114 lines
4.5 KiB
Python
114 lines
4.5 KiB
Python
from configs.config_base import config
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config['gpu'] = '1'
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config['name'] = 'v2_7_4_4'
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config['notes'] = '\
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offsets over average unposed garment. remove global orientation (in posed body input and in pose_shape parameters. | \
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retrained body encoder with deoriented bodies | \
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use mean l2 loss. small batch. l2 * 1000, balancing to 1 from 0.01 | \
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fixed gender issue and retrained body encoder, FINAL | \
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remove shape from unposed garment | \
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training on 100 garments with offsets over the average of these | \
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fixed autoencoders!!!!!!!!! | \
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cvae only loads encoders instead AEs | \
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increase balancing coeff sooner | \
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use 3d mesh loss | \
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add final gc layer | \
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starting from v2_5_2, add tanh to cond_enc last layer | \
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NOT using one-hot skinning | \
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using new average garment with one-hot versions | \
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fix collision for plotting | \
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use 3d mesh loss | \
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higher reg coeff | \
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'
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config['dataset_in_memory'] = False
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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['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'] = 1 # set to 0 if don't want to use edge+collision
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config['l2_coeff'] = 1
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if config['resolution'] != 512:
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config['notes'] += '\
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using custom enhancer for upscaling, using not filled versions\
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'
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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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'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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if config['resolution'] != 512:
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res_modifier = '_' + str(config['resolution'])
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config['signature_dynamic']['uv_body_posed' + res_modifier] = (config['resolution'], config['resolution']//2, 3)
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config['signature_dynamic']['uv_unposed' + res_modifier] = (config['resolution'], config['resolution']//2, 3)
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config['signature_dynamic']['uv_curvature' + res_modifier] = (config['resolution'], config['resolution']//2)
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config['signature_static']['uv_static' + res_modifier] = (config['resolution'], config['resolution']//2, 3)
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config['signature_static']['uv_mask' + res_modifier] = (config['resolution'], config['resolution']//2)
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if config['resolution'] == 512:
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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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else:
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config['avg_garment_path'] = ''
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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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if config['resolution'] == 512:
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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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elif config['resolution'] == 128:
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config['cvae']['kernel_size'] = 5
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config['cvae']['encoder_depths'] = [16, 16, 9, 9]
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config['cvae']['encoder_dims'] = [64, 128, 256, 256]
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config['cvae']['decoder_input'] = (4, 2, 128)
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config['cvae']['decoder_depths'] = [16, 16, 9, 9]
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config['cvae']['decoder_dims'] = [256, 256, 128, 64]
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elif config['resolution'] == 32:
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config['cvae']['kernel_size'] = 3
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config['cvae']['encoder_depths'] = [27, 27]
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config['cvae']['encoder_dims'] = [256, 256]
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config['cvae']['decoder_input'] = (4, 2, 256)
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config['cvae']['decoder_depths'] = [27, 27]
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config['cvae']['decoder_dims'] = [256, 256]
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else:
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raise NotImplementedError
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