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a lot of training

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luni
2023-03-01 19:31:57 +00:00
parent 35ba014ba5
commit 424f8d2fcc
20 changed files with 1365 additions and 27 deletions
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aaa_helpers.txt
+11 -1
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@@ -19,16 +19,22 @@ nohup python auto_encoder_curv.py --name="lhunor_curv_iccv_1_10p" > nohup/iccv/e
nohup python auto_encoder_curv.py --name="lhunor_curv_iccv_1_25p" > nohup/iccv/encoders/curv_iccv_1_25p.out 2>&1 &
nohup python cvae.py --name="lhunor_cvae_iccv_gnn_1" > nohup/iccv/cvae_iccv_gnn_1.out 2>&1 &
nohup python cvae.py --name="lhunor_abl_all" > nohup/iccv/ablation/abl_all_2.out 2>&1 &
nohup python cvae.py --name="lhunor_abl_all" > nohup/iccv/ablation/abl_all_3.out 2>&1 &
nohup python cvae.py --name="lhunor_abl_all_gnn" > nohup/iccv/ablation/abl_all_gnn.out 2>&1 &
nohup python cvae.py --name="lhunor_abl_all_gnn_2" > nohup/iccv/ablation/abl_all_gnn.out 2>&1 &
nohup python cvae.py --name="lhunor_abl_all_skirt" > nohup/iccv/ablation/abl_all_skirt.out 2>&1 &
nohup python cvae.py --name="lhunor_abl_curv" > nohup/iccv/ablation/abl_curv.out 2>&1 &
nohup python cvae.py --name="lhunor_abl_curv_skirt" > nohup/iccv/ablation/abl_curv_skirt.out 2>&1 &
nohup python cvae.py --name="lhunor_abl_skin" > nohup/iccv/ablation/abl_skin.out 2>&1 &
nohup python cvae.py --name="lhunor_abl_skin_skirt" > nohup/iccv/ablation/abl_skin_skirt.out 2>&1 &
nohup python cvae.py --name="lhunor_abl_reg" > nohup/iccv/ablation/abl_reg.out 2>&1 &
nohup python cvae.py --name="lhunor_abl_reg_skirt" > nohup/iccv/ablation/abl_reg_skirt.out 2>&1 &
nohup python cvae.py --name="lhunor_abl_off" > nohup/iccv/ablation/abl_off.out 2>&1 &
nohup python cvae.py --name="lhunor_abl_skin_curv" > nohup/iccv/ablation/abl_skin_curv.out 2>&1 &
nohup python cvae.py --name="lhunor_abl_skin_curv_skirt" > nohup/iccv/ablation/abl_skin_curv_skirt.out 2>&1 &
nohup python cvae.py --name="lhunor_abl_skin_reg" > nohup/iccv/ablation/abl_skin_reg.out 2>&1 &
nohup python cvae.py --name="lhunor_abl_skin_reg_skirt" > nohup/iccv/ablation/abl_skin_reg_skirt.out 2>&1 &
nohup python upscale_test.py --name="iccv_32_2" > nohup/iccv/upscale/iccv_32_2.out 2>&1 &
nohup python upscale_test.py --name="iccv_64_2" > nohup/iccv/upscale/iccv_64_2.out 2>&1 &
@@ -53,6 +59,10 @@ nohup python upscale_test.py --name="iccv_256_2_cape_m" > nohup/iccv/upscale/icc
nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32" > nohup/iccv/pyr/iccv_pyr_32.out 2>&1 &
nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_skirt" > nohup/iccv/pyr/iccv_pyr_32_skirt_2.out 2>&1 &
nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_skin" > nohup/iccv/pyr/iccv_pyr_32_skin.out 2>&1 &
nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_skin_skirt" > nohup/iccv/pyr/iccv_pyr_32_skin_skirt.out 2>&1 &
nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64" > nohup/iccv/pyr/iccv_pyr_32_64.out 2>&1 &
nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_skin" > nohup/iccv/pyr/iccv_pyr_32_64_skin.out 2>&1 &
nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_64_cape_f" > nohup/iccv/pyr/iccv_pyr_64_cape_f.out 2>&1 &
configs/iccv/config_abl_all.py
+1 -1
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@@ -19,7 +19,7 @@ ablation_count = [config['use_skinning'], config['remove_global_orientation'], c
assert ablation_count == 1 or ablation_count == 0
config['gpu'] = '6'
config['name'] = 'abl_all_2'
config['name'] = 'abl_all_3'
config['notes'] = ''
config['tags'] = ['iccv', 'abl_all']
configs/iccv/config_abl_all_skirt.py
+3 -3
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@@ -18,7 +18,7 @@ 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'] = '3'
config['gpu'] = '6'
config['name'] = 'abl_all_skirt'
config['notes'] = ''
config['tags'] = ['iccv', 'abl_all', 'skirt']
@@ -35,8 +35,8 @@ config['is_skirt'] = True
config['dataset_in_memory'] = False
config['is_cape'] = False
config['train_dir'] = '/home/workspace/data/dataset/local-cache/train_skirt'
config['valid_dir'] = '/home/workspace/local-data/valid_skirt'
config['train_dir'] = '/home/workspace/local-data/train_skirt'
config['valid_dir'] = '/home/workspace/local-data_127/valid_skirt'
config['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
config['static_model'] = 'checkpoints/iccv/static_iccv_1_skirt'
configs/iccv/config_abl_curv.py
+1 -1
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@@ -18,7 +18,7 @@ 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['gpu'] = '0'
config['name'] = 'abl_curv'
config['notes'] = ''
config['tags'] = ['iccv', 'abl_curv']
configs/iccv/config_abl_curv_skirt.py
+125
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@@ -0,0 +1,125 @@
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'] = 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'] = '3'
config['name'] = 'abl_curv_skirt'
config['notes'] = ''
config['tags'] = ['iccv', 'abl_curv', 'skirt']
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_128/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/iccv/static_iccv_1_skirt'
config['body_model'] = 'checkpoints/iccv/body_iccv_1_skirt'
config['curvature_model'] = 'checkpoints/iccv/curv_iccv_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['bottleneck_scale'] = 2
config['cvae'] = dict()
config['cvae']['is_label'] = False
config['cvae']['latent_dim'] = 64 * config['bottleneck_scale']
config['cvae']['add_noise'] = False
config['cvae']['noise_amount'] = 0.0
config['cvae']['kernel_size'] = 7
config['cvae']['encoder_depths'] = [3, 3, 3, 9, 3]
config['cvae']['encoder_dims'] = [32, 64, 128, 256, config['cvae']['latent_dim']]
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['bottleneck_scale']
config['cond_ae_static']['encoder_depths'] = [3, 3, 3, 27, 3]
config['cond_ae_static']['encoder_dims'] = [8, 16, 32, 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['bottleneck_scale']
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['bottleneck_scale']
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'
configs/iccv/config_abl_pyr_32_64.py
+188
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@@ -0,0 +1,188 @@
config = dict()
config['gpu'] = '3'
config['name'] = 'iccv_pyr_32_64'
config['notes'] = ''
config['tags'] = ['pyr', 'iccv']
# 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]
config['pyramid']['pretrained_pyramid'] = 'checkpoints/iccv/iccv_pyr_32_170k'
config['pyramid']['final_upscale_enhancer'] = ''
config['train_dir'] = '/home/workspace/local-data_127/train'
config['valid_dir'] = '/home/workspace/local-data_127/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['smpl_res'] = 14475
if config['is_cape']:
config['smpl_res'] = 3638
config['lr'] = 0.0001
config['starting_balancing_coeff'] = 0.001
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
config['avg_garment_path'] = ''
config['bottleneck_scale'] = 2
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']['add_noise'] = False
config['pyramid']['noise_amount'] = 0.0
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/iccv/static_iccv_1'
config['pyramid']['body_model'] = 'checkpoints/iccv/body_iccv_1'
config['pyramid']['curvature_model'] = 'checkpoints/iccv/curv_iccv_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'] = 64 * config['bottleneck_scale']
level['kernel_size'] = 7
level['encoder_depths'] = [3, 3, 9, 3]
level['encoder_dims'] = [32, 64, 128, level['latent_dim']]
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'] = 64 * config['bottleneck_scale']
level['kernel_size'] = 5
level['encoder_depths'] = [9, 9, 9, 9]
level['encoder_dims'] = [32, 64, 128, level['latent_dim']]
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/iccv/iccv_'#'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'] = 64 * config['bottleneck_scale']
level['kernel_size'] = 5
level['encoder_depths'] = [16, 9, 9, 9]
level['encoder_dims'] = [64, 128, 128, 64]
level['decoder_input'] = (4, 2, 128)
level['decoder_depths'] = [16, 9, 9, 9]
level['decoder_dims'] = [256, 128, 128, level['latent_dim']]
level['avg_garment_path'] = ''
level['upscale_enhancer'] = 'checkpoints/iccv/iccv_'#'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'] = 64 * config['bottleneck_scale']
level['kernel_size'] = 3
level['encoder_depths'] = [9, 9]
level['encoder_dims'] = [64, level['latent_dim']]
level['decoder_depths'] = level['encoder_depths']
level['decoder_dims'] = level['encoder_dims']
level['avg_garment_path'] = ''
level['upscale_enhancer'] = 'checkpoints/iccv/iccv_64_2'#checkpoints/up_3_d64_128_2'
level['upscale_enhancer_freeze'] = True
config['pyramid']['levels'].append(level)
elif res == 32:
level = dict()
level['resolution'] = 32
level['latent_dim'] = 64 * config['bottleneck_scale']
level['kernel_size'] = 3
level['encoder_depths'] = [16]
level['encoder_dims'] = [level['latent_dim']]
level['decoder_depths'] = level['encoder_depths']
level['decoder_dims'] = level['encoder_dims']
level['avg_garment_path'] = ''
level['upscale_enhancer'] = 'checkpoints/iccv/iccv_32_2'#'checkpoints/up_3_d32_64_2'
level['upscale_enhancer_freeze'] = True
config['pyramid']['levels'].append(level)
else:
raise NotImplementedError
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['bottleneck_scale']
config['cond_ae_static']['encoder_depths'] = [3, 3, 3, 27, 3]
config['cond_ae_static']['encoder_dims'] = [8, 16, 32, 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['bottleneck_scale']
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['bottleneck_scale']
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'
configs/iccv/config_abl_pyr_32_64_skin.py
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@@ -0,0 +1,195 @@
config = dict()
config['gpu'] = '4'
config['name'] = 'iccv_pyr_32_64_skin'
config['notes'] = ''
config['tags'] = ['pyr', 'iccv']
# 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'] = ''
config['pretrained_model_iteration'] = ''
config['pyramid'] = dict()
config['pyramid']['resolutions'] = [32, 64]
config['pyramid']['pretrained_pyramid'] = 'checkpoints/iccv/iccv_pyr_32_skin_165k'
config['pyramid']['final_upscale_enhancer'] = ''
config['train_dir'] = '/home/workspace/local-data_127/train'
config['valid_dir'] = '/home/workspace/local-data_127/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['smpl_res'] = 14475
if config['is_cape']:
config['smpl_res'] = 3638
config['lr'] = 0.0001
config['starting_balancing_coeff'] = 0.001
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
config['avg_garment_path'] = ''
config['bottleneck_scale'] = 2
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),
}
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']['add_noise'] = False
config['pyramid']['noise_amount'] = 0.0
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/iccv/static_iccv_1'
config['pyramid']['body_model'] = 'checkpoints/iccv/body_iccv_1'
config['pyramid']['curvature_model'] = 'checkpoints/iccv/curv_iccv_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'] = 64 * config['bottleneck_scale']
level['kernel_size'] = 7
level['encoder_depths'] = [3, 3, 9, 3]
level['encoder_dims'] = [32, 64, 128, level['latent_dim']]
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'] = 64 * config['bottleneck_scale']
level['kernel_size'] = 5
level['encoder_depths'] = [9, 9, 9, 9]
level['encoder_dims'] = [32, 64, 128, level['latent_dim']]
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/iccv/iccv_'#'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'] = 64 * config['bottleneck_scale']
level['kernel_size'] = 5
level['encoder_depths'] = [16, 9, 9, 9]
level['encoder_dims'] = [64, 128, 128, 64]
level['decoder_input'] = (4, 2, 128)
level['decoder_depths'] = [16, 9, 9, 9]
level['decoder_dims'] = [256, 128, 128, level['latent_dim']]
level['avg_garment_path'] = ''
level['upscale_enhancer'] = 'checkpoints/iccv/iccv_'#'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'] = 64 * config['bottleneck_scale']
level['kernel_size'] = 3
level['encoder_depths'] = [9, 9]
level['encoder_dims'] = [64, level['latent_dim']]
level['decoder_depths'] = level['encoder_depths']
level['decoder_dims'] = level['encoder_dims']
level['avg_garment_path'] = ''
level['upscale_enhancer'] = 'checkpoints/iccv/iccv_64_2'#checkpoints/up_3_d64_128_2'
level['upscale_enhancer_freeze'] = True
config['pyramid']['levels'].append(level)
elif res == 32:
level = dict()
level['resolution'] = 32
level['latent_dim'] = 64 * config['bottleneck_scale']
level['kernel_size'] = 3
level['encoder_depths'] = [16]
level['encoder_dims'] = [level['latent_dim']]
level['decoder_depths'] = level['encoder_depths']
level['decoder_dims'] = level['encoder_dims']
level['avg_garment_path'] = ''
level['upscale_enhancer'] = 'checkpoints/iccv/iccv_32_2'#'checkpoints/up_3_d32_64_2'
level['upscale_enhancer_freeze'] = True
config['pyramid']['levels'].append(level)
else:
raise NotImplementedError
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['bottleneck_scale']
config['cond_ae_static']['encoder_depths'] = [3, 3, 3, 27, 3]
config['cond_ae_static']['encoder_dims'] = [8, 16, 32, 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['bottleneck_scale']
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['bottleneck_scale']
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'
configs/iccv/config_abl_pyr_32_skin_skirt.py
+195
View File
@@ -0,0 +1,195 @@
config = dict()
config['gpu'] = '2'
config['name'] = 'iccv_pyr_32_skin_skirt'
config['notes'] = ''
config['tags'] = ['pyr', 'iccv']
# 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'] = ''
config['pretrained_model_iteration'] = ''
config['pyramid'] = dict()
config['pyramid']['resolutions'] = [32]
config['pyramid']['pretrained_pyramid'] = ''
config['pyramid']['final_upscale_enhancer'] = ''
config['train_dir'] = '/home/workspace/local-data_128/train_skirt'
config['valid_dir'] = '/home/workspace/local-data_127/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['dataset_in_memory'] = False
config['resolution'] = None
config['smpl_res'] = 14475
if config['is_cape']:
config['smpl_res'] = 3638
config['lr'] = 0.0001
config['starting_balancing_coeff'] = 0.001
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
config['avg_garment_path'] = ''
config['bottleneck_scale'] = 2
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),
}
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']['add_noise'] = False
config['pyramid']['noise_amount'] = 0.0
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/iccv/static_iccv_1_skirt'
config['pyramid']['body_model'] = 'checkpoints/iccv/body_iccv_1_skirt'
config['pyramid']['curvature_model'] = 'checkpoints/iccv/curv_iccv_1_skirt'
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'] = 64 * config['bottleneck_scale']
level['kernel_size'] = 7
level['encoder_depths'] = [3, 3, 9, 3]
level['encoder_dims'] = [32, 64, 128, level['latent_dim']]
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'] = 64 * config['bottleneck_scale']
level['kernel_size'] = 5
level['encoder_depths'] = [9, 9, 9, 9]
level['encoder_dims'] = [32, 64, 128, level['latent_dim']]
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/iccv/iccv_'#'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'] = 64 * config['bottleneck_scale']
level['kernel_size'] = 5
level['encoder_depths'] = [16, 9, 9, 9]
level['encoder_dims'] = [64, 128, 128, 64]
level['decoder_input'] = (4, 2, 128)
level['decoder_depths'] = [16, 9, 9, 9]
level['decoder_dims'] = [256, 128, 128, level['latent_dim']]
level['avg_garment_path'] = ''
level['upscale_enhancer'] = 'checkpoints/iccv/iccv_'#'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'] = 64 * config['bottleneck_scale']
level['kernel_size'] = 3
level['encoder_depths'] = [9, 9]
level['encoder_dims'] = [64, level['latent_dim']]
level['decoder_depths'] = level['encoder_depths']
level['decoder_dims'] = level['encoder_dims']
level['avg_garment_path'] = ''
level['upscale_enhancer'] = 'checkpoints/iccv/iccv_'#checkpoints/up_3_d64_128_2'
level['upscale_enhancer_freeze'] = True
config['pyramid']['levels'].append(level)
elif res == 32:
level = dict()
level['resolution'] = 32
level['latent_dim'] = 64 * config['bottleneck_scale']
level['kernel_size'] = 3
level['encoder_depths'] = [16]
level['encoder_dims'] = [level['latent_dim']]
level['decoder_depths'] = level['encoder_depths']
level['decoder_dims'] = level['encoder_dims']
level['avg_garment_path'] = ''
level['upscale_enhancer'] = 'checkpoints/iccv/iccv_32_2_skirt'#'checkpoints/up_3_d32_64_2'
level['upscale_enhancer_freeze'] = True
config['pyramid']['levels'].append(level)
else:
raise NotImplementedError
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['bottleneck_scale']
config['cond_ae_static']['encoder_depths'] = [3, 3, 3, 27, 3]
config['cond_ae_static']['encoder_dims'] = [8, 16, 32, 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['bottleneck_scale']
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['bottleneck_scale']
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'
configs/iccv/config_abl_pyr_32_skirt.py
+4 -4
View File
@@ -1,7 +1,7 @@
config = dict()
config['gpu'] = '5'
config['name'] = 'iccv_pyr_32_skirt_2'
config['gpu'] = '1'
config['name'] = 'iccv_pyr_32_skirt_3'
config['notes'] = ''
config['tags'] = ['pyr', 'iccv']
@@ -29,8 +29,8 @@ config['pyramid']['resolutions'] = [32]
config['pyramid']['pretrained_pyramid'] = ''
config['pyramid']['final_upscale_enhancer'] = ''
config['train_dir'] = '/home/workspace/data/dataset/local-cache/train_skirt'
config['valid_dir'] = '/home/workspace/local-data/valid_skirt'
config['train_dir'] = '/home/workspace/local-data_128/train_skirt'
config['valid_dir'] = '/home/workspace/local-data_127/valid_skirt'
config['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
config['batch_size'] = 4
config['is_skirt'] = True
configs/iccv/config_abl_reg.py
+1 -1
View File
@@ -18,7 +18,7 @@ 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['gpu'] = '5'
config['name'] = 'abl_reg'
config['notes'] = ''
config['tags'] = ['iccv', 'abl_reg']
configs/iccv/config_abl_reg_skirt.py
+125
View File
@@ -0,0 +1,125 @@
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'] = 'abl_reg_skirt'
config['notes'] = ''
config['tags'] = ['iccv', 'abl_reg', 'skirt']
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_128/train_skirt'
config['valid_dir'] = '/home/workspace/local-data_127/valid_skirt'
config['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
config['static_model'] = 'checkpoints/iccv/static_iccv_1_skirt'
config['body_model'] = 'checkpoints/iccv/body_iccv_1_skirt'
config['curvature_model'] = 'checkpoints/iccv/curv_iccv_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['bottleneck_scale'] = 2
config['cvae'] = dict()
config['cvae']['is_label'] = False
config['cvae']['latent_dim'] = 64 * config['bottleneck_scale']
config['cvae']['add_noise'] = False
config['cvae']['noise_amount'] = 0.0
config['cvae']['kernel_size'] = 7
config['cvae']['encoder_depths'] = [3, 3, 3, 9, 3]
config['cvae']['encoder_dims'] = [32, 64, 128, 256, config['cvae']['latent_dim']]
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['bottleneck_scale']
config['cond_ae_static']['encoder_depths'] = [3, 3, 3, 27, 3]
config['cond_ae_static']['encoder_dims'] = [8, 16, 32, 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['bottleneck_scale']
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['bottleneck_scale']
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'
configs/iccv/config_abl_skin_curv.py
+3 -3
View File
@@ -18,7 +18,7 @@ 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'] = '5'
config['gpu'] = '4'
config['name'] = 'abl_skin_curv'
config['notes'] = ''
config['tags'] = ['iccv', 'abl_skin_curv']
@@ -35,8 +35,8 @@ 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['train_dir'] = '/home/workspace/local-data_127/train'
config['valid_dir'] = '/home/workspace/local-data_127/valid'
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
config['static_model'] = 'checkpoints/iccv/static_iccv_1'
configs/iccv/config_abl_skin_curv_skirt.py
+125
View File
@@ -0,0 +1,125 @@
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'] = False
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_skin_curv_skirt'
config['notes'] = ''
config['tags'] = ['iccv', 'abl_skin_curv', 'skirt']
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_128/train_skirt'
config['valid_dir'] = '/home/workspace/local-data_127/valid_skirt'
config['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
config['static_model'] = 'checkpoints/iccv/static_iccv_1_skirt'
config['body_model'] = 'checkpoints/iccv/body_iccv_1_skirt'
config['curvature_model'] = 'checkpoints/iccv/curv_iccv_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['bottleneck_scale'] = 2
config['cvae'] = dict()
config['cvae']['is_label'] = False
config['cvae']['latent_dim'] = 64 * config['bottleneck_scale']
config['cvae']['add_noise'] = False
config['cvae']['noise_amount'] = 0.0
config['cvae']['kernel_size'] = 7
config['cvae']['encoder_depths'] = [3, 3, 3, 9, 3]
config['cvae']['encoder_dims'] = [32, 64, 128, 256, config['cvae']['latent_dim']]
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['bottleneck_scale']
config['cond_ae_static']['encoder_depths'] = [3, 3, 3, 27, 3]
config['cond_ae_static']['encoder_dims'] = [8, 16, 32, 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['bottleneck_scale']
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['bottleneck_scale']
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'
configs/iccv/config_abl_skin_reg.py
+125
View File
@@ -0,0 +1,125 @@
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'] = 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_skin_reg'
config['notes'] = ''
config['tags'] = ['iccv', 'abl_skin_reg']
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_127/train'
config['valid_dir'] = '/home/workspace/local-data_127/valid'
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
config['static_model'] = 'checkpoints/iccv/static_iccv_1'
config['body_model'] = 'checkpoints/iccv/body_iccv_1'
config['curvature_model'] = 'checkpoints/iccv/curv_iccv_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['bottleneck_scale'] = 2
config['cvae'] = dict()
config['cvae']['is_label'] = False
config['cvae']['latent_dim'] = 64 * config['bottleneck_scale']
config['cvae']['add_noise'] = False
config['cvae']['noise_amount'] = 0.0
config['cvae']['kernel_size'] = 7
config['cvae']['encoder_depths'] = [3, 3, 3, 9, 3]
config['cvae']['encoder_dims'] = [32, 64, 128, 256, config['cvae']['latent_dim']]
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['bottleneck_scale']
config['cond_ae_static']['encoder_depths'] = [3, 3, 3, 27, 3]
config['cond_ae_static']['encoder_dims'] = [8, 16, 32, 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['bottleneck_scale']
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['bottleneck_scale']
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'
configs/iccv/config_abl_skin_reg_skirt.py
+125
View File
@@ -0,0 +1,125 @@
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'] = 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'] = '7'
config['name'] = 'abl_skin_reg_skirt'
config['notes'] = ''
config['tags'] = ['iccv', 'abl_skin_reg', 'skirt']
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_128/train_skirt'
config['valid_dir'] = '/home/workspace/local-data_127/valid_skirt'
config['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
config['static_model'] = 'checkpoints/iccv/static_iccv_1_skirt'
config['body_model'] = 'checkpoints/iccv/body_iccv_1_skirt'
config['curvature_model'] = 'checkpoints/iccv/curv_iccv_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['bottleneck_scale'] = 2
config['cvae'] = dict()
config['cvae']['is_label'] = False
config['cvae']['latent_dim'] = 64 * config['bottleneck_scale']
config['cvae']['add_noise'] = False
config['cvae']['noise_amount'] = 0.0
config['cvae']['kernel_size'] = 7
config['cvae']['encoder_depths'] = [3, 3, 3, 9, 3]
config['cvae']['encoder_dims'] = [32, 64, 128, 256, config['cvae']['latent_dim']]
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['bottleneck_scale']
config['cond_ae_static']['encoder_depths'] = [3, 3, 3, 27, 3]
config['cond_ae_static']['encoder_dims'] = [8, 16, 32, 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['bottleneck_scale']
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['bottleneck_scale']
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'
configs/iccv/config_abl_skin_skirt.py
+125
View File
@@ -0,0 +1,125 @@
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)
assert ablation_count == 1 or ablation_count == 0
config['gpu'] = '4'
config['name'] = 'abl_skin_skirt'
config['notes'] = ''
config['tags'] = ['iccv', 'abl_skin', 'skirt']
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_128/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/iccv/static_iccv_1_skirt'
config['body_model'] = 'checkpoints/iccv/body_iccv_1_skirt'
config['curvature_model'] = 'checkpoints/iccv/curv_iccv_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['bottleneck_scale'] = 2
config['cvae'] = dict()
config['cvae']['is_label'] = False
config['cvae']['latent_dim'] = 64 * config['bottleneck_scale']
config['cvae']['add_noise'] = False
config['cvae']['noise_amount'] = 0.0
config['cvae']['kernel_size'] = 7
config['cvae']['encoder_depths'] = [3, 3, 3, 9, 3]
config['cvae']['encoder_dims'] = [32, 64, 128, 256, config['cvae']['latent_dim']]
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['bottleneck_scale']
config['cond_ae_static']['encoder_depths'] = [3, 3, 3, 27, 3]
config['cond_ae_static']['encoder_dims'] = [8, 16, 32, 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['bottleneck_scale']
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['bottleneck_scale']
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'
cvae.py
+2 -2
View File
@@ -1,6 +1,6 @@
import os
import sys
from configs.iccv.config_abl_skin import config
from configs.iccv.config_abl_skin_reg_skirt import config
os.environ["CUDA_VISIBLE_DEVICES"] = config['gpu']
import tensorflow as tf
@@ -546,7 +546,7 @@ if __name__ == '__main__':
train_loss = train_step(batch)
train_accumulator.update(train_loss)
if step % 50 == 0:
if step % 25 == 0:
data_valid = valid_iterator.get_next()
data_valid = static_dataset_valid.expand_batch(batch_to_dict(data_valid, config['signature_dynamic']))
valid_loss = valid_step(data_valid)
cvae_pyramid.py
+1 -1
View File
@@ -1,6 +1,6 @@
import os
import sys
from configs.iccv.config_abl_pyr_32 import config
from configs.iccv.config_abl_pyr_32_64_skin import config
os.environ["CUDA_VISIBLE_DEVICES"] = config['gpu']
import tensorflow as tf
downscale.py
+4 -4
View File
@@ -187,14 +187,14 @@ def downscale_uv_maps_mask(folder, type, size):
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument("-f", "--folder", help = "end of range", default='/home/workspace/local-data/train')
parser.add_argument("-s", "--start", help = "start of range", default=30700)
parser.add_argument("-e", "--end", help = "end of range", default=45000)
parser.add_argument("-f", "--folder", help = "end of range", default='/home/workspace/local-data/train_skirt')
parser.add_argument("-s", "--start", help = "start of range", default=0)
parser.add_argument("-e", "--end", help = "end of range", default=1e6)
parser.add_argument("-n", "--name", help = "end of range", default='lhunor')
args = parser.parse_args()
# sizes = [32, 64, 128, 256]
sizes = [32]
sizes = [64, 128, 256]
folder = args.folder
is_skirt = True
run_parallel.py
+6 -6
View File
@@ -4,26 +4,26 @@ import os
if __name__ == '__main__':
folder = '/home/workspace/data/dataset/test_skirt_ready_2'
# folder = '/home/workspace/data/dataset/test_skirt_ready_2'
# folder = '/home/workspace/local-data/cape_processed/train/male'
# folder = '/home/workspace/local-data/valid_skirt'
folder = '/home/workspace/local-data/train_skirt'
# folder = '/home/workspace/local-data/valid'
# ids = os.listdir(folder)
ids = os.listdir(folder + '/mesh_posed_no_orient')#[280000:]
skirt = 0
count = 0
step = 2000
step = 20000
# !!!!!!! change skirt parameter in script
while count < len(ids):
while count < 200000:
# os.system('nohup python convert_to_uv_cape.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + ' -n ' + 'to_uv_2_cape_train_male_' + str(count) + '_' + str(count+step) + ' > nohup/to_uv_2_cape_train_male_' + str(count) + '_' + str(count+step) + '.out' + ' 2>&1 &')
# os.system('nohup python convert_to_uv.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + ' -n ' + 'to_uv_train_unposed_onehot_' + str(count) + '_' + str(count+step) + ' > nohup/to_uv_train_unposed_onehot_' + str(count) + '_' + str(count+step) + '.out' + ' 2>&1 &')
# os.system('nohup python convert_to_uv_local.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + ' -n ' + 'to_uv_train_local_unposed_onehot_' + str(count) + '_' + str(count+step) + ' > nohup/to_uv_train_local_unposed_onehot_' + str(count) + '_' + str(count+step) + '.out' + ' 2>&1 &')
os.system('nohup python convert_to_uv_local_single.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + ' -n ' + 'to_uv_posed_no_orient_test_skirt_ready_' + str(count) + '_' + str(count+step) + ' > nohup/to_uv_posed_no_orient_test_skirt_ready_' + str(count) + '_' + str(count+step) + '.out' + ' 2>&1 &')
# os.system('nohup python convert_to_uv_local_single.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + ' -n ' + 'to_uv_posed_no_orient_test_skirt_ready_' + str(count) + '_' + str(count+step) + ' > nohup/to_uv_posed_no_orient_test_skirt_ready_' + str(count) + '_' + str(count+step) + '.out' + ' 2>&1 &')
# os.system('nohup python convert_to_uv_local_single.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + ' -n ' + 'to_uv_train_skirt_local_unposed_onehot_3_' + str(count) + '_' + str(count+step) + ' > nohup/to_uv_train_skirt_local_unposed_onehot_3_' + str(count) + '_' + str(count+step) + '.out' + ' 2>&1 &')
# os.system('nohup python convert_to_uv_local_single.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + ' -n ' + 'to_uv_valid_skirt_local_unposed_onehot_3_' + str(count) + '_' + str(count+step) + ' > nohup/to_uv_valid_skirt_local_unposed_onehot_' + str(count) + '_' + str(count+step) + '.out' + ' 2>&1 &')
# os.system('nohup python downscale.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + ' -n ' + 'downscale_valid_posed_no_orient_' + str(count) + '_' + str(count+step) + ' > nohup/downscale_valid_posed_no_orient_' + str(count) + '_' + str(count+step) + '.out' + ' 2>&1 &')
os.system('nohup python downscale.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + ' -n ' + 'downscale_train_skirt_posed_no_orient_' + str(count) + '_' + str(count+step) + ' > nohup/downscale_train_skirt_posed_no_orient_' + str(count) + '_' + str(count+step) + '.out' + ' 2>&1 &')
# os.system('python Data/convert_to_uv.py -f ' + folder + ' -s ' + str(count) + ' -e ' + str(count + step) + '')
count += step