#| export
from fastai.vision.all import *
import gradio as gr

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

#| export
learn = load_learner('model.pkl')

#| export
categories = ('Dog', 'Cat')

def classify_images(img):
    #'Is it a car?', 'Is it a car? but as zero or one', 'probabillity of [dog, cat]'
    pred, idx, probs = learn.predict(img)
    #return dictionary
    #zip together the categories and the
                                        #turn probs to float
    return dict(zip(categories, map(float, probs)))


examples = ['dog.jpg', 'cat.jpg', 'catdog.jpg', 'he-s-a-catdog-or-dogcat.jpeg']

intf = gr.Interface(
    fn=classify_images,
    inputs=gr.Image(type="pil", image_mode="RGB", height=192, width=192),
    outputs=gr.Label(),
    examples=examples
)

intf.launch()