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


learn = load_learner('model.pkl')

examples = ['apples.webp', 'avocadoes.jpg', 'bananas.jpg', 'blueberries.jpg', 'grapes.jpg', 'mangos.jpg', 'oranges.jpg', 'pineapples.jpg', 'strawberries.jpg', 'watermelon.jpg']
categories = ('apples', 'avocados', 'bananas', 'bluberries', 'grapes', 'mangoes', 'oranges', 'pineapples', 'strawberries', 'watermelon')
def classify_image(img):
    pred, idx, probs = learn.predict(img)
    return dict(zip(categories, map(float, probs)))

image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()

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