from fastai.vision.all import *
import gradio as gr

# Load the model
learn = load_learner('model.pkl')

# Define prediction function
def classify_image(img):
    pred, idx, probs = learn.predict(img)
    return {learn.dls.vocab[i]: float(probs[i]) for i in range(len(probs))}

# Gradio Interface
interface = gr.Interface(
    fn=classify_image,
    inputs=gr.Image(type="pil"),
    outputs=gr.Label(num_top_classes=2),
    title="Cat vs Dog Classifier",
    description="Upload an image of a cat or a dog. The model will predict which one it is.",
    examples=[
        ["cat.jpg"],
        ["dog.jpg"]
    ]
)

# Launch app
if __name__ == "__main__":
    interface.launch()