app.py

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

learn = load_learner('model.pkl')

with open('categories.json', 'r') as f:
    categories = json.load(f)

labels = learn.dls.vocab

def predict(img):
    img = PILImage.create(img)
    _, _, probs = learn.predict(img)
    return {f"{categories[labels[i]]} ({labels[i]})": float(probs[i]) for i in range(len(labels))}


title = "Predict flower species"

gr.Interface(
    fn=predict,
    inputs=gr.inputs.Image(shape=(512, 512)),
    outputs=gr.outputs.Label(num_top_classes=len(labels)),
    title=title
    ).launch()