app.py

#__all__ = ["examples", "iface", "learn", "labels", "classify_bear", "bear_image", "outputs"]

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

learn = load_learner("model/export.pkl")
labels = learn.dls.vocab

examples = [
    "examples/black.jpg",
    "examples/grizzly.jpg",
    "examples/panda.jpg",
    "examples/polar.jpg",
    "examples/teddy.png"
]

def classify_bear(img):
    img = PILImage.create(img)
    pred,idx,probs = learn.predict(img)
    return f"Prediction: {pred}; Probability: {probs[idx]:.04f}"

bear_image = gr.inputs.Image(shape=(192,192))
outputs = gr.outputs.Label(num_top_classes=5)

# App launch
iface = gr.Interface(
    fn=classify_bear, inputs=bear_image, outputs=outputs, examples=examples)
iface.launch()