# -*- coding: utf-8 -*-
"""app

Automatically generated by Colaboratory.

Original file is located at
    https://colab.research.google.com/drive/1h6riFrXG5PjYEq3Lj4OM0z3NPXmroaWI
"""

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

snail_learner = load_learner('snail_learner_1_2.pkl')

labels = snail_learner.dls.vocab
def predict(img):
    img = PILImage.create(img)
    pred,pred_idx,probs = snail_learner .predict(img)
    return {labels[i]: float(probs[i]) for i in range(len(labels))}

title = "Snail or Garden?"
description = "A snail classifier trained on internet images with fastai and validated in local garden snails pictures."
article="<p style='text-align: center'><a href='https://valentinrac.com' target='_blank'>Valentin website</a></p>"
examples = ['snail1.jpg', 'snail2.jpg','slug.jpg','snail93.jpg','snail4.jpg','snail91.jpg','snail_slug2.jpg']

iface = gr.Interface(
    fn=predict,
    inputs=gr.Image(),
    outputs=gr.Label(),
    live=True,
    title=title,
    description=description,
    article=article,
    examples=examples,
)

iface.launch(share=True)