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

def is_cat(x): return x[0].isupper()
im = PILImage.create('dog.jpeg')
im.thumbnail((192,192))

learn = load_learner('model.pkl')

categories = ('dog', 'cat')
def classify_image(img):
    pred, idx, prob = learn.predict(img)
    return dict(zip(categories, map(float, prob)))
classify_image(im)

image = gr.inputs.Image(shape=(192,192))
label = gr.outputs.Label()
examples = ['dog.jpeg', 'cat.jpeg', 'geow.jpg']
intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
intf.launch(inline=False)