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

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

# import pathlib
# temp = pathlib.PosixPath
# pathlib.PosixPath = pathlib.WindowsPath

learn = load_learner('model.pkl')

categories = ('Dog', 'Cat')

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

image = gr.components.Image(type="pil", height=192, width=192)
label = gr.Label()
examples = ['bear.jpg', 'cat.jpg', 'dog.jpg']

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