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


learn = from_pretrained_fastai("pulmonesdeminero/figure_classifier")
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 = "Figure predictor"
description = "A simple model that tries to identify geometrical figures."
examples = ['square.png', 'circle.png', 'triangle.png', 'cube.jpg', 'sphere.jpg', 'tetrahedron.jpg', 'mix1.jpg', 'mix2.png']

gr.Interface(
    fn=predict,
    inputs=gr.Image(),
    outputs=gr.Label(num_top_classes=3),
    title=title,
    description=description,
    examples=examples,
).launch()