app.py

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

def is_cat(x):
    return 'cat' if (x.name)[0].isupper() else 'dog'

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))}

gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(224, 224)), outputs=gr.outputs.Label(num_top_classes=3)).launch(share=True)