app.py

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

learn = load_learner('seiba-edisa-apple-bins.pkl')

categories = learn.dls.vocab
def predict(img):
    # img = PILImage.create(img)
    _,_,probs = learn.predict(img)
    return dict(zip(categories, map(float,probs)))

title = "Apple bins classifier"
examples = ['clean-01.JPG','clean-02.JPG','clean-03.JPG','clean-04.JPG','dirty-01.JPG','dirty-02.JPG','dirty-03.JPG','dirty-04.JPG']
interpretation='default'
enable_queue=True

gr.Interface(fn=predict,
             inputs=gr.inputs.Image(shape=(192, 192)),
             outputs=gr.outputs.Label(num_top_classes=2),
             title=title,
             examples=examples).launch(inline=False)