Update app.py

app.py

@@ -62,17 +62,19 @@ def predict(dict, prompt="", negative_prompt="", guidance_scale=7.5, steps=30, s
     
     mask_image.putdata(new_data)
     mask_image = mask_image.resize(init_image.size, resample=Image.LANCZOS)
+    mask_image = mask_image.filter(ImageFilter.GaussianBlur(5))
     #mask_image = pipe.mask_processor.blur(mask_image, blur_factor=15)
-    output = pipe(
-        prompt = prompt,
-        negative_prompt=negative_prompt,
-        image=init_image,
-        mask_image=mask_image,
-        guidance_scale=guidance_scale,
-        num_inference_steps=int(steps),
-        strength=strength,
-        clip_skip=1
-    )
+    with torch.cuda.amp.autocast():
+        output = pipe(
+            prompt=prompt,
+            negative_prompt=negative_prompt,
+            image=init_image,
+            mask_image=mask_image,
+            guidance_scale=guidance_scale,
+            num_inference_steps=int(steps),
+            strength=strength,
+            clip_skip=1
+        )
     inpainted_image = output.images[0]
     inpainted_image = inpainted_image.resize(init_image.size, resample=Image.LANCZOS)
     # Combine the original and inpainted images using the mask