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

categories = 'Giant panda', 'Red panda'

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

learn = load_learner('model.pkl')

image = gr.Image(height=192, width=192)
label = gr.Label()

examples = ['giant_0.jpg', 'red_0.jpg', 'giant_1.jpg', 'red_1.jpg']
interface = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
interface.launch(inline=False, share=True)