diff --git a/downscale.py b/downscale.py
index 31ac1b9..609c288 100644
--- a/downscale.py
+++ b/downscale.py
@@ -28,6 +28,8 @@ def fill(img, mask):
     img_data = img[img_idx[:,0], img_idx[:,1], :]
 
     interpolator =  spi.NearestNDInterpolator(x=img_idx, y=img_data)
+    # interpolator =  spi.RBFInterpolator(y=img_idx, d=img_data, neighbors=5, kernel='linear')
+
     img_2 = interpolator(coords)
     res = np.zeros((512,256,3), dtype=np.float32)
     res[coords[:,0], coords[:,1], :] = img_2
@@ -81,20 +83,19 @@ class UVMaskStore():
 
 def downscale_uv_maps_posed_body(folder, type, sizes):
     for size in sizes:
-        os.makedirs(os.path.join(folder, type + '_' + str(size)), exist_ok=True)
+        os.makedirs(os.path.join(folder, type + '_2_' + str(size)), exist_ok=True)
 
     frames = os.listdir(os.path.join(folder, type))[int(args.start):int(args.end)]
 
     for frame in tqdm.tqdm(frames):
         id, _ = frame.split('_')
         img = np.load(os.path.join(folder, type, frame)); img = img['uv_posed_body_no_orient']
-        mask_full = uv_mask_store[512][id]
-        img = fill(img, mask_full)
+        img = fill(img, uv_masks_body[512])
         for size in sizes:
-            mask = uv_mask_store[size][id]
+            mask = uv_masks_body[size]
             down = tf.image.resize(img, size=(size, int(size/2)), method=tf.image.ResizeMethod.LANCZOS5)
             down = down * mask[:,:,np.newaxis]
-            np.savez_compressed(os.path.join(folder, type + '_' + str(size), frame), uv_posed_body_no_orient = down)
+            np.savez_compressed(os.path.join(folder, type + '_2_' + str(size), frame), uv_posed_body_no_orient = down)
 
 
 def downscale_uv_maps_curv(folder, type, sizes):
@@ -169,16 +170,26 @@ def downscale_uv_maps_mask(folder, type, size):
 
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
-    parser.add_argument("-f", "--folder", help = "end of range", default='/home/workspace/local-data/valid')
-    parser.add_argument("-s", "--start", help = "start of range", default=0)
-    parser.add_argument("-e", "--end", help = "end of range", default=1000)
+    parser.add_argument("-f", "--folder", help = "end of range", default='/home/workspace/local-data/train')
+    parser.add_argument("-s", "--start", help = "start of range", default=280000)
+    parser.add_argument("-e", "--end", help = "end of range", default=10000000)
     parser.add_argument("-n", "--name", help = "end of range", default='lhunor')
     args = parser.parse_args()
 
-
     sizes = [32, 64, 128, 256]
     folder = args.folder
 
+    is_skirt = True
+    uv_masks_body = dict()
+    uv_mask_body = np.load('custom_utils/mask_256x512' + ('_skirt' if is_skirt else '') + '.npy')
+    uv_mask_body = cv2.dilate(uv_mask_body.astype(np.float32), cv2.getStructuringElement(cv2.MORPH_RECT, (2 * 2 + 1, 2 * 2 + 1), (2, 2)), iterations=2)
+    uv_masks_body[512] = uv_mask_body
+    for res in [32, 64, 128, 256]:
+        down = tf.image.resize(uv_mask_body[:,:,tf.newaxis].astype(np.int32), size=(res, int(res/2)), method=tf.image.ResizeMethod.NEAREST_NEIGHBOR)
+        down = np.squeeze(down.numpy().astype(bool))
+        uv_masks_body[res] = down
+        
+
     uv_mask_store = { size: UVMaskStore(folder, size=size) for size in sizes }
     uv_mask_store[512] = UVMaskStore(folder, size=512)
 
@@ -187,9 +198,10 @@ if __name__ == '__main__':
     # downscale_uv_maps_mask(folder=folder, type='uv_mask', size=128)
     # downscale_uv_maps_mask(folder=folder, type='uv_mask', size=256)
     # downscale_uv_maps_static(folder=folder, type='uv_static', sizes=sizes)
+
     # downscale_uv_maps_unposed(folder=folder, type='uv_unposed_no_shape', sizes=sizes)
-    downscale_uv_maps_curv(folder=folder, type='uv_curvature', sizes=sizes)
-    # downscale_uv_maps_posed_body(folder=folder, type='uv_posed_body_no_orient', sizes=sizes)
+    # downscale_uv_maps_curv(folder=folder, type='uv_curvature', sizes=sizes)
+    downscale_uv_maps_posed_body(folder=folder, type='uv_posed_body_no_orient', sizes=sizes)
 
 
     print()
\ No newline at end of file