app.py

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

learn = load_learner('fruity1.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 = "Classify fruits using a classifier trained on Fruits-360"

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