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

learn = load_learner('model.pkl')

categories = 'elliptical', 'irregular', 'spiral'
def classify_img(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()
examples = ['elliptical.jpg', 'irregular.jpg', 'spiral.jpg']
for img in examples:
    img = Image.open(img)
    img = img.resize((192,192), Image.NEAREST)

iface = gr.Interface(fn = classify_img, inputs = image, outputs = label, title = 'Galaxy Classifier', examples = examples)
iface.launch()