Update app.py

app.py

@@ -20,7 +20,7 @@ def mask_to_rgb(mask):
     return bg_transparent
 
 def get_processed_inputs(image, points):
-    input_points = [[list(map(int, point.split(',')))] for point in points.split('|') if point]
+    input_points = [points]
     inputs = processor(image, input_points, return_tensors="pt").to(device)
     with torch.no_grad():
         outputs = model(**inputs)
@@ -49,20 +49,27 @@ def inpaint(raw_image, input_mask, prompt, negative_prompt=None, seed=74294536,
     ).images[0]
     return image
 
-# Updated Gradio interface
-def gradio_interface(image, points):
+def gradio_interface(image, coordinates, positive_prompt, negative_prompt):
     raw_image = Image.fromarray(image).convert("RGB").resize((512, 512))
+    points = [int(coord) for coord in coordinates]
     mask = get_processed_inputs(raw_image, points)
-    processed_image = inpaint(raw_image, mask, "a car driving on Mars. Studio lights, 1970s", "artifacts, low quality, distortion")
+    processed_image = inpaint(raw_image, mask, positive_prompt, negative_prompt)
     return processed_image, mask_to_rgb(mask)
 
 iface = gr.Interface(
     fn=gradio_interface,
     inputs=[
-        gr.Image(image_mode='RGB'),  # Removed image_shape parameter
-        "text"  # To allow users to enter points manually or through another input method
+        gr.Image(type="numpy", tool="select"),
+        gr.Textbox(label="Coordinates (automatically filled)"),
+        gr.Textbox(label="Positive Prompt", placeholder="Enter positive prompt here"),
+        gr.Textbox(label="Negative Prompt", placeholder="Enter negative prompt here")
     ],
-    outputs=["image", "image"]
+    outputs=[
+        gr.Image(label="Inpainted Image"),
+        gr.Image(label="Segmentation Mask")
+    ],
+    title="Interactive Image Inpainting",
+    description="Select an area on the image, provide prompts, and see the inpainted result."
 )
 
 iface.launch(share=True)