making ready for skirts

configs/config_ae_body.py

@@ -1,8 +1,8 @@
 from configs.config_base import config
 
-config['gpu'] = '1'
+config['gpu'] = '3'
 config['lr'] = 0.0001
-config['name'] = 'ae_body_10_3'
+config['name'] = 'ae_body_10_3_skirt'
 
 config['notes'] = 'convnext + convnext, add dense with tanh at the end of reverse convnext,\
     flattened bottleneck with 128 latent_dim\ remove global orientation\
@@ -13,7 +13,7 @@ config['notes'] = 'convnext + convnext, add dense with tanh at the end of revers
     larger batch size, 32 instead of 4\
     '
 
-config['dataset_in_memory'] = False
+config['dataset_in_memory'] = True
 config['batch_size'] = 32
 
 

configs/config_ae_curv.py

@@ -1,8 +1,9 @@
 from configs.config_base import config
 
-config['gpu'] = '2'
+config['gpu'] = '0'
 config['lr'] = 0.001
-config['name'] = 'x' #'ae_curv_9'
+config['name'] = 'ae_curv_9_skirt' #'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'
 
 config['cond_ae']['is_label'] = True
 config['cond_ae']['upscale_output'] = False

configs/config_ae_static.py

@@ -1,8 +1,8 @@
 from configs.config_base import config
 
-config['gpu'] = '1'
+config['gpu'] = '2'
 config['lr'] = 0.0005
-config['name'] = 'ae_static_7_2'
+config['name'] = 'ae_static_7_2_skirt'
 
 config['cond_ae']['upscale_output'] = False
 

configs/config_base.py

@@ -2,15 +2,17 @@ config = dict()
 
 
 config['batch_size'] = 4
-config['train_dir'] = '/home/workspace/local-data/train_100'
-config['valid_dir'] = '/home/workspace/local-data/train_100'
+config['train_dir'] = '/home/workspace/local-data/train_skirt_25_2'
+config['valid_dir'] = '/home/workspace/local-data/train_skirt_25_2'
 config['use_filled'] = False
 config['resolution'] = 512
+config['is_skirt'] = True
 
 config['latent_dim'] = 128
 
 config['cond_ae'] = dict()
 config['cond_ae']['is_label'] = False
+config['cond_ae']['upscale_output'] = False
 config['cond_ae']['latent_dim'] = config['latent_dim']
 config['cond_ae']['kernel_size'] = 7
 config['cond_ae']['bottleneck_size'] = 64
@@ -18,4 +20,15 @@ config['cond_ae']['encoder_depths'] = [3, 3, 9, 9, 3]
 config['cond_ae']['encoder_dims'] = [32, 64, 128, 256, config['cond_ae']['bottleneck_size']]
 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']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
+
+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

@@ -1,7 +1,7 @@
 from configs.config_base import config
 
-config['gpu'] = '4'
-config['name'] = 'cvae_low_4_3_d32'
+config['gpu'] = '2'
+config['name'] = 'cvae_19_skirt'
 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 \
@@ -11,13 +11,13 @@ remove shape from unposed garment\
 training on 100 garments with offsets over the average of these\
 fixed autoencoders!!!!!!!!!\
 cvae only loads encoders instead AEs\
-full res loss\
 '
-config['dataset_in_memory'] = False
+config['dataset_in_memory'] = True
 
 
-config['resolution'] = 32
-
+config['resolution'] = 512
+config['is_skirt'] = True
+config['reg_loss_coeff'] = 0 # set to 0 if don't want to use edge+collision
 
 if config['resolution'] != 512:
   config['notes'] += '\
@@ -50,13 +50,14 @@ 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_100_no_shape_avg_uv.npy'
+  config['avg_garment_path'] = 'custom_data/train_skirt_25_2_no_shape_avg_uv.npy'
 else:
   config['avg_garment_path'] = ''
 
-config['static_model'] = 'checkpoints/ae_static_7_2_x'
-config['body_model'] = 'checkpoints/ae_body_9_x'
-config['curvature_model'] = 'checkpoints/ae_curv_9_x'
+config['static_model'] = 'checkpoints/ae_static_7_2_skirt_x'
+config['body_model'] = 'checkpoints/ae_body_10_3_skirt_x'
+config['curvature_model'] = 'checkpoints/ae_curv_9_skirt_x'
+config['upscale_enhancer'] = 'checkpoints/up_2_3_skirt_x_d32'
 config['freeze_encoders'] = True
 
 config['cvae'] = dict()