||||
config['test_dir'] = '/home/workspace/local-data/cape_processed/train/male'
|
||||
config['is_skirt'] = False
|
||||
config['is_cape'] = True
|
||||
|
||||
config['frames_file'] = 'frames_00032_SL_train_2.txt'
|
||||
config['frames_file_valid'] = 'frames_00032_SL_test_2.txt'
|
||||
config['frames_file_test'] = 'frames_00032_SL_test_2.txt'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1_cape_m'
|
||||
config['body_model'] = 'checkpoints/body_1_cape_m'
|
||||
config['curvature_model'] = 'checkpoints/curv_1_cape_m'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
config['balancing_activation_limit'] = 0.005
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (config['smpl_res'], 3,),
|
||||
'mesh_posed': (config['smpl_res'], 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (config['smpl_res'],),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (config['smpl_res'], 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,190 @@
|
||||
{
|
||||
"batch_size": 4,
|
||||
"train_dir": "/home/workspace/local-data/train",
|
||||
"valid_dir": "/home/workspace/local-data/valid",
|
||||
"test_dir": "/home/workspace/data/dataset/test_ready",
|
||||
"use_filled": false,
|
||||
"resolution": 512,
|
||||
"is_skirt": false,
|
||||
"dataset_in_memory": false,
|
||||
"is_cape": false,
|
||||
"smpl_res": 14475,
|
||||
"latent_dim": 128,
|
||||
"cond_ae": {
|
||||
"is_label": false,
|
||||
"upscale_output": false,
|
||||
"latent_dim": 128,
|
||||
"kernel_size": 7,
|
||||
"bottleneck_size": 64,
|
||||
"encoder_depths": [
|
||||
3,
|
||||
3,
|
||||
9,
|
||||
9,
|
||||
3
|
||||
],
|
||||
"encoder_dims": [
|
||||
32,
|
||||
64,
|
||||
128,
|
||||
256,
|
||||
64
|
||||
],
|
||||
"decoder_input": [
|
||||
8,
|
||||
4,
|
||||
64
|
||||
],
|
||||
"decoder_depths": [
|
||||
3,
|
||||
3,
|
||||
9,
|
||||
3,
|
||||
3
|
||||
],
|
||||
"decoder_dims": [
|
||||
64,
|
||||
256,
|
||||
128,
|
||||
64,
|
||||
16
|
||||
]
|
||||
},
|
||||
"cond_ae_body": {
|
||||
"latent_dim": 128,
|
||||
"kernel_size": 7,
|
||||
"upscale_output": true,
|
||||
"bottleneck_size": 512,
|
||||
"encoder_depths": [
|
||||
3,
|
||||
3,
|
||||
9,
|
||||
9,
|
||||
3,
|
||||
3
|
||||
],
|
||||
"encoder_dims": [
|
||||
32,
|
||||
64,
|
||||
128,
|
||||
256,
|
||||
256,
|
||||
512
|
||||
],
|
||||
"decoder_input": [
|
||||
4,
|
||||
2,
|
||||
512
|
||||
],
|
||||
"decoder_depths": [
|
||||
3,
|
||||
3,
|
||||
9,
|
||||
3
|
||||
],
|
||||
"decoder_dims": [
|
||||
512,
|
||||
128,
|
||||
64,
|
||||
16
|
||||
]
|
||||
},
|
||||
"gpu": "0",
|
||||
"name": "v2_7_4_3",
|
||||
"notes": "offsets over average unposed garment. remove global orientation (in posed body input and in pose_shape parameters. | retrained body encoder with deoriented bodies | use mean l2 loss. small batch. l2 * 1000, balancing to 1 from 0.01 | fixed gender issue and retrained body encoder, FINAL | remove shape from unposed garment | training on 100 garments with offsets over the average of these | fixed autoencoders!!!!!!!!! | cvae only loads encoders instead AEs | increase balancing coeff sooner | use 3d mesh loss | add final gc layer | starting from v2_5_2, add tanh to cond_enc last layer | NOT using one-hot skinning | using new average garment with one-hot versions | fix collision for plotting | use 3d mesh loss | ",
|
||||
"pretrained_model": "checkpoints/v2_5_2",
|
||||
"reg_loss_coeff": 0.1,
|
||||
"l2_coeff": 1,
|
||||
"lr": 0.0001,
|
||||
"starting_balancing_coeff": 0.0001,
|
||||
"signature_dynamic": {
|
||||
"id": [],
|
||||
"pose_shape": [
|
||||
83
|
||||
],
|
||||
"uv_body_posed": [
|
||||
512,
|
||||
256,
|
||||
3
|
||||
],
|
||||
"mesh_body_posed": [
|
||||
14475,
|
||||
3
|
||||
],
|
||||
"mesh_posed": [
|
||||
14475,
|
||||
3
|
||||
],
|
||||
"mesh_unposed": [
|
||||
14475,
|
||||
3
|
||||
],
|
||||
"uv_unposed": [
|
||||
512,
|
||||
256,
|
||||
3
|
||||
],
|
||||
"uv_curvature": [
|
||||
512,
|
||||
256,
|
||||
7
|
||||
]
|
||||
},
|
||||
"signature_static": {
|
||||
"uv_static": [
|
||||
512,
|
||||
256,
|
||||
3
|
||||
],
|
||||
"mesh_mask": [
|
||||
14475
|
||||
],
|
||||
"uv_mask": [
|
||||
512,
|
||||
256
|
||||
]
|
||||
},
|
||||
"avg_garment_path": "custom_data/train_no_shape_avg_uv.npy",
|
||||
"static_model": "checkpoints/static_1",
|
||||
"body_model": "checkpoints/body_1",
|
||||
"curvature_model": "checkpoints/curv_1",
|
||||
"upscale_enhancer": "",
|
||||
"freeze_encoders": true,
|
||||
"use_one_hot": false,
|
||||
"cvae": {
|
||||
"is_label": false,
|
||||
"latent_dim": 128,
|
||||
"add_noise": true,
|
||||
"noise_amount": 0.025,
|
||||
"kernel_size": 7,
|
||||
"encoder_depths": [
|
||||
3,
|
||||
3,
|
||||
9,
|
||||
3
|
||||
],
|
||||
"encoder_dims": [
|
||||
32,
|
||||
64,
|
||||
128,
|
||||
256
|
||||
],
|
||||
"decoder_input": [
|
||||
16,
|
||||
8,
|
||||
80
|
||||
],
|
||||
"decoder_depths": [
|
||||
3,
|
||||
3,
|
||||
9,
|
||||
3
|
||||
],
|
||||
"decoder_dims": [
|
||||
256,
|
||||
128,
|
||||
64,
|
||||
16
|
||||
]
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,113 @@
|
||||
from configs.config_base import config
|
||||
|
||||
config['gpu'] = '1'
|
||||
config['name'] = 'v2_7_4_4'
|
||||
config['notes'] = '\
|
||||
offsets over average unposed garment. remove global orientation (in posed body input and in pose_shape parameters. | \
|
||||
retrained body encoder with deoriented bodies | \
|
||||
use mean l2 loss. small batch. l2 * 1000, balancing to 1 from 0.01 | \
|
||||
fixed gender issue and retrained body encoder, FINAL | \
|
||||
remove shape from unposed garment | \
|
||||
training on 100 garments with offsets over the average of these | \
|
||||
fixed autoencoders!!!!!!!!! | \
|
||||
cvae only loads encoders instead AEs | \
|
||||
increase balancing coeff sooner | \
|
||||
use 3d mesh loss | \
|
||||
add final gc layer | \
|
||||
starting from v2_5_2, add tanh to cond_enc last layer | \
|
||||
NOT using one-hot skinning | \
|
||||
using new average garment with one-hot versions | \
|
||||
fix collision for plotting | \
|
||||
use 3d mesh loss | \
|
||||
higher reg coeff | \
|
||||
'
|
||||
config['dataset_in_memory'] = False
|
||||
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['pretrained_model'] = 'checkpoints/v2_5_2'
|
||||
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['reg_loss_coeff'] = 1 # set to 0 if don't want to use edge+collision
|
||||
config['l2_coeff'] = 1
|
||||
|
||||
if config['resolution'] != 512:
|
||||
config['notes'] += '\
|
||||
using custom enhancer for upscaling, using not filled versions\
|
||||
'
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'mesh_unposed': (14475, 3,),
|
||||
'uv_unposed': (512, 256, 3),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['resolution'] != 512:
|
||||
res_modifier = '_' + str(config['resolution'])
|
||||
config['signature_dynamic']['uv_body_posed' + res_modifier] = (config['resolution'], config['resolution']//2, 3)
|
||||
config['signature_dynamic']['uv_unposed' + res_modifier] = (config['resolution'], config['resolution']//2, 3)
|
||||
config['signature_dynamic']['uv_curvature' + res_modifier] = (config['resolution'], config['resolution']//2)
|
||||
config['signature_static']['uv_static' + res_modifier] = (config['resolution'], config['resolution']//2, 3)
|
||||
config['signature_static']['uv_mask' + res_modifier] = (config['resolution'], config['resolution']//2)
|
||||
|
||||
if config['resolution'] == 512:
|
||||
config['avg_garment_path'] = 'custom_data/train_no_shape_avg_uv.npy' # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
else:
|
||||
config['avg_garment_path'] = ''
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1'
|
||||
config['body_model'] = 'checkpoints/body_1'
|
||||
config['curvature_model'] = 'checkpoints/curv_1'
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
if config['resolution'] == 512:
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
elif config['resolution'] == 128:
|
||||
config['cvae']['kernel_size'] = 5
|
||||
config['cvae']['encoder_depths'] = [16, 16, 9, 9]
|
||||
config['cvae']['encoder_dims'] = [64, 128, 256, 256]
|
||||
config['cvae']['decoder_input'] = (4, 2, 128)
|
||||
config['cvae']['decoder_depths'] = [16, 16, 9, 9]
|
||||
config['cvae']['decoder_dims'] = [256, 256, 128, 64]
|
||||
elif config['resolution'] == 32:
|
||||
config['cvae']['kernel_size'] = 3
|
||||
config['cvae']['encoder_depths'] = [27, 27]
|
||||
config['cvae']['encoder_dims'] = [256, 256]
|
||||
config['cvae']['decoder_input'] = (4, 2, 256)
|
||||
config['cvae']['decoder_depths'] = [27, 27]
|
||||
config['cvae']['decoder_dims'] = [256, 256]
|
||||
else:
|
||||
raise NotImplementedError
|
||||
@@ -0,0 +1 @@
|
||||
{"batch_size": 4, "train_dir": "/home/workspace/local-data/train", "valid_dir": "/home/workspace/local-data/valid", "test_dir": "/home/workspace/data/dataset/test_ready", "use_filled": false, "resolution": 512, "is_skirt": false, "dataset_in_memory": false, "is_cape": false, "smpl_res": 14475, "latent_dim": 128, "cond_ae": {"is_label": false, "upscale_output": false, "latent_dim": 128, "kernel_size": 7, "bottleneck_size": 64, "encoder_depths": [3, 3, 9, 9, 3], "encoder_dims": [32, 64, 128, 256, 64], "decoder_input": [8, 4, 64], "decoder_depths": [3, 3, 9, 3, 3], "decoder_dims": [64, 256, 128, 64, 16]}, "cond_ae_body": {"latent_dim": 128, "kernel_size": 7, "upscale_output": true, "bottleneck_size": 512, "encoder_depths": [3, 3, 9, 9, 3, 3], "encoder_dims": [32, 64, 128, 256, 256, 512], "decoder_input": [4, 2, 512], "decoder_depths": [3, 3, 9, 3], "decoder_dims": [512, 128, 64, 16]}, "gpu": "0", "name": "v2_7_4_3", "notes": "offsets over average unposed garment. remove global orientation (in posed body input and in pose_shape parameters. | retrained body encoder with deoriented bodies | use mean l2 loss. small batch. l2 * 1000, balancing to 1 from 0.01 | fixed gender issue and retrained body encoder, FINAL | remove shape from unposed garment | training on 100 garments with offsets over the average of these | fixed autoencoders!!!!!!!!! | cvae only loads encoders instead AEs | increase balancing coeff sooner | use 3d mesh loss | add final gc layer | starting from v2_5_2, add tanh to cond_enc last layer | NOT using one-hot skinning | using new average garment with one-hot versions | fix collision for plotting | use 3d mesh loss | ", "pretrained_model": "checkpoints/v2_5_2", "reg_loss_coeff": 0.1, "l2_coeff": 1, "lr": 0.0001, "starting_balancing_coeff": 0.0001, "signature_dynamic": {"id": [], "pose_shape": [83], "uv_body_posed": [512, 256, 3], "mesh_body_posed": [14475, 3], "mesh_posed": [14475, 3], "mesh_unposed": [14475, 3], "uv_unposed": [512, 256, 3], "uv_curvature": [512, 256, 7]}, "signature_static": {"uv_static": [512, 256, 3], "mesh_mask": [14475], "uv_mask": [512, 256]}, "avg_garment_path": "custom_data/train_no_shape_avg_uv.npy", "static_model": "checkpoints/static_1", "body_model": "checkpoints/body_1", "curvature_model": "checkpoints/curv_1", "upscale_enhancer": "", "freeze_encoders": true, "use_one_hot": false, "cvae": {"is_label": false, "latent_dim": 128, "add_noise": true, "noise_amount": 0.025, "kernel_size": 7, "encoder_depths": [3, 3, 9, 3], "encoder_dims": [32, 64, 128, 256], "decoder_input": [16, 8, 80], "decoder_depths": [3, 3, 9, 3], "decoder_dims": [256, 128, 64, 16]}}
|
||||
@@ -0,0 +1,95 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '2'
|
||||
config['name'] = 'cvae_curv_8'
|
||||
config['notes'] = 'no activation for decoder, softmax at the very end, lower balancing, output only 6 values, concatenate background | \
|
||||
same as 3 but use ce loss | \
|
||||
add ce mesh loss | \
|
||||
higher balancing coeff | \
|
||||
start from curv_5, but higher balancing '
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1'
|
||||
config['body_model'] = 'checkpoints/body_1'
|
||||
config['curvature_model'] = 'checkpoints/curv_1'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = 'checkpoints/cvae_curv_5'
|
||||
config['pretrained_model_iteration'] = '100000'
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.25
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
# 'mesh_curvature': (14475)
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = True
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.001
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
@@ -0,0 +1,115 @@
|
||||
config = dict()
|
||||
|
||||
# DON'T FORGET TO RESET SSIM LOSS USAGE
|
||||
# DON'T FORGET TO CHECK MODEL LOADING
|
||||
# DON'T FORGET TO CHECK IF STORE IN MEMORY
|
||||
# DON'T FORGET TO CHECK REG LOSS COEFF
|
||||
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
|
||||
# DON'T FORGET TO CHECK AVG GARMENT USED
|
||||
|
||||
config['use_skinning'] = False # and deshaping
|
||||
config['remove_global_orientation'] = True
|
||||
config['use_curvature'] = True
|
||||
config['use_extra_losses'] = True # edge, collision, 3d mesh
|
||||
config['use_offsets'] = True
|
||||
|
||||
ablation_count = [config['use_skinning'], config['remove_global_orientation'], config['use_curvature'], config['use_extra_losses'], config['use_offsets']].count(False)
|
||||
assert ablation_count == 1 or ablation_count == 0
|
||||
|
||||
config['gpu'] = '2'
|
||||
config['name'] = 'test'
|
||||
config['notes'] = ''
|
||||
|
||||
config['avg_garment_path'] = '' #custom_data/train_no_shape_avg_uv.npy # train_no_shape_avg_uv train_no_shape_one_hot_avg_uv
|
||||
if config['use_skinning']:
|
||||
assert (config['use_offsets'] and config['avg_garment_path'] != '') or (not config['use_offsets'] and config['avg_garment_path'] == '')
|
||||
|
||||
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
|
||||
|
||||
config['batch_size'] = 4
|
||||
config['resolution'] = 512
|
||||
config['is_skirt'] = False
|
||||
config['dataset_in_memory'] = False
|
||||
config['is_cape'] = False
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
|
||||
|
||||
config['static_model'] = 'checkpoints/static_1'
|
||||
config['body_model'] = 'checkpoints/body_1'
|
||||
config['curvature_model'] = 'checkpoints/curv_1'
|
||||
|
||||
|
||||
config['smpl_res'] = 14475
|
||||
if config['is_cape']:
|
||||
config['smpl_res'] = 3638
|
||||
|
||||
config['latent_dim'] = 128
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
|
||||
###############
|
||||
config['lr'] = 0.0001# 0.0001
|
||||
###############
|
||||
config['starting_balancing_coeff'] = 0.0001
|
||||
|
||||
config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
|
||||
'pose_shape': (72 + 11,),
|
||||
'uv_body_posed': (512, 256, 3),
|
||||
'mesh_body_posed': (14475, 3,),
|
||||
'mesh_posed': (14475, 3,),
|
||||
'uv_curvature': (512, 256, 7),
|
||||
}
|
||||
config['signature_static'] = { 'uv_static': (512, 256, 3),
|
||||
'mesh_mask': (14475,),
|
||||
'uv_mask': (512, 256,),
|
||||
}
|
||||
|
||||
if config['use_skinning']:
|
||||
config['signature_dynamic']['uv_unposed'] = (512, 256, 3)
|
||||
config['signature_dynamic']['mesh_unposed'] = (14475, 3,)
|
||||
else:
|
||||
config['signature_dynamic']['uv_posed'] = (512, 256, 3)
|
||||
|
||||
|
||||
config['upscale_enhancer'] = ''
|
||||
config['freeze_encoders'] = True
|
||||
config['use_one_hot'] = False
|
||||
|
||||
config['cvae'] = dict()
|
||||
config['cvae']['is_label'] = False
|
||||
config['cvae']['latent_dim'] = config['latent_dim']
|
||||
config['cvae']['add_noise'] = True
|
||||
config['cvae']['noise_amount'] = 0.025
|
||||
|
||||
config['cvae']['kernel_size'] = 7
|
||||
config['cvae']['encoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['encoder_dims'] = [32, 64, 128, 256]
|
||||
config['cvae']['decoder_input'] = (16, 8, 80)
|
||||
config['cvae']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cvae']['decoder_dims'] = [256, 128, 64, 16]
|
||||
|
||||
|
||||
config['cond_ae'] = dict()
|
||||
config['cond_ae']['is_label'] = False
|
||||
config['cond_ae']['upscale_output'] = False
|
||||
config['cond_ae']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae']['kernel_size'] = 7
|
||||
config['cond_ae']['bottleneck_size'] = 64
|
||||
config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
|
||||
config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
|
||||
config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
|
||||
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
|
||||
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
|
||||
|
||||
config['cond_ae_body'] = dict()
|
||||
config['cond_ae_body']['latent_dim'] = config['latent_dim']
|
||||
config['cond_ae_body']['kernel_size'] = 7
|
||||
config['cond_ae_body']['upscale_output'] = True
|
||||
config['cond_ae_body']['bottleneck_size'] = 512
|
||||
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
|
||||
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
|
||||
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
|
||||
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
|
||||
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user