generate curv with 100

aaa_helpers.txt

@@ -1,3 +1,5 @@
+nohup python curvature_labels.py  > nohup/curv_labels_train_skirt_15k_25k.out 2>&1 &
+
 one final convolutional layer for smoothing, on the final coordinates
 
 skirts!!!!

curvature_labels.py

@@ -252,8 +252,8 @@ def read_raw_curvatures(folder, frames, neighbourhood):
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument("-f", "--folder", help = "process the given folder", default=r'/home/workspace/data/dataset/local-cache/train_skirt')
-    parser.add_argument("-s", "--start", help = "start of range", default=5000)
-    parser.add_argument("-e", "--end", help = "end of range", default=15000)
+    parser.add_argument("-s", "--start", help = "start of range", default=15000)
+    parser.add_argument("-e", "--end", help = "end of range", default=25000)
     parser.add_argument("-n", "--name", help = "end of range", default="lhunor")
     args = parser.parse_args()
 
@@ -274,6 +274,7 @@ if __name__ == '__main__':
         dist = np.load('custom_data/dijkstra_skirt.npy')
 
     print('SKIRT' if is_skirt else 'NOT SKIRT')
+    print(f'params: -f {args.folder} -s {args.start} -e {args.end} -n {args.name} -skirt {is_skirt} -neigh {neighbourhood}')
 
     # frames = sorted(os.listdir(os.path.join(folder, 'mesh_posed')))[int(args.start):int(args.end)]
     # frames = [frame.split('.')[0] for frame in frames]