app.py

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

learn = load_learner('export.pkl')

labels = learn.dls.vocab
def predict(img):
    img = PILImage.create(img)
    pred,pred_idx,probs = learn.predict(img)
    return {labels[i]: float(probs[i]) for i in range(len(labels))}

title = "Avengers Classifier"
description = "A Avenger Classifier is  trained on the Avengers dataset with fastai. Created as a demo for Gradio and HuggingFace Spaces."
examples = [['iron-man.jpg'], ['wolverine.jpg']]
interpretation='default'


gr.Interface(fn=predict,inputs="image",outputs="label", title=title,description=description,examples=examples).launch()