Update app.py

app.py

@@ -80,15 +80,18 @@ def generate(
                 pipe = AutoPipelineForImage2Image.from_pretrained(model, vae=vae, torch_dtype=torch.float16)
                 
         if use_inpainting:
-            pipe = AutoPipelineForInpainting.from_pretrained(model, torch_dtype=torch.float16)
-            
-            response = requests.get(url)
-            init_image = Image.open(BytesIO(response.content)).convert("RGB")
-            init_image = init_image.resize((width, height))
+            controlnet = ControlNetModel.from_pretrained("lllyasviel/sd-controlnet-canny", torch_dtype=torch.float16)
+            pipe = StableDiffusionControlNetImg2ImgPipeline.from_pretrained(model, controlnet=controlnet, torch_dtype=torch.float16)
+
+            image = load_image(img_url)
+            np_image = np.array(image)
+
+            # get canny image
+            np_image = cv2.Canny(np_image, 100, 200)
+            np_image = np_image[:, :, None]
+            np_image = np.concatenate([np_image, np_image, np_image], axis=2)
+            canny_image = Image.fromarray(np_image)
 
-            image_init = load_image(img_url)
-            mask_image = load_image(mask_url)
-            
         if use_lora:
             pipe.load_lora_weights(lora)
             pipe.fuse_lora(lora_scale)
@@ -114,9 +117,8 @@ def generate(
     if use_inpainting:
         image = pipe(
             prompt=prompt,
-            image=image_init,
-            mask_image=mask_image,
-            strength=strength_img2img,
+            image=image,
+            control_image=canny_image,
             negative_prompt=negative_prompt,
             prompt_2=prompt_2,
             width=width,