client.py

# -*- coding:utf-8 -*-
# @time :2019.09.24
# @IDE : pycharm
# @author :lxztju
# @github : https://github.com/lxztju

import requests
import argparse

# Initialize the keras REST API endpoint URL.
REST_API_URL = 'http://127.0.0.1:5000/predict'


def predict_result(image_path):
    # Initialize image path
    image = open(image_path, 'rb').read()
    payload = {'image': image}

    # Submit the request.
    r = requests.post(REST_API_URL, files=payload).json()

    # Ensure the request was successful.
    if r['success']:
        print(r['predictions'])

    # Otherwise, the request failed.
    else:
        print('Request failed')


if __name__ == '__main__':
    parser = argparse.ArgumentParser(description='Classification demo')
    parser.add_argument('--file', type=str, help='test image file')

    args = parser.parse_args()
    predict_result(args.file)