Machine Learning with TensorFlow 1.x

Loading the user-labeled data

First, we will add the code to download all user-labeled images from the production server:

 import tensorflow as tf import os import json import random import requests import shutil from scipy.misc import imread, imsave from datetime import datetime from tqdm import tqdm import nets, models, datasets def ensure_folder_exists(folder_path): if not os.path.exists(folder_path): os.mkdir(folder_path) return folder_path def download_user_data(url, user_dir, train_ratio=0.8): response = requests.get("%s/user-labels" % url) data = json.loads(response.text) if not os.path.exists(user_dir): os.mkdir(user_dir) user_dir = ensure_folder_exists(user_dir) train_folder = ensure_folder_exists(os.path.join(user_dir, "trainval")) ...