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started training pyramid

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luni
2023-02-26 22:25:50 +00:00
parent a678724711
commit 64ecb900f5
8 changed files with 314 additions and 79 deletions
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configs/iccv/config_abl_pyr_32.py
+29 -25
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@@ -1,6 +1,6 @@
config = dict()
config['gpu'] = '2'
config['gpu'] = '0'
config['name'] = 'iccv_pyr_32'
config['notes'] = ''
config['tags'] = ['pyr', 'iccv']
@@ -47,6 +47,7 @@ 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,),
@@ -63,8 +64,8 @@ config['signature_static'] = { 'uv_static': (512, 256, 3),
}
config['pyramid']['is_label'] = False
config['pyramid']['add_noise'] = True
config['pyramid']['noise_amount'] = 0.001
config['pyramid']['add_noise'] = False
config['pyramid']['noise_amount'] = 0.0
config['pyramid']['loss_weights'] = [1,1,1,1,1]
@@ -77,9 +78,10 @@ for res in config['pyramid']['resolutions']:
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/post/static_post_2'
config['pyramid']['body_model'] = 'checkpoints/post/body_post_2'
config['pyramid']['curvature_model'] = 'checkpoints/post/curv_post_1'
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
@@ -88,10 +90,10 @@ for res in config['pyramid']['resolutions']:
if res == 512:
level = dict()
level['resolution'] = 512
level['latent_dim'] = config['latent_dim']
level['latent_dim'] = 64 * config['bottleneck_scale']
level['kernel_size'] = 7
level['encoder_depths'] = [3, 3, 9, 3]
level['encoder_dims'] = [32, 64, 128, 64]
level['encoder_dims'] = [32, 64, 128, level['latent_dim']]
level['decoder_input'] = (16, 8, 80)
level['decoder_depths'] = [3, 3, 9, 3]
level['decoder_dims'] = [256, 128, 64, 16]
@@ -101,53 +103,55 @@ for res in config['pyramid']['resolutions']:
elif res == 256:
level = dict()
level['resolution'] = 256
level['latent_dim'] = config['latent_dim']
level['kernel_size'] = 7
level['latent_dim'] = 64 * config['bottleneck_scale']
level['kernel_size'] = 5
level['encoder_depths'] = [9, 9, 9, 9]
level['encoder_dims'] = [32, 64, 128, 64]
level['encoder_dims'] = [32, 64, 128, level['latent_dim']]
level['decoder_input'] = (8, 4, 128)
level['decoder_depths'] = [9, 9, 9, 9]
level['decoder_dims'] = [256, 128, 64, 16]
level['avg_garment_path'] = ''
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
level['upscale_enhancer'] = 'checkpoints/iccv/iccv_'#'checkpoints/up_3_d256_512_2'
level['upscale_enhancer_freeze'] = True
config['pyramid']['levels'].append(level)
elif res == 128:
level = dict()
level['resolution'] = 128
level['latent_dim'] = config['latent_dim']
level['latent_dim'] = 64 * config['bottleneck_scale']
level['kernel_size'] = 5
level['encoder_depths'] = [16, 9, 9, 9]
level['encoder_dims'] = [64, 128, 128, 64]
level['decoder_input'] = (4, 2, 128)
level['decoder_depths'] = [16, 9, 9, 9]
level['decoder_dims'] = [256, 128, 128, 64]
level['decoder_dims'] = [256, 128, 128, level['latent_dim']]
level['avg_garment_path'] = ''
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
level['upscale_enhancer'] = 'checkpoints/iccv/iccv_'#'checkpoints/up_3_d128_256_2'
level['upscale_enhancer_freeze'] = True
config['pyramid']['levels'].append(level)
elif res == 64:
level = dict()
level['resolution'] = 64
level['kernel_size'] = 5
level['latent_dim'] = 64 * config['bottleneck_scale']
level['kernel_size'] = 3
level['encoder_depths'] = [9, 9]
level['encoder_dims'] = [64, 64]
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/64_512_2'#checkpoints/up_3_d64_128_2'
level['upscale_enhancer'] = 'checkpoints/iccv/iccv_'#checkpoints/up_3_d64_128_2'
level['upscale_enhancer_freeze'] = True
config['pyramid']['levels'].append(level)
elif res == 32:
level = dict()
level['resolution'] = 32
level['latent_dim'] = 64 * config['bottleneck_scale']
level['kernel_size'] = 3
level['encoder_depths'] = [16]
level['encoder_dims'] = [64]
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/32_512_4'#'checkpoints/up_3_d32_64_2'
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:
@@ -156,9 +160,9 @@ for res in config['pyramid']['resolutions']:
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['cond_ae_static']['encoder_depths'] = [3, 3, 3, 9, 3]
config['cond_ae_static']['encoder_dims'] = [16, 32, 64, 64, config['cond_ae_static']['bottleneck_size']]
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'
@@ -166,7 +170,7 @@ 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['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']
@@ -176,7 +180,7 @@ 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['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']