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

# Define the labeling function used during training
# This must match the function used when the model was trained
def is_cat(x):
    return x[0].isupper()

learn = load_learner('cat_or_dog_model.pkl')
categories = ('Dog', 'Cat')

def classify_image(img):
    pred, idx, probs = learn.predict(img)
    return dict(zip(categories, map(float, probs)))

# Modern Gradio API
intf = gr.Interface(
    fn=classify_image,
    inputs=gr.Image(),
    outputs=gr.Label(num_top_classes=2),
    title="Cat or Dog Classifier",
    description="Upload an image to classify whether it's a cat or dog"
)

intf.launch()