Update app.py

app.py

@@ -17,6 +17,15 @@ from diffusers.utils import load_image
 controlnet_canny = SD3ControlNetModel.from_pretrained("InstantX/SD3-Controlnet-Canny")
 controlnet_tile = SD3ControlNetModel.from_pretrained("InstantX/SD3-Controlnet-Tile")
 
+pipe_canny = StableDiffusion3ControlNetPipeline.from_pretrained(
+            "stabilityai/stable-diffusion-3-medium-diffusers",
+            controlnet=controlnet_canny
+        )
+
+pipe_tile = StableDiffusion3ControlNetPipeline.from_pretrained(
+            "stabilityai/stable-diffusion-3-medium-diffusers",
+            controlnet=controlnet_tile
+        )
 
 def resize_image(input_path, output_path, target_height):
     # Open the input image
@@ -43,11 +52,7 @@ def infer_canny(image_in, prompt, control_type, inference_steps, guidance_scale,
     n_prompt = 'NSFW, nude, naked, porn, ugly'
 
     if control_type == "canny":
-        pipe = StableDiffusion3ControlNetPipeline.from_pretrained(
-            "stabilityai/stable-diffusion-3-medium-diffusers",
-            controlnet=controlnet_canny
-        )
-
+        pipe = pipe_canny
         # Canny preprocessing
         image_to_canny = load_image(image_in)
         image_to_canny = np.array(image_to_canny)
@@ -59,15 +64,10 @@ def infer_canny(image_in, prompt, control_type, inference_steps, guidance_scale,
         control_image = image_to_canny
     
     elif control_type == "tile":
-        pipe = StableDiffusion3ControlNetPipeline.from_pretrained(
-            "stabilityai/stable-diffusion-3-medium-diffusers",
-            controlnet=controlnet_tile
-        )
-
+        pipe = pipe_tile
         control_image = load_image(image_in)
 
-   
-    pipe.to("cuda", torch.float16)
+   pipe.to("cuda", torch.float16)
     
     # infer
     image = pipe(