app.py

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


learn = load_learner('model.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 = "Fruit classifier"
description = "Quick Fastai classifier for typical market fruit."
examples = ['Green Apple.jpg', 'Red Apple.jpg','RedGreen.jpg', 'Pineapple.jpg','Pear.jpg','Kiwi.jpg','Orange.jpg','Strawberry.jpg','Banana.jpg','Frutas.jpg']

gr.Interface(
    fn=predict,
    inputs=gr.Image(),
    outputs=gr.Label(num_top_classes=3),
    title=title,
    description=description,
    examples=examples,
).launch()
iface.launch()