from fastbook import *
from fastai.vision.widgets import *
from fastai.vision.all import *

import gradio as gr
import pathlib

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

learn = load_learner("model.pkl")
categories = ("Cat", "Dog")

def classify_img(img):
	pred, idx, probs = learn.predict(img)
	return dict(zip(categories, map(float, probs)))

image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
examples = ['dog0.jpg', 'dog1.jpg', 'dog2.jpg', 'dog3.jpg', 'dog4.jpg', 'dog5.jpg', 'dog6.jpg', 'dog7.jpg', 'dog8.jpg', 'dog9.jpg', 'cat1.jpg', 'cat2.jpg', 'cat3.jpg', 'cat4.jpg', 'cat5.jpg', 'cat6.jpg', 'cat7.jpg', 'cat8.jpg', 'cat9.jpg']

iface = gr.Interface(fn=classify_img, inputs=image, outputs=label, examples=examples)
iface.launch(inline=False)