train encoder with radius 100

auto_encoder_curv.py

@@ -1,6 +1,6 @@
 import os
 import sys
-from configs.config_ae_curv_1_orig_curv_10_10p_r2 import config
+from configs.config_ae_curv_1_orig_curv_100_10p_r2 import config
 os.environ["CUDA_VISIBLE_DEVICES"] = config['gpu']
 
 import tensorflow as tf

configs/config_ae_curv_1_orig_curv_100_10p_r2.py

@@ -0,0 +1,30 @@
+from configs.config_base import config
+
+config['gpu'] = '1'
+config['lr'] = 0.001
+config['name'] = 'curv_1_orig_curv_100_10p_r2' #'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['tags'] = ['review_2']
+config['remove_global_orientation'] = True
+config['dataset_in_memory'] = True
+
+config['cond_ae']['is_label'] = True
+config['is_skirt'] = True
+
+config['train_dir'] = '/home/workspace/data/dataset/local-cache/train_skirt'
+config['valid_dir'] = '/home/workspace/local-data/valid_skirt'
+config['test_dir'] = '/home/workspace/data/dataset/test_skirt_ready_2'
+config['frames_file'] = 'frames_skirt_10p.txt'
+config['frames_file_valid'] = 'frames_skirt_10p.txt'
+config['curv_neighbourhood'] = 100
+
+config['signature_dynamic'] = { 'id': (), 'frame_nr': (),
+                          'uv_curvature': (512, 256, 7),
+                          'mesh_curvature':  (config['smpl_res'])
+                        }
+config['signature_static'] = { 'mesh_mask': (config['smpl_res'],),
+                         'uv_mask': (512, 256,),
+                        }
+