from fastai import *
from fastai.vision.all import *
import gradio as gr
import pathlib
#  def is_cat(x): return x[0].isupper()


# Ensure that the correct Path object is used here based on the OS
# pathlib.PosixPath = pathlib.WindowsPath
# path = Path()
model_path = str(Path('export.pkl'))
learn = load_learner(model_path)
# learn = load_learner(path/'export.pkl')

categories = ('black', 'grizzly', 'teddy')

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)