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


learn = from_pretrained_fastai("nnifil19/graph_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 = "graphic predictor"
description = "A model that classifies between different graphs"
examples = ['cosine', 'exponential', 'tangential','logarithmic','gaussian']

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