diff --git a/README.md b/README.md
index 0c6138f6..8dc58b64 100644
--- a/README.md
+++ b/README.md
@@ -428,15 +428,11 @@ class ControlNetExampleForge(scripts.Script):
 
         # Below are two methods to preprocess images.
         # Method 1: do it in your own way
-        canny_image_1 = cv2.cvtColor(cv2.Canny(input_image, 100, 200), cv2.COLOR_GRAY2RGB)
+        canny_image = cv2.cvtColor(cv2.Canny(input_image, 100, 200), cv2.COLOR_GRAY2RGB)
 
         # Method 2: use built-in preprocessor
-        from modules_forge.shared import shared_preprocessors
-        canny_image_2 = shared_preprocessors['canny'](input_image, 100, 200)
-
-        # The two methods will give your same result
-        assert np.allclose(canny_image_1, canny_image_2)
-        canny_image = canny_image_1
+        # from modules_forge.shared import shared_preprocessors
+        # canny_image = shared_preprocessors['canny'](input_image, 100, 200)
 
         # Output preprocessor result. Now called every sampling. Cache in your own way.
         p.extra_result_images.append(canny_image)
diff --git a/extensions-builtin/sd_forge_controlnet_example/scripts/sd_forge_controlnet_example.py b/extensions-builtin/sd_forge_controlnet_example/scripts/sd_forge_controlnet_example.py
index 6c424619..64696724 100644
--- a/extensions-builtin/sd_forge_controlnet_example/scripts/sd_forge_controlnet_example.py
+++ b/extensions-builtin/sd_forge_controlnet_example/scripts/sd_forge_controlnet_example.py
@@ -80,15 +80,11 @@ class ControlNetExampleForge(scripts.Script):
 
         # Below are two methods to preprocess images.
         # Method 1: do it in your own way
-        canny_image_1 = cv2.cvtColor(cv2.Canny(input_image, 100, 200), cv2.COLOR_GRAY2RGB)
+        canny_image = cv2.cvtColor(cv2.Canny(input_image, 100, 200), cv2.COLOR_GRAY2RGB)
 
         # Method 2: use built-in preprocessor
-        from modules_forge.shared import shared_preprocessors
-        canny_image_2 = shared_preprocessors['canny'](input_image, 100, 200)
-
-        # The two methods will give your same result
-        assert np.allclose(canny_image_1, canny_image_2)
-        canny_image = canny_image_1
+        # from modules_forge.shared import shared_preprocessors
+        # canny_image = shared_preprocessors['canny'](input_image, 100, 200)
 
         # Output preprocessor result. Now called every sampling. Cache in your own way.
         p.extra_result_images.append(canny_image)