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


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))}


title = "Gradio test"
description = "Fastai classifier for AI/non AI portraits and Landscapes."
examples = ['examples/port.jpg', 'examples/ia_port.jpg', 'examples/land.jpg','examples/ia_land.jpg']

gr.Interface(
    fn=predict,
    inputs=gr.Image(),
    outputs=gr.Label(num_top_classes=2),
    title=title,
    description=description,
    examples=examples,
).launch()
iface.launch()