app.py

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


os.environ["OMP_NUM_THREADS"] = "1"
_all_ = ['is_cat', 'learn', 'classify_image',
         'categories', 'image', 'label', 'examples', 'intf']


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


learn = load_learner('CatsClassifier.pkl')
categories = ("Dog", "Cat")


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()
examples = ['dog.jpg', 'cat.jpg', 'ambiguous.jpg']

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