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

learn = load_learner('model.pkl')

def classify_image(img):
    pred, idx, probs = learn.predict(img)
    d = dict(zip(learn.dls.vocab, map(float,probs)))
    ds = sorted(d.items(), key=lambda item: item[1], reverse=True)
    return dict(ds[0:5])

#image = gr.Image(shape=(244, 244))
image = gr.Image()
label = gr.Label()
examples = ['dog1.jpg', 'dog2.jpg', 'dog3.jpg']

#demo = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
demo = gr.Interface(fn=classify_image, inputs=image, outputs=label, analytics_enabled=False)
demo.launch(inline=False)