diff --git a/downscale.py b/downscale.py
index 450753d..411615f 100644
--- a/downscale.py
+++ b/downscale.py
@@ -1,3 +1,4 @@
+import argparse
 import os
 import tqdm
 import cv2
@@ -7,7 +8,7 @@ import numpy as np
 import plotly.graph_objects as go
 import plotly.express as ex
 
-os.environ["CUDA_VISIBLE_DEVICES"] = "4"
+os.environ["CUDA_VISIBLE_DEVICES"] = "1"
 
 gpus = tf.config.experimental.list_physical_devices('GPU')
 if gpus:
@@ -67,75 +68,84 @@ class UVMaskStore():
         return self.store[id]
 
 
-def downscale_uv_maps_posed_body(folder, type, size: int):
-    os.makedirs(os.path.join(folder, type + '_' + str(size)), exist_ok=True)
+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)
 
-    frames = os.listdir(os.path.join(folder, type))
+    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_full[id]
+        mask_full = uv_mask_store[512][id]
         img = fill(img, mask_full)
-        mask = uv_mask_store_low[id]
-        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)
+        for size in sizes:
+            mask = uv_mask_store[size][id]
+            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)
 
 
-def downscale_uv_maps_curv(folder, type, size):
-    os.makedirs(os.path.join(folder, type + '_' + str(size)), exist_ok=True)
+def downscale_uv_maps_curv(folder, type, sizes):
+    for size in sizes:
+        os.makedirs(os.path.join(folder, type + '_' + str(size)), exist_ok=True)
 
-    frames = os.listdir(os.path.join(folder, type))
+    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['curvature_uv']
-        mask_full = uv_mask_store_full[id]
+        mask_full = uv_mask_store[512][id]
         img = fill_label(img, mask_full)
-        mask = uv_mask_store_low[id]
-        down = tf.image.resize(img[:,:,tf.newaxis], size=(size, int(size/2)), method=tf.image.ResizeMethod.NEAREST_NEIGHBOR)
-        down = np.squeeze(down) * mask[:,:]
-        np.savez_compressed(os.path.join(folder, type + '_' + str(size), frame), uv_curvature = down)
+        for size in sizes:
+            mask = uv_mask_store[size][id]
+            down = tf.image.resize(img[:,:,tf.newaxis], size=(size, int(size/2)), method=tf.image.ResizeMethod.NEAREST_NEIGHBOR)
+            down = np.squeeze(down) * mask[:,:]
+            np.savez_compressed(os.path.join(folder, type + '_' + str(size), frame), uv_curvature = down)
 
 
 
-def downscale_uv_maps_unposed(folder, type, size):
-    os.makedirs(os.path.join(folder, type + '_' + str(size)), exist_ok=True)
+def downscale_uv_maps_unposed(folder, type, sizes):
+    for size in sizes:
+        os.makedirs(os.path.join(folder, type + '_' + str(size)), exist_ok=True)
 
-    frames = os.listdir(os.path.join(folder, type))
+    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_unposed_no_shape']
-        mask_full = uv_mask_store_full[id]
+        mask_full = uv_mask_store[512][id]
         img = fill(img, mask_full)
-        mask = uv_mask_store_low[id]
-        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_unposed_no_shape = down)
+        for size in sizes:
+            mask = uv_mask_store[size][id]
+            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_unposed_no_shape = down)
 
 
-def downscale_uv_maps_static(folder, type, size):
-    os.makedirs(os.path.join(folder, type + '_' + str(size)), exist_ok=True)
+def downscale_uv_maps_static(folder, type, sizes):
+    for size in sizes:
+        os.makedirs(os.path.join(folder, type + '_' + str(size)), exist_ok=True)
 
-    frames = os.listdir(os.path.join(folder, type))
+    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_static']
-        mask_full = uv_mask_store_full[id]
+        mask_full = uv_mask_store[512][id]
         img = fill(img, mask_full)
-        down = tf.image.resize(img, size=(size, int(size/2)), method=tf.image.ResizeMethod.LANCZOS5)
-        mask = uv_mask_store_low[id]
-        down = down * mask[:,:,np.newaxis]
-        np.savez_compressed(os.path.join(folder, type + '_' + str(size), frame), uv_static = down)
+
+        for size in sizes:
+            down = tf.image.resize(img, size=(size, int(size/2)), method=tf.image.ResizeMethod.LANCZOS5)
+            mask = uv_mask_store[size][id]
+            down = down * mask[:,:,np.newaxis]
+            np.savez_compressed(os.path.join(folder, type + '_' + str(size), frame), uv_static = down)
 
 
 def downscale_uv_maps_mask(folder, type, size):
     os.makedirs(os.path.join(folder, type + '_' + str(size)), exist_ok=True)
 
-    frames = os.listdir(os.path.join(folder, type))
+    frames = os.listdir(os.path.join(folder, type))[int(args.start):int(args.end)]
 
     for frame in tqdm.tqdm(frames):
         id, _ = frame.split('.')
@@ -147,20 +157,25 @@ def downscale_uv_maps_mask(folder, type, size):
 
 
 if __name__ == '__main__':
-    size = 32
-    folder = '/home/workspace/local-data/train'
+    parser = argparse.ArgumentParser()
+    parser.add_argument("-f", "--folder", help = "end of range", default='/home/workspace/data/dataset/train_skirt')
+    parser.add_argument("-s", "--start", help = "start of range", default=0)
+    parser.add_argument("-e", "--end", help = "end of range", default=1)
+    parser.add_argument("-n", "--name", help = "end of range", default='lhunor')
+    args = parser.parse_args()
 
-    uv_mask_store_full = UVMaskStore(folder, size=512)
-    uv_mask_store_low = UVMaskStore(folder, size=size)
+
+    sizes = [32, 64, 128, 256]
+    folder = args.folder
+
+    uv_mask_store = { size: UVMaskStore(folder, size=size) for size in sizes }
+    uv_mask_store[512] = UVMaskStore(folder, size=512)
 
     # downscale_uv_maps_mask(folder=folder, type='uv_mask', size=size)
-    # downscale_uv_maps_unposed(folder=folder, type='uv_unposed_no_shape', size=size)
-    # downscale_uv_maps_curv(folder=folder, type='uv_curvature', size=size)
-    # downscale_uv_maps_posed_body(folder=folder, type='uv_posed_body_no_orient', size=size)
+    # 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_static(folder=folder, type='uv_static', size=32)
-    downscale_uv_maps_static(folder=folder, type='uv_static', size=64)
-    downscale_uv_maps_static(folder=folder, type='uv_static', size=128)
-    downscale_uv_maps_static(folder=folder, type='uv_static', size=256)
 
     print()
\ No newline at end of file