diff --git a/facefusion/vision.py b/facefusion/vision.py
index 2b7c9f62..26021e32 100644
--- a/facefusion/vision.py
+++ b/facefusion/vision.py
@@ -210,6 +210,24 @@ def normalize_frame_color(vision_frame : VisionFrame) -> VisionFrame:
 	return cv2.cvtColor(vision_frame, cv2.COLOR_BGR2RGB)
 
 
+def match_frame_color(source_vision_frame : VisionFrame, target_vision_frame : VisionFrame) -> VisionFrame:
+	color_difference_sizes = numpy.linspace(16, target_vision_frame.shape[0], 3, endpoint = False)
+
+	for color_difference_size in color_difference_sizes:
+		source_vision_frame = equalize_frame_color(source_vision_frame, target_vision_frame, normalize_resolution((color_difference_size, color_difference_size)))
+	target_vision_frame = equalize_frame_color(source_vision_frame, target_vision_frame, target_vision_frame.shape[:2][::-1])
+	return target_vision_frame
+
+
+def equalize_frame_color(source_vision_frame : VisionFrame, target_vision_frame : VisionFrame, size : Size) -> VisionFrame:
+	source_frame_resize = cv2.resize(source_vision_frame, size, interpolation = cv2.INTER_AREA).astype(numpy.float32)
+	target_frame_resize = cv2.resize(target_vision_frame, size, interpolation = cv2.INTER_AREA).astype(numpy.float32)
+	color_difference_vision_frame = numpy.subtract(source_frame_resize, target_frame_resize)
+	color_difference_vision_frame = cv2.resize(color_difference_vision_frame, target_vision_frame.shape[:2][::-1], interpolation = cv2.INTER_CUBIC)
+	target_vision_frame = numpy.add(target_vision_frame, color_difference_vision_frame).clip(0, 255).astype(numpy.uint8)
+	return target_vision_frame
+
+
 def create_tile_frames(vision_frame : VisionFrame, size : Size) -> Tuple[List[VisionFrame], int, int]:
 	vision_frame = numpy.pad(vision_frame, ((size[1], size[1]), (size[1], size[1]), (0, 0)))
 	tile_width = size[0] - 2 * size[2]
@@ -247,21 +265,3 @@ def merge_tile_frames(tile_vision_frames : List[VisionFrame], temp_width : int,
 		merge_vision_frame[top:bottom, left:right, :] = tile_vision_frame
 	merge_vision_frame = merge_vision_frame[size[1] : size[1] + temp_height, size[1]: size[1] + temp_width, :]
 	return merge_vision_frame
-
-
-def match_frame_color(source_vision_frame : VisionFrame, target_vision_frame : VisionFrame) -> VisionFrame:
-	color_difference_sizes = numpy.linspace(16, target_vision_frame.shape[0], 3, endpoint = False)
-
-	for color_difference_size in color_difference_sizes:
-		source_vision_frame = equalize_frame_color(source_vision_frame, target_vision_frame, normalize_resolution((color_difference_size, color_difference_size)))
-	target_vision_frame = equalize_frame_color(source_vision_frame, target_vision_frame, target_vision_frame.shape[:2][::-1])
-	return target_vision_frame
-
-
-def equalize_frame_color(source_vision_frame : VisionFrame, target_vision_frame : VisionFrame, size : Size) -> VisionFrame:
-	source_frame_resize = cv2.resize(source_vision_frame, size, interpolation = cv2.INTER_AREA).astype(numpy.float32)
-	target_frame_resize = cv2.resize(target_vision_frame, size, interpolation = cv2.INTER_AREA).astype(numpy.float32)
-	color_difference_vision_frame = numpy.subtract(source_frame_resize, target_frame_resize)
-	color_difference_vision_frame = cv2.resize(color_difference_vision_frame, target_vision_frame.shape[:2][::-1], interpolation = cv2.INTER_CUBIC)
-	target_vision_frame = numpy.add(target_vision_frame, color_difference_vision_frame).clip(0, 255).astype(numpy.uint8)
-	return target_vision_frame
diff --git a/tests/test_vision.py b/tests/test_vision.py
index 418ce7af..9f5e770c 100644
--- a/tests/test_vision.py
+++ b/tests/test_vision.py
@@ -123,6 +123,5 @@ def test_match_frame_color() -> None:
 	output_vision_frame = match_frame_color(source_vision_frame, target_vision_frame)
 	histogram_source = cv2.calcHist([ cv2.cvtColor(source_vision_frame, cv2.COLOR_BGR2HSV) ], [ 0, 1 ], None, [ 50, 60 ], [ 0, 180, 0, 256 ])
 	histogram_output = cv2.calcHist([ cv2.cvtColor(output_vision_frame, cv2.COLOR_BGR2HSV) ], [ 0, 1 ], None, [ 50, 60 ], [ 0, 180, 0, 256 ])
-	cv2.normalize(histogram_source, histogram_source, 0, 1, cv2.NORM_MINMAX)
-	cv2.normalize(histogram_output, histogram_output, 0, 1, cv2.NORM_MINMAX)
+
 	assert cv2.compareHist(histogram_source, histogram_output, cv2.HISTCMP_CORREL) > 0.5