102 lines
3.8 KiB
Python
102 lines
3.8 KiB
Python
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['batch_size'] = 4
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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['use_filled'] = False
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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['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['gpu'] = '1'
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config['name'] = 'ab_1'
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config['notes'] = ''
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config['pretrained_model'] = 'checkpoints/v2_5_2'
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config['resolution'] = 512
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config['is_skirt'] = False
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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['l2_coeff'] = 1
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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': (),
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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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'mesh_unposed': (14475, 3,),
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'uv_unposed': (512, 256, 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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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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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['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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