app.py

import gradio as gr
import numpy as np
import tensorflow as tf
import json
import cv2
from os.path import dirname, realpath, join

current_dir = dirname(realpath(__file__))
with open(join(current_dir, 'image_labels.json')) as labels_file:
    labels=json.load(labels_file)

mobile_net = tf.keras.applications.MobileNetV2()
def image_classifier(img):
    img = cv2.resize(img, (224,224))
    arr = np.expand_dims(img, axis=0)
    arr = tf.keras.applications.mobilenet.preprocess_input(arr)
    prediction = mobile_net.predict(arr).flatten()
    return {labels[i]:float(prediction[i]) for i in range(1000)}
iface = gr.Interface(
    image_classifier,
    gr.Image(height=224, width=224),
    gr.Label(num_top_classes = 3),
    examples=[
        ['Komodo_dragon.jpg'],['tiger_shark.jpg'],['tench.jpg'],['hair_slide.jpg']
    ],
    example_labels = ['Komodo_dragon','tiger_shark','tench','hair_slide']
)
if __name__ == '__main__':
    iface.launch(share=True)