diff --git a/apps/stable_diffusion/src/utils/stencils/stencil_utils.py b/apps/stable_diffusion/src/utils/stencils/stencil_utils.py
index 685d542405..41800f0cb7 100644
--- a/apps/stable_diffusion/src/utils/stencils/stencil_utils.py
+++ b/apps/stable_diffusion/src/utils/stencils/stencil_utils.py
@@ -1,6 +1,10 @@
 import numpy as np
 from PIL import Image
 import torch
+import os
+from pathlib import Path
+import torchvision
+import time
 from apps.stable_diffusion.src.utils.stencils import (
     CannyDetector,
     OpenposeDetector,
@@ -10,6 +14,33 @@
 stencil = {}
 
 
+def save_img(img):
+    from apps.stable_diffusion.src.utils import (
+        get_generated_imgs_path,
+        get_generated_imgs_todays_subdir,
+    )
+
+    subdir = Path(
+        get_generated_imgs_path(), get_generated_imgs_todays_subdir()
+    )
+    os.makedirs(subdir, exist_ok=True)
+    if isinstance(img, Image.Image):
+        img.save(
+            os.path.join(
+                subdir, "controlnet_" + str(int(time.time())) + ".png"
+            )
+        )
+    elif isinstance(img, np.ndarray):
+        img = Image.fromarray(img)
+        img.save(os.path.join(subdir, str(int(time.time())) + ".png"))
+    else:
+        converter = torchvision.transforms.ToPILImage()
+        for i in img:
+            converter(i).save(
+                os.path.join(subdir, str(int(time.time())) + ".png")
+            )
+
+
 def HWC3(x):
     assert x.dtype == np.uint8
     if x.ndim == 2:
@@ -161,6 +192,7 @@ def hint_canny(
         detected_map = stencil["canny"](
             input_image, low_threshold, high_threshold
         )
+        save_img(detected_map)
         detected_map = HWC3(detected_map)
         return detected_map
 
@@ -176,6 +208,7 @@ def hint_openpose(
             stencil["openpose"] = OpenposeDetector()
 
         detected_map, _ = stencil["openpose"](input_image)
+        save_img(detected_map)
         detected_map = HWC3(detected_map)
         return detected_map
 
@@ -187,6 +220,7 @@ def hint_scribble(image: Image.Image):
 
         detected_map = np.zeros_like(input_image, dtype=np.uint8)
         detected_map[np.min(input_image, axis=2) < 127] = 255
+        save_img(detected_map)
         return detected_map
 
 
@@ -199,5 +233,6 @@ def hint_zoedepth(image: Image.Image):
             stencil["depth"] = ZoeDetector()
 
         detected_map = stencil["depth"](input_image)
+        save_img(detected_map)
         detected_map = HWC3(detected_map)
         return detected_map