slowly update dataset (untested)

data/preprocessing.py

@@ -75,7 +75,31 @@ def split_data(folder, ratio):
         f.writelines(valid_frames)
 
 
-    pass
+def genereated_registered_and_mask(folder, is_skirt = False):
+    ids = os.listdir(folder)
+
+    for id in tqdm(ids):
+        garment_dir = os.path.join(folder, id)
+        if not os.path.isdir(garment_dir):
+            continue
+        garments = [f.replace('.pc16','') for f in os.listdir(garment_dir) if f.find('_') == -1 and not f.endswith('.mat') and not f.endswith('.obj') and not f.startswith('Combined')]
+        
+        assert len(garments) == 1
+
+        if os.path.exists(os.path.join(garment_dir, garments[0] + '_registered.pc16')):
+            continue
+        
+        garment = garments[0]
+
+        verts = readPC2(os.path.join(garment_dir, garment + '.pc16'), True)['V']
+        map = sio.loadmat(os.path.join(garment_dir, garment + '_map.mat'))['map'].reshape((-1))
+        verts = verts[:, map, :] # ---------------> This is the garment after registration
+        raw_mask = sio.loadmat(os.path.join(garment_dir, garment + '_mask.mat'))['mask'].reshape((-1))
+        mask = raw_mask > 0
+        # boundaries = raw_mask == 2
+
+        writePC2(os.path.join(garment_dir, garment + '_registered.pc16'), verts, True)
+        np.save(os.path.join(garment_dir, garment + '_mask.npy'), mask)