__all__ = ['learn','classify_image','categories','image','label','examples','intf']

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

# Cell
learn = load_learner('handpose.pkl')

# Cell
categories = ('call', 'dislike', 'fist', 'four', 'like', 'mute', 'ok', 'one', 'palm', 'peace', 
    'peace_inverted', 'rock', 'stop', 'stop_inverted', 'three', 'three2', 'two_up', 'two_up_inverted')

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

# Cell
image = gr.inputs.Image(shape=(192,192),source='webcam')
label = gr.outputs.Label()
#examples = ['beyonce-ok.jpg','dalai-lama-one.jpg']


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