117 lines
4.6 KiB
Python
117 lines
4.6 KiB
Python
config_a = 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_a['use_skinning'] = False # and deshaping
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config_a['remove_global_orientation'] = True
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config_a['use_curvature'] = True
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config_a['use_extra_losses'] = True # edge, collision, 3d mesh
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config_a['use_offsets'] = True
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config_a['use_norm_loss'] = False
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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)
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config_a['gpu'] = '4'
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config_a['name'] = 'abl_skin_skirt'
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config_a['notes'] = ''
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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
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if config_a['use_skinning']:
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assert (config_a['use_offsets'] and config_a['avg_garment_path'] != '') or (not config_a['use_offsets'] and config_a['avg_garment_path'] == '')
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config_a['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
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config_a['batch_size'] = 4
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config_a['resolution'] = 512
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config_a['is_skirt'] = True
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config_a['dataset_in_memory'] = False
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config_a['is_cape'] = False
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config_a['train_dir'] = '/home/workspace/local-data/train_skirt'
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config_a['valid_dir'] = '/home/workspace/local-data/valid_skirt'
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config_a['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
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config_a['static_model'] = 'checkpoints/static_1_skirt'
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config_a['body_model'] = 'checkpoints/body_1_skirt_2_2'
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config_a['curvature_model'] = 'checkpoints/curv_1_skirt'
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config_a['smpl_res'] = 14475
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if config_a['is_cape']:
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config_a['smpl_res'] = 3638
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config_a['latent_dim'] = 128
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config_a['pretrained_model'] = ''
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###############
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config_a['lr'] = 0.0001# 0.0001
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###############
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config_a['starting_balancing_coeff'] = 0.0001
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config_a['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_a['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_a['use_skinning']:
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config_a['signature_dynamic']['uv_unposed'] = (512, 256, 3)
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config_a['signature_dynamic']['mesh_unposed'] = (14475, 3,)
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else:
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config_a['signature_dynamic']['uv_posed'] = (512, 256, 3)
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config_a['upscale_enhancer'] = ''
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config_a['freeze_encoders'] = True
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config_a['use_one_hot'] = False
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config_a['cvae'] = dict()
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config_a['cvae']['is_label'] = False
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config_a['cvae']['latent_dim'] = config_a['latent_dim']
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config_a['cvae']['add_noise'] = True
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config_a['cvae']['noise_amount'] = 0.025
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config_a['cvae']['kernel_size'] = 7
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config_a['cvae']['encoder_depths'] = [3, 3, 9, 3]
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config_a['cvae']['encoder_dims'] = [32, 64, 128, 256]
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config_a['cvae']['decoder_input'] = (16, 8, 80)
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config_a['cvae']['decoder_depths'] = [3, 3, 9, 3]
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config_a['cvae']['decoder_dims'] = [256, 128, 64, 16]
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config_a['cond_ae'] = dict()
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config_a['cond_ae']['is_label'] = False
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config_a['cond_ae']['upscale_output'] = False
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config_a['cond_ae']['latent_dim'] = config_a['latent_dim']
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config_a['cond_ae']['kernel_size'] = 7
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config_a['cond_ae']['bottleneck_size'] = 64
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config_a['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
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config_a['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config_a['cond_ae']['bottleneck_size']]
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config_a['cond_ae']['decoder_input'] = (8, 4, config_a['cond_ae']['bottleneck_size'])
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config_a['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
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config_a['cond_ae']['decoder_dims'] = [config_a['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
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config_a['cond_ae_body'] = dict()
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config_a['cond_ae_body']['latent_dim'] = config_a['latent_dim']
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config_a['cond_ae_body']['kernel_size'] = 7
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config_a['cond_ae_body']['upscale_output'] = True
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config_a['cond_ae_body']['bottleneck_size'] = 512
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config_a['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
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config_a['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config_a['cond_ae_body']['bottleneck_size']]
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config_a['cond_ae_body']['decoder_input'] = (4, 2, config_a['cond_ae_body']['bottleneck_size'])
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config_a['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
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config_a['cond_ae_body']['decoder_dims'] = [config_a['cond_ae_body']['bottleneck_size'], 128, 64, 16]
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