save and read images with hdf5

hdf5.py

import os.path as osp
dataset_dir = '/home/frankllin/Downloads/DomainNet'
split_dir = osp.join(dataset_dir, 'splits_mini')
image_size = 84
from PIL import Image
import h5py
import numpy as np
from tqdm import tqdm

def store_many_hdf5(h5file, images, labels):
    """ Stores an array of images to HDF5.
        Parameters:
        ---------------
        images       images array, (N, 32, 32, 3) to be stored
        labels       labels array, (N, 1) to be stored
    """
    num_images = len(images)

    # Create a dataset in the file
    dataset = h5file.create_dataset(
        "images", np.shape(images), h5py.h5t.STD_U8BE, data=images
    )
    meta_set = h5file.create_dataset(
        "labels", np.shape(labels), h5py.h5t.STD_U8BE, data=labels
    )

def read_many_hdf5(h5file):
    """ Reads image from HDF5.
        Parameters:
        ---------------
        num_images   number of images to read

        Returns:
        ----------
        images      images array, (N, 32, 32, 3) to be stored
        labels      associated meta data, int label (N, 1)
    """
    images = np.array(h5file["images"]).astype("uint8")
    labels = np.array(h5file["labels"]).astype("uint8")

    return images, labels

def main():
    # domains = ['clipart', 'painting', 'real', 'sketch']
    domains = ['clipart']
    h5file = h5py.File(osp.join(dataset_dir, 'miniDomainNet.h5'), 'w')

    for domain in domains:
        print('processing '+domain)
        h5group = h5file.create_group(domain)
        train_file_name = osp.join(split_dir,domain+'_train.txt')
        test_file = osp.join(split_dir, domain + '_test.txt')

        with open(train_file_name) as train_file:
            lines = train_file.read().splitlines()
        images = np.zeros(shape=(len(lines), image_size, image_size, 3))
        labels = np.zeros(shape=(len(lines), 1))
        for i, line in tqdm(enumerate(lines)):
            list = line.split(' ')
            image_path = osp.join(dataset_dir,list[0])
            image = Image.open(image_path)
            new_image = image.resize((image_size, image_size))
            new_image = np.array(new_image)
            label = int(list[1])
            images[i] = new_image
            labels[i]= label
        store_many_hdf5(h5group, images, labels)
    h5file.close()

if __name__ == '__main__':
    # main()
    h5file = h5py.File(osp.join(dataset_dir, 'miniDomainNet.h5'), 'r')
    h5_group = h5file['/clipart']
    images,_ = read_many_hdf5(h5_group)
    img = Image.fromarray(images[0], 'RGB')
    Image._show(img)