save configs

configs/config_ae_body.py

@@ -1,6 +1,6 @@
 from configs.config_base import config
 
-config['gpu'] = '0'
+config['gpu'] = '1'
 config['lr'] = 0.0001
 config['name'] = 'body_1'
 

configs/config_ae_curv.py

@@ -1,10 +1,12 @@
 from configs.config_base import config
 
-config['gpu'] = '2'
+config['gpu'] = '5'
 config['lr'] = 0.001
-config['name'] = 'curv_1_3' #'ae_curv_9'
+config['name'] = 'curv_1_5' #'ae_curv_9'
 config['notes'] = 'convnext + convnext, 16*8*32, ce loss. flattened latent dim of 128. trained on 100 garments. switched back to sparse CCE, normal one was giving NaN | \
-  try ssim loss'
+  try ssim loss | \
+  smaller model | \
+  '
 
 config['cond_ae']['is_label'] = True
 

configs/config_ae_static.py

@@ -1,10 +1,17 @@
 from configs.config_base import config
 
-config['gpu'] = '5'
+config['gpu'] = '4'
 config['lr'] = 0.0005
-config['name'] = 'static_1'
+config['name'] = 'static_1_5'
+config['notes'] = 'convnext + convnext, add dense with tanh at the end of reverse convnext, | \
+    flattened latent dim to 128 | \
+    train on 100 garments | \
+    deeper model | \
+    larger batch size | \
+    ' 
 
 config['cond_ae']['upscale_output'] = False
+config['batch_size'] = 32
 
 
 config['signature_dynamic'] = { 'id': (), }

configs/config_base.py

@@ -4,6 +4,7 @@ config = dict()
 config['batch_size'] = 4
 config['train_dir'] = '/home/workspace/local-data/train'
 config['valid_dir'] = '/home/workspace/local-data/valid'
+config['test_dir'] = '/home/workspace/data/dataset/test_ready'
 config['use_filled'] = False
 config['resolution'] = 512
 config['is_skirt'] = False
@@ -23,14 +24,26 @@ config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size']
 config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
 config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
 
-config['cond_ae_body'] = config['cond_ae']
+# config['cond_ae'] = dict()
-# config['cond_ae_body'] = dict()
+# config['cond_ae']['is_label'] = False
-# config['cond_ae_body']['latent_dim'] = config['latent_dim']
+# config['cond_ae']['upscale_output'] = False
-# config['cond_ae_body']['kernel_size'] = 7
+# config['cond_ae']['latent_dim'] = config['latent_dim']
-# config['cond_ae_body']['upscale_output'] = True
+# config['cond_ae']['kernel_size'] = 7
-# config['cond_ae_body']['bottleneck_size'] = 512
+# config['cond_ae']['bottleneck_size'] = 64
-# config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
+# config['cond_ae']['encoder_depths'] = [3, 3, 3, 3, 3]
-# config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
+# config['cond_ae']['encoder_dims'] = [16, 32, 128, 128, config['cond_ae']['bottleneck_size']]
-# config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
+# config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
-# config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
+# config['cond_ae']['decoder_depths'] = [3, 3, 3, 3, 3]
-# config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
+# config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 128, 128, 32, 8]
+
+# config['cond_ae_body'] = config['cond_ae']
+config['cond_ae_body'] = dict()
+config['cond_ae_body']['latent_dim'] = config['latent_dim']
+config['cond_ae_body']['kernel_size'] = 7
+config['cond_ae_body']['upscale_output'] = True
+config['cond_ae_body']['bottleneck_size'] = 512
+config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
+config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
+config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
+config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
+config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]

configs/config_cvae.py

@@ -1,23 +1,31 @@
 from configs.config_base import config
 
-config['gpu'] = '2'
+config['gpu'] = '4'
-config['name'] = 'cvae_19_skirt'
+config['name'] = 'v2_4'
 config['notes'] = '\
-offsets over average unposed garment. remove global orientation (in posed body input and in pose_shape parameters. \
+offsets over average unposed garment. remove global orientation (in posed body input and in pose_shape parameters. | \
-retrained body encoder with deoriented bodies \
+retrained body encoder with deoriented bodies | \
-use mean l2 loss. small batch. l2 * 1000, balancing to 1 from 0.01\
+use mean l2 loss. small batch. l2 * 1000, balancing to 1 from 0.01 | \
-fixed gender issue and retrained body encoder, FINAL\
+fixed gender issue and retrained body encoder, FINAL | \
-remove shape from unposed garment\
+remove shape from unposed garment | \
-training on 100 garments with offsets over the average of these\
+training on 100 garments with offsets over the average of these | \
-fixed autoencoders!!!!!!!!!\
+fixed autoencoders!!!!!!!!! | \
-cvae only loads encoders instead AEs\
+cvae only loads encoders instead AEs | \
+increase balancing coeff sooner | \
 '
-config['dataset_in_memory'] = True
+config['dataset_in_memory'] = False
+
+
+# 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
 
 
 config['resolution'] = 512
-config['is_skirt'] = True
+config['is_skirt'] = False
-config['reg_loss_coeff'] = 0 # set to 0 if don't want to use edge+collision
+config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
 
 if config['resolution'] != 512:
   config['notes'] += '\
@@ -50,14 +58,14 @@ if config['resolution'] != 512:
   config['signature_static']['uv_mask' + res_modifier] = (config['resolution'], config['resolution']//2)
 
 if config['resolution'] == 512:
-  config['avg_garment_path'] = 'custom_data/train_skirt_25_2_no_shape_avg_uv.npy'
+  config['avg_garment_path'] = 'custom_data/train_no_shape_avg_uv.npy'
 else:
   config['avg_garment_path'] = ''
 
-config['static_model'] = 'checkpoints/ae_static_7_2_skirt_x'
+config['static_model'] = 'checkpoints/static_1'
-config['body_model'] = 'checkpoints/ae_body_10_3_skirt_x'
+config['body_model'] = 'checkpoints/body_1'
-config['curvature_model'] = 'checkpoints/ae_curv_9_skirt_x'
+config['curvature_model'] = 'checkpoints/curv_1'
-config['upscale_enhancer'] = 'checkpoints/up_2_3_skirt_x_d32'
+config['upscale_enhancer'] = ''
 config['freeze_encoders'] = True
 
 config['cvae'] = dict()

configs/config_pyramid.py

@@ -1,7 +1,7 @@
 from configs.config_base import config
 
-config['gpu'] = '1'
+config['gpu'] = '3'
-config['name'] = 'cvae_pyr_7_32_64_128_256_512'
+config['name'] = 'pyr_1_32_64_128'
 config['notes'] = '\
 offsets over average unposed garment. remove global orientation (in posed body input and in pose_shape parameters. | \
 retrained body encoder with deoriented bodies | \
@@ -56,9 +56,9 @@ config['pyramid'] = dict()
 config['pyramid']['is_label'] = False
 config['pyramid']['latent_dim'] = config['latent_dim']
 
-config['pyramid']['resolutions'] = [32, 64, 128, 256, 512]
+config['pyramid']['resolutions'] = [32, 64, 128]
 config['pyramid']['loss_weights'] = [1,1,1,1,1]
-config['pyramid']['pretrained_pyramid'] = 'checkpoints/cvae_pyr_7_32_64_128_256_50k'
+config['pyramid']['pretrained_pyramid'] = 'checkpoints/pyr_1_32_64'
 
 for res in config['pyramid']['resolutions']:
   if res != 512:
@@ -73,13 +73,16 @@ for res in config['pyramid']['resolutions']:
 # config['pyramid']['static_model'] = 'checkpoints/ae_static_7_2_x'
 # config['pyramid']['body_model'] = 'checkpoints/ae_body_9_x'
 # config['pyramid']['curvature_model'] = 'checkpoints/ae_curv_9_x'
+# config['pyramid']['static_model'] = 'checkpoints/static_1'
+# config['pyramid']['body_model'] = 'checkpoints/body_1'
+# config['pyramid']['curvature_model'] = 'checkpoints/curv_1'
 config['pyramid']['static_model'] = ''
 config['pyramid']['body_model'] = ''
 config['pyramid']['curvature_model'] = ''
 config['pyramid']['freeze_encoders'] = True
 
 config['avg_garment_path'] = ''
-config['pyramid']['final_upscale_enhancer'] = ''
+config['pyramid']['final_upscale_enhancer'] = 'checkpoints/128_512_3'
 
 
 config['pyramid']['levels'] = []
@@ -108,7 +111,7 @@ for res in config['pyramid']['resolutions']:
     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/up_3_d256_512_2'
     level['upscale_enhancer_freeze'] = True
     config['pyramid']['levels'].append(level)
   elif res == 128:
@@ -122,7 +125,7 @@ for res in config['pyramid']['resolutions']:
     level['decoder_depths'] = [16, 16, 9, 9]
     level['decoder_dims'] = [256, 256, 128, 64]
     level['avg_garment_path'] = ''
-    level['upscale_enhancer'] = 'checkpoints/up_3_d128_256_2'
+    level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
     level['upscale_enhancer_freeze'] = True
     config['pyramid']['levels'].append(level)
   elif res == 64:
@@ -136,7 +139,7 @@ for res in config['pyramid']['resolutions']:
     level['decoder_depths'] = [27, 27, 16]
     level['decoder_dims'] = [256, 256, 256]
     level['avg_garment_path'] = ''
-    level['upscale_enhancer'] = 'checkpoints/up_3_d64_128_2'
+    level['upscale_enhancer'] = 'checkpoints/64_512_2'#checkpoints/up_3_d64_128_2'
     level['upscale_enhancer_freeze'] = False
     config['pyramid']['levels'].append(level)
   elif res == 32:
@@ -150,7 +153,7 @@ for res in config['pyramid']['resolutions']:
     level['decoder_depths'] = [27, 27]
     level['decoder_dims'] = [256, 256]
     level['avg_garment_path'] = ''
-    level['upscale_enhancer'] = 'checkpoints/up_3_d32_64_2'
+    level['upscale_enhancer'] = 'checkpoints/32_512_4'#'checkpoints/up_3_d32_64_2'
     level['upscale_enhancer_freeze'] = True
     config['pyramid']['levels'].append(level)
   else: