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

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

learn = load_learner('model.pkl')

categories = ('Dog', 'Cat')

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

with gr.Blocks() as demo:
    image = gr.Image(type="pil")
    label = gr.Label()
    examples = gr.Examples(['dog.jpg', 'cat.jpg', 'dunno.jpg'], image)
    
    classify_btn = gr.Button("Classify")
    classify_btn.click(fn=classify_image, inputs=image, outputs=label)

# Launch the interface
demo.launch(inline=False)