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

def is_cat(x): return x[0].isupper()

learn = load_learner('model.pkl')

labels = learn.dls.vocab

categories = ('Dog', 'Cat')

def predict(img):
    img = PILImage.create(img)
    img.thumbnail((192, 192))
    pred,pred_idx,probs = learn.predict(img)
    return dict(zip(categories, map(float, probs)))

examples = ['cat.jpeg', 'dog.jpeg',]
title = "Cat vs Dog classifier"

description = "Classification of dog and cat :)"
article="<p style='text-align: center'><a href='https://tmabraham.github.io/blog/gradio_hf_spaces_tutorial' target='_blank'>Blog post</a></p>"

gr.Interface(fn=predict, inputs="image", outputs="label",title=title,description=description,article=article,examples=examples).launch()