diff --git a/scripts/postprocessing_pixelization.py b/scripts/postprocessing_pixelization.py
index b4b98ac..4c99887 100644
--- a/scripts/postprocessing_pixelization.py
+++ b/scripts/postprocessing_pixelization.py
@@ -13,6 +13,8 @@
 from pixelization.models.networks import define_G
 import pixelization.models.c2pGen
 
+import colorsys
+
 pixelize_code = [
     233356.8125, -27387.5918, -32866.8008, 126575.0312, -181590.0156,
     -31543.1289, 50374.1289, 99631.4062, -188897.3750, 138322.7031,
@@ -153,17 +155,46 @@ def process(img):
     return trans(img)[None, :, :, :]
 
 
-def to_image(tensor, pixel_size, upscale_after):
+def to_image(tensor, pixel_size, upscale_after, original_img, copy_hue, copy_sat):
     img = tensor.data[0].cpu().float().numpy()
     img = (np.transpose(img, (1, 2, 0)) + 1) / 2.0 * 255.0
     img = img.astype(np.uint8)
     img = Image.fromarray(img)
-    img = img.resize((img.size[0]//4, img.size[1]//4), resample=Image.Resampling.NEAREST)
+    width = img.size[0]//4
+    height = img.size[1]//4
+    img = img.resize((width, height), resample=Image.Resampling.NEAREST)
+    
+    if copy_hue or copy_sat:
+        original_img = original_img.resize((width, height), resample=Image.Resampling.NEAREST)
+        img = color_image(img, original_img, copy_hue, copy_sat);
+    
     if upscale_after:
         img = img.resize((img.size[0]*pixel_size, img.size[1]*pixel_size), resample=Image.Resampling.NEAREST)
 
     return img
+    
+def color_image(img, original_img, copy_hue, copy_sat):
+    img = img.convert("RGB")
+    original_img = original_img.convert("RGB")
+
+    colored_img = Image.new("RGB", img.size)
+    
+    print(img.width, img.height)
+
+    for x in range(img.width):
+        for y in range(img.height):
+            pixel = original_img.getpixel((x, y))
+            r, g, b = pixel
+            original_h, original_s, original_v = colorsys.rgb_to_hsv(r / 255, g / 255, b / 255)
+
+            pixel = img.getpixel((x, y))
+            r, g, b = pixel
+            h, s, v = colorsys.rgb_to_hsv(r / 255, g / 255, b / 255)
 
+            r, g, b = colorsys.hsv_to_rgb(original_h if copy_hue else h, original_s if copy_sat else s, v)
+            colored_img.putpixel((x, y), (int(r * 255), int(g * 255), int(b * 255)))
+
+    return colored_img
 
 class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostprocessing):
     name = "Pixelization"
@@ -176,17 +207,21 @@ def ui(self):
                 with FormRow():
                     enable = gr.Checkbox(False, label="Enable pixelization")
                     upscale_after = gr.Checkbox(False, label="Keep resolution")
-
+                with FormRow():
+                    copy_hue = gr.Checkbox(False, label="Restore hue")
+                    copy_sat = gr.Checkbox(False, label="Restore saturation")
             with gr.Column():
                 pixel_size = gr.Slider(minimum=1, maximum=16, step=1, label="Pixel size", value=4, elem_id="pixelization_pixel_size")
-
+                     
         return {
             "enable": enable,
             "upscale_after": upscale_after,
             "pixel_size": pixel_size,
+            "copy_hue": copy_hue,
+            "copy_sat": copy_sat,
         }
 
-    def process(self, pp: scripts_postprocessing.PostprocessedImage, enable, upscale_after, pixel_size):
+    def process(self, pp: scripts_postprocessing.PostprocessedImage, enable, upscale_after, pixel_size, copy_hue, copy_sat):
         if not enable:
             return
 
@@ -199,6 +234,7 @@ def process(self, pp: scripts_postprocessing.PostprocessedImage, enable, upscale
         self.model.to(devices.device)
 
         pp.image = pp.image.resize((pp.image.width * 4 // pixel_size, pp.image.height * 4 // pixel_size))
+        original_img = pp.image.copy()
 
         with torch.no_grad():
             in_t = process(pp.image).to(devices.device)
@@ -209,7 +245,7 @@ def process(self, pp: scripts_postprocessing.PostprocessedImage, enable, upscale
             images = self.model.G_A_net.module.RGBDec(feature, adain_params)
             out_t = self.model.alias_net(images)
 
-            pp.image = to_image(out_t, pixel_size=pixel_size, upscale_after=upscale_after)
+            pp.image = to_image(out_t, pixel_size=pixel_size, upscale_after=upscale_after, original_img=original_img, copy_hue=copy_hue, copy_sat=copy_sat)
 
         self.model.to(devices.cpu)