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app.py

@@ -17,7 +17,7 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
 pipe.to(device)
 print(f"Model loaded on {device}")
 
-def process_image(image, mask, instruction, num_steps=50, guidance_scale=5.0):
+def process_image(image, instruction, num_steps=50, guidance_scale=5.0):
     """
     Process an image with RMBG-3.0
     """
@@ -28,20 +28,13 @@ def process_image(image, mask, instruction, num_steps=50, guidance_scale=5.0):
         return None, "Please provide an editing instruction"
 
     try:
-        # Prepare inputs
-        kwargs = {
-            "image": image,
-            "prompt": instruction,
-            "num_inference_steps": num_steps,
-            "guidance_scale": guidance_scale
-        }
-
-        # Add mask if provided
-        if mask is not None:
-            kwargs["mask"] = mask.convert("L")
-
         # Run the pipeline
-        result = pipe(**kwargs).images[0]
+        result = pipe(
+            image=image,
+            prompt=instruction,
+            num_inference_steps=num_steps,
+            guidance_scale=guidance_scale
+        ).images[0]
 
         return result, "✅ Image processed successfully!"
 
@@ -64,9 +57,9 @@ with gr.Blocks(title="RMBG-3.0 - Background Removal & Image Editing") as demo:
 
     ### How to use:
     1. Upload your image
-    2. (Optional) Upload a mask to edit specific regions
-    3. Describe what you want to change
-    4. Adjust settings and click Process!
+    2. Review or modify the editing instruction
+    3. Adjust settings if needed
+    4. Click Process!
     """)
 
     with gr.Row():
@@ -77,12 +70,6 @@ with gr.Blocks(title="RMBG-3.0 - Background Removal & Image Editing") as demo:
                 height=400
             )
 
-            mask_image = gr.Image(
-                label="Mask (Optional - for targeted edits)",
-                type="pil",
-                height=200
-            )
-
             instruction = gr.Textbox(
                 label="Editing Instruction",
                 value="{'edit_instruction':'Generate a detailed grayscale alpha matte. Map the opaque foreground to white and the background to black. Produce soft, anti-aliased grayscale gradients at the edges of the subject to represent fine details and transparency.'}",
@@ -138,7 +125,7 @@ with gr.Blocks(title="RMBG-3.0 - Background Removal & Image Editing") as demo:
     # Connect the button
     process_btn.click(
         fn=process_image,
-        inputs=[input_image, mask_image, instruction, num_steps, guidance_scale],
+        inputs=[input_image, instruction, num_steps, guidance_scale],
         outputs=[output_image, status_text]
     )