Update app.py

app.py

@@ -18,8 +18,7 @@ pipe = StableDiffusionInpaintPipeline.from_pretrained(
 pipe.to('cpu')
 
 def inpaint_image(image, mask, prompt, negative_prompt):
-    # Convert PIL images to numpy arrays if needed
-    # Process your images as required by your inpainting model
+    print(image_file, mask_file, prompt, negative_prompt)
     n_image = pipe(prompt, image=image, mask_image=mask, guidance_scale=5,height=int(8*round(image.height/8)), width=int(8*round(image.width/8)), num_inference_steps=70,negative_prompt=negative_prompt).images[0]  
     return n_image