Create app.py

app.py

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+import gradio as gr
+from transformers import AutoModel, AutoProcessor
+from PIL import Image
+import torch
+
+# Load model and processor
+model = AutoModel.from_pretrained("zxhezexin/openlrm-mix-large-1.1")
+processor = AutoProcessor.from_pretrained("zxhezexin/openlrm-mix-large-1.1")
+
+# Define function to generate 3D output from 2D image
+def image_to_3d(image):
+    inputs = processor(images=image, return_tensors="pt")
+    with torch.no_grad():
+        outputs = model(**inputs)
+    # This is placeholder logic; you'd need to process the outputs appropriately
+    return "3D Output Generated"  # Replace with actual visualization code
+
+# Gradio interface
+interface = gr.Interface(
+    fn=image_to_3d,
+    inputs=gr.Image(type="pil"),
+    outputs="text",  # Replace with "3D" if you can visualize the output
+    title="OpenLRM Mix-Large 1.1 - Image to 3D"
+)
+
+interface.launch()