import fastai.vision.all as faiv
# import pathlib
from pathlib import Path
import gradio as gr

# make this work on Windows
#temp = pathlib.PosixPath
#pathlib.PosixPath = pathlib.WindowsPath

# load model
learn = faiv.load_learner('aih_model.pkl')

# define categories
categories = ('AI Hand', 'Human Hand')

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

# set interface
image = gr.Image(shape=(512,512))
label = gr.Label()
examples = [str(x) for x in Path('./samples').glob('*')]

intf = gr.Interface(
    fn=classify_image, 
    inputs=image, 
    outputs=label,
    examples=examples,
    title='AI Hand Classifier')

intf.launch()