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


import pathlib
plt = platform.system()
if plt == 'Linux':
    pathlib.WindowsPath = pathlib.PosixPath

learner = load_learner('model.pkl')
labels = tuple(learner.dls.vocab)


def predict_fn(img):
    pred, pred_idx, probs = learner.predict(img)
    return {labels[i]: float(probs[i]) for i in range(len(labels))}


gr.Interface(predict_fn,
             inputs=gr.components.Image(),
             outputs=gr.components.Label(num_top_classes=8),
             examples=['t.jpg', 'tbad.jpg', 'e.jpg', 'ebad.jpg'],
             ).launch()