Update app.py

app.py

@@ -5,17 +5,17 @@ import torch
 import requests
 from io import BytesIO
 
-# Load model and processor
+# Load model and processor from Hugging Face
 try:
     model = AutoModel.from_pretrained("zxhezexin/openlrm-mix-large-1.1")
     processor = AutoProcessor.from_pretrained("zxhezexin/openlrm-mix-large-1.1")
 except Exception as e:
     print(f"Error loading model or processor: {e}")
 
-# Example image URL (change this to a suitable 2D image URL)
-example_image_url = "https://example.com/path-to-your-example-image.jpg"
+# Example image URL (replace this with a suitable example)
+example_image_url = "https://huggingface.co/datasets/nateraw/image-folder/resolve/main/example_1.png"
 
-# Load example image
+# Function to load example image from URL
 def load_example_image():
     try:
         response = requests.get(example_image_url)
@@ -35,23 +35,23 @@ def image_to_3d(image):
         with torch.no_grad():
             outputs = model(**inputs)
         
-        # Placeholder return, replace this with actual 3D visualization
-        return "3D model generated!"  
+        # Placeholder return, replace this with actual 3D visualization logic
+        return "3D model generated from input image!"  
     except Exception as e:
         return f"Error during inference: {str(e)}"
 
-# Gradio interface
+# Load the example image for the Gradio interface
 example_image = load_example_image()
 
+# Gradio interface setup
 interface = gr.Interface(
     fn=image_to_3d,
     inputs=gr.Image(type="pil", label="Upload an Image or use Example"),
-    outputs="text",  # Placeholder output (you can modify this for 3D)
+    outputs="text",  # Placeholder output (replace with 3D rendering if needed)
     title="OpenLRM Mix-Large 1.1 - Image to 3D",
     description="Upload an image to generate a 3D model using OpenLRM Mix-Large 1.1.",
-    examples=[[example_image]] if example_image else None  # Include the example image
+    examples=[[example_image]] if example_image else None  # Include the example image if loaded
 )
 
 # Launch the Gradio interface
 interface.launch()
-