app.py

import gradio as gr
from fastai.vision.all import load_learner, PILImage
 
# Meto el modelo
learn = load_learner('model.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))}
 
# Ponemos titulo y descripción
gr.Interface(
    fn=predict,
    inputs=gr.Image(),
    outputs=gr.Label(num_top_classes=2),
    title="Classifier",
    description="Human vs Monkey").launch()