model.py

import gradio as gr
from PIL import Image
from model import predict

def classify_image(img: Image.Image):
    label, confidence, probs = predict(img)

    return (
        label,
        round(confidence, 3),
        {k: round(v, 3) for k, v in probs.items()}
    )

demo = gr.Interface(
    fn=classify_image,
    inputs=gr.Image(type="pil", label="Upload an image"),
    outputs=[
        gr.Label(label="Predicted Class"),
        gr.Number(label="Confidence"),
        gr.JSON(label="All Probabilities")
    ],
    title="Animal Image Classifier",
    description="Upload an image and the model will predict the animal."
)

if __name__ == "__main__":
    demo.launch()