MCP ready

demo_gradio.py

@@ -90,7 +90,34 @@ transform = Compose(
 model.eval()
 
 @spaces.GPU()
-def greet(input_image, material_exemplar, progress=gr.Progress(track_tqdm=True)):
+def infer(input_image, material_exemplar, progress=gr.Progress(track_tqdm=True)):
+    """
+    Perform zero-shot material transfer from a single input image and a material exemplar image.
+
+    This function uses a combination of a depth estimation model (DPT), foreground/background separation,
+    grayscale stylization, and IP-Adapter+ControlNet with Stable Diffusion XL to generate an output image
+    in which the material style from the exemplar image is applied to the input image's object.
+
+    Args:
+        input_image (PIL.Image): The original image containing the object to which the new material will be applied.
+        material_exemplar (PIL.Image): A reference image whose material (texture, reflectance, etc.) is to be transferred to the object in the input image.
+        progress (gradio.Progress, optional): For tracking the progress bar in Gradio UI. Default enables tqdm tracking.
+
+    Returns:
+        PIL.Image: The output image showing the object from `input_image` rendered with the material of `material_exemplar`.
+
+    Steps:
+    1. Compute a depth map from `input_image` using a DPT-based model.
+    2. Remove the background from the input image to isolate the object and convert it into a grayscale version.
+    3. Combine and align the input image, depth map, and mask for use with the IP-Adapter + ControlNet SDXL pipeline.
+    4. Use the `IPAdapterXL.generate()` function to synthesize a new image by guiding generation using:
+        - material_exemplar for style/material guidance
+        - input_image's structure/content in grayscale
+        - the estimated depth map for spatial layout
+        - the mask for region-specific conditioning (object-only)
+    5. Return the first image in the generated list as the final material transfer result.
+    """
+
     
     """
     Compute depth map from input_image
@@ -209,6 +236,6 @@ with gr.Blocks(css=css) as demo:
                 )
             with gr.Column():
                 output_image = gr.Image(label="transfer result")
-    submit_btn.click(fn=greet, inputs=[input_image, input_image2], outputs=[output_image])
+    submit_btn.click(fn=infer, inputs=[input_image, input_image2], outputs=[output_image])
 
-demo.queue().launch(show_error=True)
+demo.queue().launch(show_error=True, ssr_mode=False, mcp_server=True)