doing color transfer for image harmonization

src/background_processor.py

@@ -194,6 +194,9 @@ class BackgroundProcessor:
         #height = foreground_img_pil.height
         #background_image_pil = Image.open(background_img_path)
         #background_image_pil = background_image_pil.resize((width, height)) 
+        
+        # Do color transfer of background to foreground to adjust lighting condition
+        foreground_img_pil = cls.color_transfer(foreground_img_pil, background_image_pil)
 
         foreground_binary = ImageFormatConvertor.pil_image_to_binary_data(foreground_img_pil)
         background_binary = ImageFormatConvertor.pil_image_to_binary_data(background_image_pil)
@@ -229,4 +232,26 @@ class BackgroundProcessor:
         logging.error(f"failed to use remove bg. Status: {remove_bg_request.status_code}. Resp: {remove_bg_request.content}")
         return None
     
-                    
+    @classmethod
+    def color_transfer(cls, source_pil: Image, target_pil: Image) -> Image:
+        source = ImageFormatConvertor.pil_to_cv2(source_pil)
+        target = ImageFormatConvertor.pil_to_cv2(target_pil)
+        source = cv2.cvtColor(source, cv2.COLOR_BGR2LAB)
+        target = cv2.cvtColor(target, cv2.COLOR_BGR2LAB)
+
+        # Compute the mean and standard deviation of the source and target images
+        source_mean, source_std = cv2.meanStdDev(source)
+        target_mean, target_std = cv2.meanStdDev(target)
+
+        #Reshape the mean and std to (1, 1, 3) so they can be broadcast correctly
+        source_mean = source_mean.reshape((1, 1, 3))
+        source_std = source_std.reshape((1, 1, 3))
+        target_mean = target_mean.reshape((1, 1, 3))
+        target_std = target_std.reshape((1, 1, 3))
+        # Subtract the mean from the source image
+        result = (source - source_mean) * (target_std / source_std) + target_mean
+        result = np.clip(result, 0, 255).astype(np.uint8)
+
+        res = cv2.cvtColor(result, cv2.COLOR_LAB2BGR) 
+        res_pil = ImageFormatConvertor.cv2_to_pil(res)
+        return res_pil