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

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

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

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

# Cell
categories = ('Meat', 'Vegetable')


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))
label = gr.outputs.Label()
examples = ['01b6f435-79ea-420c-89e8-edf515ea1446.jpg', '01bc3d53-ec5a-4e00-9a2d-88cb1160a50a.jpg', '01f91a06-3599-4f22-8854-056177c51fec.jpg', '3261012543_blue_apple_in_a_wicker_basket.png', '550b5661-880a-42e9-90ed-de0bea2505f0.jpg'  ]


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