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

learn = load_learner('model.pkl')

image = gr.inputs.Image(shape=(128, 128))
label = gr.outputs.Label()
examples = ['coral.jpg', 'crabs.jpg', 'dolphin.jpg', 'sea_rays.jpg', 'seahorse.jpg', 'turtle_tortoise.jpg']

categories = ('corals','crabs','dolphin','eel','jelly fish','lobster','nudibranchs','octopus','penguin','puffers','sea rays','sea urchins','seahorse','seal','sharks','squid','starfish','turtle_tortoise','whale')

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

interface = gr.Interface(fn=classify_img,
                inputs=image,
                outputs=label,
                examples=examples)

interface.launch(inline=False)