Update app.py

app.py

@@ -5,28 +5,33 @@ from diffusers import StableDiffusionInpaintPipeline
 import torch
 from diffusers.utils import load_image
 from diffusers.pipelines.stable_diffusion import safety_checker
-def sc(self, clip_input, images) :
-    return images, [False for i in images]
+# Bypass the safety checker
+def sc(self, clip_input, images):
+    return images, [False for _ in images]
 safety_checker.StableDiffusionSafetyChecker.forward = sc
 
-
+# Initialize the inpainting pipeline
 pipe = StableDiffusionInpaintPipeline.from_pretrained(
     "runwayml/stable-diffusion-inpainting",
-    revision="fp16",
+    variant="fp16",
     torch_dtype=torch.float16,
 )
 pipe.to('cpu')
 
+# Inpainting function
 def inpaint_image(image, mask, prompt, negative_prompt):
-    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]  
+    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
 
+# Processing uploaded files
 def process_files(image_file, mask_file, prompt, negative_prompt):
     image = Image.open(image_file)
     mask = Image.open(mask_file)
     return inpaint_image(image, mask, prompt, negative_prompt)
 
+# Gradio UI
 with gr.Blocks() as demo:
     gr.Markdown("## Inpainting App")
 
@@ -49,4 +54,4 @@ with gr.Blocks() as demo:
     )
 
 # Launch the interface
-demo.launch(show_error=True)
+demo.launch(show_error=True)