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app.py

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+# app.py
+import gradio as gr
+from fastai.learner import load_learner
+from fastai.vision.all import PILImage
+from PIL import Image
+
+# Load the model
+model = load_learner('model.pkl')
+
+def classify_image(image):
+    # Convert to FastAI PILImage
+    img = PILImage.create(image)
+    
+    # Get prediction
+    pred, pred_idx, probs = model.predict(img)
+    
+    # Return prediction and confidence
+    return {
+        "cat": float(probs[pred_idx]) if str(pred) == "cat" else 1 - float(probs[pred_idx])
+    }
+
+# Create Gradio interface
+iface = gr.Interface(
+    fn=classify_image,
+    inputs=gr.Image(),
+    outputs=gr.Label(num_top_classes=2),
+    title="Cat Classifier",
+    description="Upload an image to check if it contains a cat!",
+    examples=["example1.jpg", "example2.jpg"]  # Optional: Add example images if you have them
+)
+
+iface.launch()