update

app.py

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+import gradio as gr
+from transformers import pipeline
+from PIL import Image
+import torch
+
+# Load your model
+device = 0 if torch.cuda.is_available() else -1
+pipe = pipeline("image-classification", model="beingamit99/car_damage_detection", device=device)
+
+def predict_damage(image):
+    if image.mode != "RGB":
+        image = image.convert("RGB")
+    results = pipe(image)
+    return results
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=predict_damage,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.JSON(),
+    title="Car Damage Detection API",
+    description="Upload an image of a car to detect damages."
+)
+
+if __name__ == "__main__":
+    iface.launch()