controlnet scale

app.py

@@ -81,6 +81,7 @@ def inpaint(
     strength,
     num_inference_steps,
     guidance_scale,
+    controlnet_conditioning_scale
 ):
     generator = torch.Generator(device=device).manual_seed(random.randint(0, MAX_SEED))
 
@@ -101,7 +102,7 @@ def inpaint(
         num_inference_steps=num_inference_steps,
         guidance_scale=guidance_scale,
         generator=generator,
-        controlnet_conditioning_scale=0.1
+        controlnet_conditioning_scale=controlnet_conditioning_scale
     ).images[0]
 
     return image_res, canny_image, resized_image, resized_mask
@@ -115,6 +116,7 @@ iface = gr.Interface(
         gr.Slider(0, 1, value=0.85, label="Strength"),
         gr.Slider(1, 50, value=30, step=1, label="Number of Inference Steps"),
         gr.Slider(1, 20, value=7.0, label="Guidance Scale"),
+        gr.Slider(0, 1, value=0.7, label="Controlnet conditioning")
         # gr.Number(label="Seed", precision=0),
     ],
     outputs=[