Deep Learning By Example

Loading the CIFAR-10 dataset

In this implementation, we'll use CIFAR-10, which is one of the most widely used datasets for object detection. So, let's start off by defining a helper class to download and extract the CIFAR-10 dataset, if it's not already downloaded:

cifar10_batches_dir_path = 'cifar-10-batches-py'tar_gz_filename = 'cifar-10-python.tar.gz'class DLProgress(tqdm):    last_block = 0    def hook(self, block_num=1, block_size=1, total_size=None):        self.total = total_size        self.update((block_num - self.last_block) * block_size)        self.last_block = block_numif not isfile(tar_gz_filename):    with DLProgress(unit='B', unit_scale=True, miniters=1, desc='CIFAR-10 Python Images Batches') as pbar:        urlretrieve( 'https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz', ...