app.py

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

def is_cat(x): return x[0].isupper() 

learner = load_learner("model.pkl")
categories = ("Dog", "Cat")

def classify_image(img):
    if img is None:
        return {}
    img = PILImage.create(img)
    pred, pred_idx, probs = learner.predict(img)
    return dict(zip(categories, map(float, probs)))

demo = gr.Interface(
    fn=classify_image,
    inputs=gr.Image(type="pil"),
    outputs=gr.Label(),
    examples=["cat1.jpeg", "dog1.jpeg", "cat2.jpeg", "dog2.jpg"],
    cache_examples=False, 
)

demo.launch()