166 lines
6.7 KiB
Python
166 lines
6.7 KiB
Python
from configs.config_base import config
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config['gpu'] = '2'
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config['name'] = 'pyr_4_32_2_64_2'
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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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common condition encoders for all levels, only run once | \
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full res loss on each level | \
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all higher levels are added to the output of first level | \
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using custom MLP upscale enhancement | \
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only train highest level, all other use from pretrained pyramids with one less level | \
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maybe upscale enhancer was not frozen? --> fixed pretrained approach | \
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upscale from level to level, not to final res, only at the end to final res | \
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updated upscale enhancers | \
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try with l2 loss | \
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fixed low res body inputs | \
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with 3d loss | \
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continued from pyr_4_32_2, changed encoders, upscaler, added tanh to cond_encoder | \
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'
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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 IF SKIRT
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# DON'T FORGET TO CHECK IF CAPE
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# DON'T FORGET TO CHECK IF USING DOWNSCALE NONE OR _2
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# DON'T FORGET TO CHECK UPSCALING and ENCODER CHECKPOINTS
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config['dataset_in_memory'] = False
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config['resolution'] = None
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config['lr'] = 0.0001
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config['starting_balancing_coeff'] = 0.0001
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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['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': (config['smpl_res'], 3,),
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'mesh_posed': (config['smpl_res'], 3,),
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'mesh_unposed': (config['smpl_res'], 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': (config['smpl_res'],),
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'uv_mask': (512, 256,),
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}
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config['pyramid'] = dict()
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config['pyramid']['is_label'] = False
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config['pyramid']['latent_dim'] = config['latent_dim']
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config['pyramid']['add_noise'] = True
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config['pyramid']['resolutions'] = [32]
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config['pyramid']['loss_weights'] = [1,1,1,1,1]
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config['pyramid']['pretrained_pyramid'] = 'checkpoints/pyr_4_32_2'
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for res in config['pyramid']['resolutions']:
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if res != 512:
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res_modifier = '_' + str(res)
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config['signature_dynamic']['uv_body_posed' + res_modifier] = (res, res//2, 3)
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config['signature_dynamic']['uv_unposed' + res_modifier] = (res, res//2, 3)
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config['signature_dynamic']['uv_curvature' + res_modifier] = (res, res//2, 7)
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config['signature_static']['uv_static' + res_modifier] = (res, res//2, 3)
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config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
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# config['pyramid']['static_model'] = 'checkpoints/static_1_skirt'
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# config['pyramid']['body_model'] = 'checkpoints/body_1_skirt_2_2'
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# config['pyramid']['curvature_model'] = 'checkpoints/curv_1_skirt'
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config['pyramid']['static_model'] = 'checkpoints/static_1'
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config['pyramid']['body_model'] = 'checkpoints/body_1'
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config['pyramid']['curvature_model'] = 'checkpoints/curv_1'
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# config['pyramid']['static_model'] = 'checkpoints/static_1_cape_f'
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# config['pyramid']['body_model'] = 'checkpoints/body_1_cape_f'
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# config['pyramid']['curvature_model'] = 'checkpoints/curv_1_cape_f'
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# config['pyramid']['static_model'] = ''
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# config['pyramid']['body_model'] = ''
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# config['pyramid']['curvature_model'] = ''
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config['pyramid']['freeze_encoders'] = True
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config['avg_garment_path'] = ''
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config['pyramid']['final_upscale_enhancer'] = 'checkpoints/32_512_4'
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config['pyramid']['levels'] = []
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for res in config['pyramid']['resolutions']:
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if res == 512:
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level = dict()
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level['resolution'] = 512
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level['latent_dim'] = config['latent_dim']
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level['kernel_size'] = 7
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level['encoder_depths'] = [3, 3, 9, 3]
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level['encoder_dims'] = [32, 64, 128, 256]
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level['decoder_input'] = (16, 8, 80)
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level['decoder_depths'] = [3, 3, 9, 3]
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level['decoder_dims'] = [256, 128, 64, 16]
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level['avg_garment_path'] = ''
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level['upscale_enhancer'] = ''
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config['pyramid']['levels'].append(level)
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elif res == 256:
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level = dict()
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level['resolution'] = 256
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level['latent_dim'] = config['latent_dim']
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level['kernel_size'] = 7
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level['encoder_depths'] = [9, 9, 9, 9]
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level['encoder_dims'] = [32, 64, 128, 256]
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level['decoder_input'] = (8, 4, 128)
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level['decoder_depths'] = [9, 9, 9, 9]
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level['decoder_dims'] = [256, 128, 64, 16]
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level['avg_garment_path'] = ''
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level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
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level['upscale_enhancer_freeze'] = True
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config['pyramid']['levels'].append(level)
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elif res == 128:
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level = dict()
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level['resolution'] = 128
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level['latent_dim'] = config['latent_dim']
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level['kernel_size'] = 5
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level['encoder_depths'] = [16, 9, 9, 9]
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level['encoder_dims'] = [64, 128, 128, 256]
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level['decoder_input'] = (4, 2, 128)
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level['decoder_depths'] = [16, 9, 9, 9]
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level['decoder_dims'] = [256, 128, 128, 64]
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level['avg_garment_path'] = ''
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level['upscale_enhancer'] = 'checkpoints/128_512_cape_f'#'checkpoints/up_3_d128_256_2'
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level['upscale_enhancer_freeze'] = True
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config['pyramid']['levels'].append(level)
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elif res == 64:
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level = dict()
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level['resolution'] = 64
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level['latent_dim'] = config['latent_dim']
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level['kernel_size'] = 5
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level['encoder_depths'] = [9, 9, 9]
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level['encoder_dims'] = [64, 128, 256]
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level['decoder_input'] = (4, 2, 256)
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level['decoder_depths'] = [9, 9, 9]
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level['decoder_dims'] = [256, 128, 64]
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level['avg_garment_path'] = ''
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level['upscale_enhancer'] = ''#checkpoints/up_3_d64_128_2'
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level['upscale_enhancer_freeze'] = False
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config['pyramid']['levels'].append(level)
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elif res == 32:
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level = dict()
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level['resolution'] = 32
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level['latent_dim'] = config['latent_dim']
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level['kernel_size'] = 3
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level['encoder_depths'] = [9, 9]
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level['encoder_dims'] = [256, 256]
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level['decoder_input'] = (4, 2, 256)
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level['decoder_depths'] = [9, 9]
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level['decoder_dims'] = [256, 256]
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level['avg_garment_path'] = ''
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level['upscale_enhancer'] = ''#'checkpoints/up_3_d32_64_2'
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level['upscale_enhancer_freeze'] = True
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config['pyramid']['levels'].append(level)
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else:
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raise NotImplementedError |