app.py

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

# pretrained model
learn = load_learner('model.pkl')

# The categories
categories = ('Katy', 'Zooey')

# Define the prediction function
def classify_image(img):
    pred, idx, probs = learn.predict(img)
    return {categories[i]: float(probs[i]) for i in range(len(categories))}

# Gradio interface
image = gr.Image(type="pil")
label = gr.Label()
examples = ['katy.jpg', 'katy2.jpg', 'zooey1.jpg', 'zooey2.jpg']

intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
intf.launch(inline=False)