save
This commit is contained in:
@@ -84,6 +84,7 @@ nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_tshirt" > nohup/iccv/pyr
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_skirt_skirt" > nohup/iccv/pyr/iccv_pyr_32_skirt_skirt.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_skirt_dress" > nohup/iccv/pyr/iccv_pyr_32_skirt_dress.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_skirt_batch" > nohup/iccv/pyr/iccv_pyr_32_skirt_batch.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_seq" > nohup/iccv/pyr/iccv_pyr_32_seq_2.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64" > nohup/iccv/pyr/iccv_pyr_32_64.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_skirt" > nohup/iccv/pyr/iccv_pyr_32_64_skirt.out 2>&1 &
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@@ -95,6 +96,14 @@ nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_reg" > nohup/iccv/pyr
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_reg_skirt" > nohup/iccv/pyr/iccv_pyr_32_64_reg_skirt.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_10p" > nohup/iccv/pyr/iccv_pyr_32_64_10p.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_25p" > nohup/iccv/pyr/iccv_pyr_32_64_25p.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_tshirt" > nohup/iccv/pyr/iccv_pyr_32_64_tshirt.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_trousers" > nohup/iccv/pyr/iccv_pyr_32_64_trousers.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_top" > nohup/iccv/pyr/iccv_pyr_32_64_top.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_skirt_skirt" > nohup/iccv/pyr/iccv_pyr_32_64_skirt_skirt.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_skirt_dress" > nohup/iccv/pyr/iccv_pyr_32_64_skirt_dress.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_jumpsuit" > nohup/iccv/pyr/iccv_pyr_32_64_jumpsuit.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_seq" > nohup/iccv/pyr/iccv_pyr_32_64_seq.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_seq_2" > nohup/iccv/pyr/iccv_pyr_32_64_seq_2.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_64_cape_f" > nohup/iccv/pyr/iccv_pyr_64_cape_f.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_64_cape_m" > nohup/iccv/pyr/iccv_pyr_64_cape_m.out 2>&1 &
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@@ -116,6 +125,14 @@ nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_128_reg" > nohup/iccv
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_128_curv" > nohup/iccv/pyr/iccv_pyr_32_64_128_curv.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_128_curv_skirt" > nohup/iccv/pyr/iccv_pyr_32_64_128_curv_skirt.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_128_var" > nohup/iccv/pyr/iccv_pyr_32_64_128_var.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_128_tshirt" > nohup/iccv/pyr/iccv_pyr_32_64_128_tshirt.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_128_trousers" > nohup/iccv/pyr/iccv_pyr_32_64_128_trousers.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_128_top" > nohup/iccv/pyr/iccv_pyr_32_64_128_top.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_128_jumpsuit" > nohup/iccv/pyr/iccv_pyr_32_64_128_jumpsuit.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_128_skirt_skirt" > nohup/iccv/pyr/iccv_pyr_32_64_128_skirt_skirt.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_128_skirt_dress" > nohup/iccv/pyr/iccv_pyr_32_64_128_skirt_dress.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_128" > nohup/iccv/pyr/iccv_pyr_32_64_128.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_32_64_128" > nohup/iccv/pyr/iccv_pyr_32_64_128.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_64_128_cape_m_00032_SL" > nohup/iccv/pyr/iccv_pyr_64_128_cape_m_00032_SL.out 2>&1 &
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nohup python cvae_pyramid.py --name="lhunor_iccv_pyr_64_128_cape_f_03223_SL" > nohup/iccv/pyr/iccv_pyr_64_128_cape_f_03223_SL.out 2>&1 &
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@@ -1,6 +1,6 @@
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config = dict()
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config['gpu'] = '4'
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config['gpu'] = '0'
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config['name'] = 'iccv_pyr_32_64_128_256_512'
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config['notes'] = ''
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config['tags'] = ['pyr', 'iccv']
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@@ -34,8 +34,8 @@ config['pyramid']['final_upscale_enhancer'] = ''
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config['train_dir'] = '/home/workspace/local-data/train'
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config['valid_dir'] = '/home/workspace/local-data/train'
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config['test_dir'] = '/home/workspace/local-data/test_ready'
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config['frames_file'] = 'frames_00761_0.txt'
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config['frames_file_valid'] = 'frames_00761_0.txt'
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# config['frames_file'] = 'frames_00761_0.txt'
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# config['frames_file_valid'] = 'frames_00761_0.txt'
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config['batch_size'] = 4
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config['is_skirt'] = False
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config['is_cape'] = False
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@@ -1,6 +1,6 @@
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config = dict()
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config['gpu'] = '4'
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config['gpu'] = '2'
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config['name'] = 'iccv_pyr_32_64_128_256_512_skirt'
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config['notes'] = ''
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config['tags'] = ['pyr', 'iccv']
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@@ -0,0 +1,190 @@
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config = dict()
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config['gpu'] = '3'
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config['name'] = 'iccv_pyr_32_64_128_jumpsuit'
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config['notes'] = ''
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config['tags'] = ['pyr', 'iccv']
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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['use_skinning'] = True # and deshaping
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config['remove_global_orientation'] = True
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config['use_extra_losses'] = True # edge, collision, 3d mesh
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config['use_offsets'] = False
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config['use_norm_loss'] = True
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config['use_curvature'] = True
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config['pretrained_model'] = ''
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config['pretrained_model_iteration'] = ''
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config['pyramid'] = dict()
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config['pyramid']['resolutions'] = [32, 64, 128]
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config['pyramid']['pretrained_pyramid'] = 'checkpoints/iccv/iccv_pyr_32_64_jumpsuit'
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config['pyramid']['final_upscale_enhancer'] = ''
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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/local-data_127/test_ready'
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config['frames_file'] = 'frames_jumpsuit.txt'
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config['frames_file_valid'] = 'frames_jumpsuit.txt'
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config['frames_file_test'] = 'frames_jumpsuit.txt'
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config['batch_size'] = 4
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config['is_skirt'] = False
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config['is_cape'] = False
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config['dataset_in_memory'] = False
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config['resolution'] = None
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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['lr'] = 0.0001
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config['starting_balancing_coeff'] = 0.001
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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['avg_garment_path'] = ''
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config['bottleneck_scale'] = 2
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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': (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']['is_label'] = False
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config['pyramid']['add_noise'] = False
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config['pyramid']['noise_amount'] = 0.0
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config['pyramid']['loss_weights'] = [1,1,1,1,1]
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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/iccv/static_iccv_1'
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config['pyramid']['body_model'] = 'checkpoints/iccv/body_iccv_1'
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config['pyramid']['curvature_model'] = 'checkpoints/iccv/curv_iccv_1'
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config['pyramid']['freeze_encoders'] = True
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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'] = 64 * config['bottleneck_scale']
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level['kernel_size'] = 7
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level['encoder_depths'] = [3, 3, 3, 9, 3]
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level['encoder_dims'] = [16, 32, 64, 128, level['latent_dim']]
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level['decoder_depths'] = level['encoder_depths']
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level['decoder_dims'] = level['encoder_dims']
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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'] = 64 * config['bottleneck_scale']
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level['kernel_size'] = 5
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level['encoder_depths'] = [3, 3, 9, 3]
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level['encoder_dims'] = [64, 128, 128, level['latent_dim']]
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level['decoder_depths'] = level['encoder_depths']
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level['decoder_dims'] = level['encoder_dims']
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level['avg_garment_path'] = ''
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level['upscale_enhancer'] = 'checkpoints/iccv/iccv_256_2'#'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'] = 64 * config['bottleneck_scale']
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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'] = [128, 128, level['latent_dim']]
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level['decoder_depths'] = level['encoder_depths']
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level['decoder_dims'] = level['encoder_dims']
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level['avg_garment_path'] = ''
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level['upscale_enhancer'] = 'checkpoints/iccv/iccv_128_2'#'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'] = 64 * config['bottleneck_scale']
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level['kernel_size'] = 3
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level['encoder_depths'] = [9, 9]
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level['encoder_dims'] = [64, level['latent_dim']]
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level['decoder_depths'] = level['encoder_depths']
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level['decoder_dims'] = level['encoder_dims']
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level['avg_garment_path'] = ''
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level['upscale_enhancer'] = 'checkpoints/iccv/iccv_64_2'#checkpoints/up_3_d64_128_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 == 32:
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level = dict()
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level['resolution'] = 32
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level['latent_dim'] = 64 * config['bottleneck_scale']
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level['kernel_size'] = 3
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level['encoder_depths'] = [16]
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level['encoder_dims'] = [level['latent_dim']]
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level['decoder_depths'] = level['encoder_depths']
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level['decoder_dims'] = level['encoder_dims']
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level['avg_garment_path'] = ''
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level['upscale_enhancer'] = 'checkpoints/iccv/iccv_32_2'#'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
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config['cond_ae_static'] = dict()
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config['cond_ae_static']['is_label'] = False
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config['cond_ae_static']['kernel_size'] = 7
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config['cond_ae_static']['bottleneck_size'] = 8 * config['bottleneck_scale']
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config['cond_ae_static']['encoder_depths'] = [3, 3, 3, 27, 3]
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config['cond_ae_static']['encoder_dims'] = [8, 16, 32, 64, config['cond_ae_static']['bottleneck_size']]
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config['cond_ae_static']['decoder_depths'] = config['cond_ae_static']['encoder_depths']
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config['cond_ae_static']['decoder_dims'] = config['cond_ae_static']['encoder_dims']
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config['cond_ae_static']['activation'] = 'tanh'
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config['cond_ae_curv'] = dict()
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config['cond_ae_curv']['is_label'] = True
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config['cond_ae_curv']['kernel_size'] = 7
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config['cond_ae_curv']['bottleneck_size'] = 40 * config['bottleneck_scale']
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config['cond_ae_curv']['encoder_depths'] = [3, 3, 9, 9, 3]
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config['cond_ae_curv']['encoder_dims'] = [16, 32, 64, 128, config['cond_ae_curv']['bottleneck_size']]
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config['cond_ae_curv']['decoder_depths'] = config['cond_ae_curv']['encoder_depths']
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config['cond_ae_curv']['decoder_dims'] = config['cond_ae_curv']['encoder_dims']
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config['cond_ae_curv']['activation'] = 'tanh'
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config['cond_ae_body'] = dict()
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config['cond_ae_body']['is_label'] = False
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config['cond_ae_body']['kernel_size'] = 7
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config['cond_ae_body']['bottleneck_size'] = 16 * config['bottleneck_scale']
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config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3]
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config['cond_ae_body']['encoder_dims'] = [16, 32, 64, 128, config['cond_ae_body']['bottleneck_size']]
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config['cond_ae_body']['decoder_depths'] = config['cond_ae_body']['encoder_depths']
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config['cond_ae_body']['decoder_dims'] = config['cond_ae_body']['encoder_dims']
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config['cond_ae_body']['activation'] = 'tanh'
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@@ -0,0 +1,190 @@
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config = dict()
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config['gpu'] = '7'
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config['name'] = 'iccv_pyr_32_64_128_skirt_dress'
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config['notes'] = ''
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config['tags'] = ['pyr', 'iccv']
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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['use_skinning'] = True # and deshaping
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config['remove_global_orientation'] = True
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config['use_extra_losses'] = True # edge, collision, 3d mesh
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config['use_offsets'] = False
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config['use_norm_loss'] = True
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config['use_curvature'] = True
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config['pretrained_model'] = ''
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config['pretrained_model_iteration'] = ''
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config['pyramid'] = dict()
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config['pyramid']['resolutions'] = [32, 64, 128]
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config['pyramid']['pretrained_pyramid'] = 'checkpoints/iccv/iccv_pyr_32_64_skirt_dress'
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config['pyramid']['final_upscale_enhancer'] = ''
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config['train_dir'] = '/home/workspace/local-data/train_skirt'
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config['valid_dir'] = '/home/workspace/local-data_127/valid_skirt'
|
||||
config['test_dir'] = '/home/workspace/local-data/test_skirt_ready_2'
|
||||
config['frames_file'] = 'frames_dress.txt'
|
||||
config['frames_file_valid'] = 'frames_dress.txt'
|
||||
config['frames_file_test'] = 'frames_dress.txt'
|
||||
|
||||
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),
|
||||
}
|
||||
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_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, 3, 9, 3]
|
||||
level['encoder_dims'] = [16, 32, 64, 128, level['latent_dim']]
|
||||
level['decoder_depths'] = level['encoder_depths']
|
||||
level['decoder_dims'] = level['encoder_dims']
|
||||
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'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [64, 128, 128, 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_256_2_skirt'#'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'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [128, 128, 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_128_2_skirt'#'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_skirt'#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'
|
||||
@@ -0,0 +1,190 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '3'
|
||||
config['name'] = 'iccv_pyr_32_64_128_skirt_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'] = 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['use_curvature'] = True
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
config['pretrained_model_iteration'] = ''
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32, 64, 128]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/iccv/iccv_pyr_32_64_skirt_skirt'
|
||||
config['pyramid']['final_upscale_enhancer'] = ''
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['valid_dir'] = '/home/workspace/local-data_127/valid_skirt'
|
||||
config['test_dir'] = '/home/workspace/local-data/test_skirt_ready_2'
|
||||
config['frames_file'] = 'frames_skirt.txt'
|
||||
config['frames_file_valid'] = 'frames_skirt.txt'
|
||||
config['frames_file_test'] = 'frames_skirt.txt'
|
||||
|
||||
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),
|
||||
}
|
||||
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_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, 3, 9, 3]
|
||||
level['encoder_dims'] = [16, 32, 64, 128, level['latent_dim']]
|
||||
level['decoder_depths'] = level['encoder_depths']
|
||||
level['decoder_dims'] = level['encoder_dims']
|
||||
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'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [64, 128, 128, 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_256_2_skirt'#'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'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [128, 128, 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_128_2_skirt'#'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_skirt'#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'
|
||||
@@ -0,0 +1,197 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '3'
|
||||
config['name'] = 'iccv_pyr_32_64_128_top'
|
||||
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['use_curvature'] = True
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
config['pretrained_model_iteration'] = ''
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32, 64, 128]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/iccv/iccv_pyr_32_64_top'
|
||||
config['pyramid']['final_upscale_enhancer'] = ''
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/local-data_127/test_ready'
|
||||
config['train_dir_skirt'] = '/home/workspace/local-data_128/train_skirt'
|
||||
config['valid_dir_skirt'] = '/home/workspace/local-data/valid_skirt'
|
||||
config['test_dir_skirt'] = '/home/workspace/local-data_128/test_skirt_ready_2'
|
||||
config['frames_file'] = 'frames_top.txt'
|
||||
config['frames_file_valid'] = 'frames_top.txt'
|
||||
config['frames_file_test'] = 'frames_top.txt'
|
||||
config['frames_file_skirt'] = 'frames_top.txt'
|
||||
config['frames_file_valid_skirt'] = 'frames_top.txt'
|
||||
config['frames_file_test_skirt'] = 'frames_top.txt'
|
||||
|
||||
|
||||
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, 3, 9, 3]
|
||||
level['encoder_dims'] = [16, 32, 64, 128, level['latent_dim']]
|
||||
level['decoder_depths'] = level['encoder_depths']
|
||||
level['decoder_dims'] = level['encoder_dims']
|
||||
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'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [64, 128, 128, 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_256_2'#'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'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [128, 128, 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_128_2'#'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'
|
||||
@@ -0,0 +1,190 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '2'
|
||||
config['name'] = 'iccv_pyr_32_64_128_trousers'
|
||||
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['use_curvature'] = True
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
config['pretrained_model_iteration'] = ''
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32, 64, 128]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/iccv/iccv_pyr_32_64_trousers'
|
||||
config['pyramid']['final_upscale_enhancer'] = ''
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/local-data_127/test_ready'
|
||||
config['frames_file'] = 'frames_trousers.txt'
|
||||
config['frames_file_valid'] = 'frames_trousers.txt'
|
||||
config['frames_file_test'] = 'frames_trousers.txt'
|
||||
|
||||
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, 3, 9, 3]
|
||||
level['encoder_dims'] = [16, 32, 64, 128, level['latent_dim']]
|
||||
level['decoder_depths'] = level['encoder_depths']
|
||||
level['decoder_dims'] = level['encoder_dims']
|
||||
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'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [64, 128, 128, 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_256_2'#'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'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [128, 128, 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_128_2'#'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'
|
||||
@@ -0,0 +1,196 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '2'
|
||||
config['name'] = 'iccv_pyr_32_64_128_tshirt'
|
||||
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['use_curvature'] = True
|
||||
|
||||
config['pretrained_model'] = ''
|
||||
config['pretrained_model_iteration'] = ''
|
||||
|
||||
config['pyramid'] = dict()
|
||||
config['pyramid']['resolutions'] = [32, 64, 128]
|
||||
config['pyramid']['pretrained_pyramid'] = 'checkpoints/iccv/iccv_pyr_32_64_tshirt'
|
||||
config['pyramid']['final_upscale_enhancer'] = ''
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/local-data_127/test_ready'
|
||||
config['train_dir_skirt'] = '/home/workspace/local-data_128/train_skirt'
|
||||
config['valid_dir_skirt'] = '/home/workspace/local-data/valid_skirt'
|
||||
config['test_dir_skirt'] = '/home/workspace/local-data_128/test_skirt_ready_2'
|
||||
config['frames_file'] = 'frames_tshirt.txt'
|
||||
config['frames_file_valid'] = 'frames_tshirt.txt'
|
||||
config['frames_file_test'] = 'frames_tshirt.txt'
|
||||
config['frames_file_skirt'] = 'frames_tshirt.txt'
|
||||
config['frames_file_valid_skirt'] = 'frames_tshirt.txt'
|
||||
config['frames_file_test_skirt'] = 'frames_tshirt.txt'
|
||||
|
||||
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, 3, 9, 3]
|
||||
level['encoder_dims'] = [16, 32, 64, 128, level['latent_dim']]
|
||||
level['decoder_depths'] = level['encoder_depths']
|
||||
level['decoder_dims'] = level['encoder_dims']
|
||||
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'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [64, 128, 128, 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_256_2'#'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'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [128, 128, 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_128_2'#'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'
|
||||
@@ -0,0 +1,190 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '3'
|
||||
config['name'] = 'iccv_pyr_32_64_jumpsuit'
|
||||
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['use_curvature'] = 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_jumpsuit'
|
||||
config['pyramid']['final_upscale_enhancer'] = ''
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/local-data_127/test_ready'
|
||||
config['frames_file'] = 'frames_jumpsuit.txt'
|
||||
config['frames_file_valid'] = 'frames_jumpsuit.txt'
|
||||
config['frames_file_test'] = 'frames_jumpsuit.txt'
|
||||
|
||||
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, 3, 9, 3]
|
||||
level['encoder_dims'] = [16, 32, 64, 128, level['latent_dim']]
|
||||
level['decoder_depths'] = level['encoder_depths']
|
||||
level['decoder_dims'] = level['encoder_dims']
|
||||
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'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [64, 128, 128, 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_256_2'#'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'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [128, 128, 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_128_2'#'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'
|
||||
@@ -0,0 +1,190 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '3'
|
||||
config['name'] = 'iccv_pyr_32_64_skirt_dress'
|
||||
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['use_curvature'] = 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_skirt_dress'
|
||||
config['pyramid']['final_upscale_enhancer'] = ''
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['valid_dir'] = '/home/workspace/local-data_127/valid_skirt'
|
||||
config['test_dir'] = '/home/workspace/local-data/test_skirt_ready_2'
|
||||
config['frames_file'] = 'frames_dress.txt'
|
||||
config['frames_file_valid'] = 'frames_dress.txt'
|
||||
config['frames_file_test'] = 'frames_dress.txt'
|
||||
|
||||
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),
|
||||
}
|
||||
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_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, 3, 9, 3]
|
||||
level['encoder_dims'] = [16, 32, 64, 128, level['latent_dim']]
|
||||
level['decoder_depths'] = level['encoder_depths']
|
||||
level['decoder_dims'] = level['encoder_dims']
|
||||
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'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [64, 128, 128, 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_256_2_skirt'#'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'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [128, 128, 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_128_2_skirt'#'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_skirt'#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'
|
||||
@@ -0,0 +1,190 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '3'
|
||||
config['name'] = 'iccv_pyr_32_64_skirt_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'] = 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['use_curvature'] = 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_skirt_skirt'
|
||||
config['pyramid']['final_upscale_enhancer'] = ''
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train_skirt'
|
||||
config['valid_dir'] = '/home/workspace/local-data_127/valid_skirt'
|
||||
config['test_dir'] = '/home/workspace/local-data/test_skirt_ready_2'
|
||||
config['frames_file'] = 'frames_skirt.txt'
|
||||
config['frames_file_valid'] = 'frames_skirt.txt'
|
||||
config['frames_file_test'] = 'frames_skirt.txt'
|
||||
|
||||
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),
|
||||
}
|
||||
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_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, 3, 9, 3]
|
||||
level['encoder_dims'] = [16, 32, 64, 128, level['latent_dim']]
|
||||
level['decoder_depths'] = level['encoder_depths']
|
||||
level['decoder_dims'] = level['encoder_dims']
|
||||
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'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [64, 128, 128, 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_256_2_skirt'#'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'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [128, 128, 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_128_2_skirt'#'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_skirt'#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'
|
||||
@@ -0,0 +1,197 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '3'
|
||||
config['name'] = 'iccv_pyr_32_64_top'
|
||||
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['use_curvature'] = 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_top'
|
||||
config['pyramid']['final_upscale_enhancer'] = ''
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/local-data_127/test_ready'
|
||||
config['train_dir_skirt'] = '/home/workspace/local-data_128/train_skirt'
|
||||
config['valid_dir_skirt'] = '/home/workspace/local-data/valid_skirt'
|
||||
config['test_dir_skirt'] = '/home/workspace/local-data_128/test_skirt_ready_2'
|
||||
config['frames_file'] = 'frames_top.txt'
|
||||
config['frames_file_valid'] = 'frames_top.txt'
|
||||
config['frames_file_test'] = 'frames_top.txt'
|
||||
config['frames_file_skirt'] = 'frames_top.txt'
|
||||
config['frames_file_valid_skirt'] = 'frames_top.txt'
|
||||
config['frames_file_test_skirt'] = 'frames_top.txt'
|
||||
|
||||
|
||||
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, 3, 9, 3]
|
||||
level['encoder_dims'] = [16, 32, 64, 128, level['latent_dim']]
|
||||
level['decoder_depths'] = level['encoder_depths']
|
||||
level['decoder_dims'] = level['encoder_dims']
|
||||
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'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [64, 128, 128, 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_256_2'#'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'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [128, 128, 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_128_2'#'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'
|
||||
@@ -0,0 +1,190 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '2'
|
||||
config['name'] = 'iccv_pyr_32_64_trousers'
|
||||
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['use_curvature'] = 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_trousers'
|
||||
config['pyramid']['final_upscale_enhancer'] = ''
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/local-data_127/test_ready'
|
||||
config['frames_file'] = 'frames_trousers.txt'
|
||||
config['frames_file_valid'] = 'frames_trousers.txt'
|
||||
config['frames_file_test'] = 'frames_trousers.txt'
|
||||
|
||||
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, 3, 9, 3]
|
||||
level['encoder_dims'] = [16, 32, 64, 128, level['latent_dim']]
|
||||
level['decoder_depths'] = level['encoder_depths']
|
||||
level['decoder_dims'] = level['encoder_dims']
|
||||
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'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [64, 128, 128, 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_256_2'#'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'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [128, 128, 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_128_2'#'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'
|
||||
@@ -0,0 +1,196 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '2'
|
||||
config['name'] = 'iccv_pyr_32_64_tshirt'
|
||||
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['use_curvature'] = 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_tshirt'
|
||||
config['pyramid']['final_upscale_enhancer'] = ''
|
||||
|
||||
config['train_dir'] = '/home/workspace/local-data/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/local-data_127/test_ready'
|
||||
config['train_dir_skirt'] = '/home/workspace/local-data_128/train_skirt'
|
||||
config['valid_dir_skirt'] = '/home/workspace/local-data/valid_skirt'
|
||||
config['test_dir_skirt'] = '/home/workspace/local-data_128/test_skirt_ready_2'
|
||||
config['frames_file'] = 'frames_tshirt.txt'
|
||||
config['frames_file_valid'] = 'frames_tshirt.txt'
|
||||
config['frames_file_test'] = 'frames_tshirt.txt'
|
||||
config['frames_file_skirt'] = 'frames_tshirt.txt'
|
||||
config['frames_file_valid_skirt'] = 'frames_tshirt.txt'
|
||||
config['frames_file_test_skirt'] = 'frames_tshirt.txt'
|
||||
|
||||
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, 3, 9, 3]
|
||||
level['encoder_dims'] = [16, 32, 64, 128, level['latent_dim']]
|
||||
level['decoder_depths'] = level['encoder_depths']
|
||||
level['decoder_dims'] = level['encoder_dims']
|
||||
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'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [64, 128, 128, 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_256_2'#'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'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [128, 128, 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_128_2'#'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'
|
||||
@@ -0,0 +1,193 @@
|
||||
config = dict()
|
||||
|
||||
config['gpu'] = '2'
|
||||
config['name'] = 'iccv_pyr_32_test'
|
||||
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['use_curvature'] = 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/train'
|
||||
config['valid_dir'] = '/home/workspace/local-data/valid'
|
||||
config['test_dir'] = '/home/workspace/local-data_127/test_ready'
|
||||
config['train_dir_skirt'] = '/home/workspace/local-data_128/train_skirt'
|
||||
config['valid_dir_skirt'] = '/home/workspace/local-data/valid_skirt'
|
||||
config['test_dir_skirt'] = '/home/workspace/local-data_128/test_skirt_ready_2'
|
||||
config['frames_file'] = 'frames_top.txt'
|
||||
config['frames_file_valid'] = 'frames_top.txt'
|
||||
config['frames_file_test'] = 'frames_top.txt'
|
||||
|
||||
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, 3, 9, 3]
|
||||
level['encoder_dims'] = [16, 32, 64, 128, level['latent_dim']]
|
||||
level['decoder_depths'] = level['encoder_depths']
|
||||
level['decoder_dims'] = level['encoder_dims']
|
||||
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'] = [3, 3, 9, 3]
|
||||
level['encoder_dims'] = [64, 128, 128, 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_256_2'#'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'] = [9, 9, 9]
|
||||
level['encoder_dims'] = [128, 128, 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_128_2'#'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'
|
||||
+30
-11
@@ -1,6 +1,6 @@
|
||||
import os
|
||||
import sys
|
||||
from configs.iccv.config_abl_pyr_32_tshirt import config
|
||||
from configs.iccv.config_abl_pyr_32_64_128_skirt_dress import config
|
||||
|
||||
os.environ["CUDA_DEVICE_ORDER"]="PCI_BUS_ID"
|
||||
os.environ["CUDA_VISIBLE_DEVICES"] = config['gpu']
|
||||
@@ -39,12 +39,13 @@ else:
|
||||
from losses import uv_mask_loss, bend_loss, kl_loss, collision_ratio, normal_loss
|
||||
# from losses import collision_penalty as collision_penalty
|
||||
from losses import collision_loss as collision_penalty
|
||||
from custom_utils.custom_utils import batch_to_dict, load_model
|
||||
from custom_utils.custom_utils import batch_to_dict, load_model, save_stl
|
||||
from dataset import DatasetFactory, StaticDataset
|
||||
from custom_utils.smpl import SMPL
|
||||
from models.pyramid_model_optimized import PyramidNew as Pyramid
|
||||
from postprocessing import fix_collision
|
||||
from custom_utils.custom_utils import Accumulator
|
||||
from sample_pro_2 import postprocess
|
||||
|
||||
|
||||
def init_wandb():
|
||||
@@ -682,9 +683,10 @@ def test():
|
||||
|
||||
|
||||
def generate_results():
|
||||
load_model(model, 'checkpoints/' + config['name'])
|
||||
load_model(model, 'checkpoints/iccv/' + config['name'])
|
||||
F = np.load("custom_utils/smpl_faces" + skirt_modifier + ".npy").astype(np.int32)
|
||||
|
||||
dataset_test = factory.get_dataset(folder=config['test_dir'],
|
||||
dataset_test = factory.get_dataset(folder=config['train_dir'],
|
||||
batch_size=config['batch_size'],
|
||||
# batch_size=1,
|
||||
signature=config['signature_dynamic'],
|
||||
@@ -693,15 +695,16 @@ def generate_results():
|
||||
is_cape=config['is_cape'],
|
||||
frames_file=config['frames_file'] if 'frames_file' in config.keys() else None,
|
||||
do_repeat=False,
|
||||
shuffle=False)
|
||||
static_dataset_test = StaticDataset(folder=config['test_dir'],
|
||||
shuffle=True)
|
||||
static_dataset_test = StaticDataset(folder=config['train_dir'],
|
||||
signature=config['signature_static'],
|
||||
resolutions=dataset_resolutions,
|
||||
in_memory=True,
|
||||
is_cape=config['is_cape'])
|
||||
folder = os.path.join('/home/workspace/data/results/cape', config['name'])
|
||||
folder = os.path.join('examples/qualitative', config['name'])
|
||||
os.makedirs(folder, exist_ok=True)
|
||||
|
||||
|
||||
for batch in tqdm.tqdm(dataset_test):
|
||||
batch = static_dataset_test.expand_batch(batch_to_dict(batch, config['signature_dynamic']))
|
||||
|
||||
@@ -718,14 +721,28 @@ def generate_results():
|
||||
mesh_pred = uv2mesh(pred)
|
||||
mesh_pred_shaped = mesh_pred + shape_offsets * batch['mesh_mask'][:,:,tf.newaxis]
|
||||
mesh_pred_posed = smpl.run_garment(batch['pose_shape'][:, :72], batch['pose_shape'][:, 72:], mesh_pred_shaped)
|
||||
mesh_gt = batch['mesh_posed'].numpy()
|
||||
body = batch['mesh_body_posed'].numpy()
|
||||
|
||||
for i in range(batch['id'].shape[0]):
|
||||
mask = batch['mesh_mask'][i].numpy().astype(bool)
|
||||
id, frame_nr = batch['id'][i].numpy().decode("utf-8"), batch['frame_nr'][i].numpy().decode("utf-8")
|
||||
unposed = mesh_pred[i].numpy()[mask, :]
|
||||
posed = mesh_pred_posed[i].numpy()[mask, :]
|
||||
np.save(os.path.join(folder, id + '_' + frame_nr + '_posed.npy'), posed)
|
||||
np.save(os.path.join(folder, id + '_' + frame_nr + '_unposed.npy'), unposed)
|
||||
_, faces_garment = _maskFaces(np.zeros((14475, 3), np.float32), F, mask)
|
||||
faces_garment = faces_garment.astype(np.int32)
|
||||
posed_unmasked = np.zeros((1, 14475, 3), np.float32)
|
||||
posed_unmasked[0, mask, :] = posed
|
||||
posed = postprocess(posed_unmasked, body[i], faces_garment, mask, do_smoothing=True)
|
||||
unposed_unmasked = np.zeros((1, 14475, 3), np.float32)
|
||||
unposed_unmasked[0, mask, :] = unposed
|
||||
unposed = postprocess(unposed_unmasked, body[i], faces_garment, mask, do_smoothing=True)
|
||||
save_stl(os.path.join(folder, id + '_' + frame_nr + '_posed.stl'), posed, faces_garment)
|
||||
save_stl(os.path.join(folder, id + '_' + frame_nr + '_unposed.stl'), unposed, faces_garment)
|
||||
save_stl(os.path.join(folder, id + '_' + frame_nr + '_gt.stl'), mesh_gt[i][mask, :], faces_garment)
|
||||
print(id + '_' + frame_nr)
|
||||
# np.save(os.path.join(folder, id + '_' + frame_nr + '_posed.npy'), posed)
|
||||
# np.save(os.path.join(folder, id + '_' + frame_nr + '_unposed.npy'), unposed)
|
||||
|
||||
pass
|
||||
|
||||
@@ -772,7 +789,7 @@ if __name__ == '__main__':
|
||||
in_memory=config['dataset_in_memory'],
|
||||
is_cape=config['is_cape'],
|
||||
frames_file=config['frames_file'] if 'frames_file' in config.keys() else None,
|
||||
frames_file_skirt=config['frames_file'] if 'frames_file' in config.keys() else '',
|
||||
frames_file_skirt=config['frames_file_skirt'] if 'frames_file_skirt' in config.keys() else '',
|
||||
folder_skirt=config['train_dir_skirt'] if 'train_dir_skirt' in config.keys() else '',
|
||||
)
|
||||
static_dataset_train = StaticDataset(folder=config['train_dir'],
|
||||
@@ -788,7 +805,7 @@ if __name__ == '__main__':
|
||||
in_memory=config['dataset_in_memory'],
|
||||
is_cape=config['is_cape'],
|
||||
frames_file=config['frames_file_valid'] if 'frames_file_valid' in config.keys() else None,
|
||||
frames_file_skirt=config['frames_file_valid'] if 'frames_file_valid' in config.keys() else '',
|
||||
frames_file_skirt=config['frames_file_valid_skirt'] if 'frames_file_valid_skirt' in config.keys() else '',
|
||||
folder_skirt=config['valid_dir_skirt'] if 'valid_dir_skirt' in config.keys() else '',
|
||||
)
|
||||
static_dataset_valid = StaticDataset(folder=config['valid_dir'],
|
||||
@@ -812,6 +829,8 @@ if __name__ == '__main__':
|
||||
|
||||
# generate_results()
|
||||
|
||||
|
||||
|
||||
ckpt = tf.train.Checkpoint(model=model)
|
||||
manager = tf.train.CheckpointManager(ckpt, 'checkpoints/iccv/' + config['name'], max_to_keep=20)
|
||||
train_accumulator = Accumulator()
|
||||
|
||||
Reference in New Issue
Block a user