def main(argv):
# Get the data.
train_images_filename = input_data.maybe_download(
TRAIN_IMAGES, FLAGS.directory)
train_labels_filename = input_data.maybe_download(
TRAIN_LABELS, FLAGS.directory)
test_images_filename = input_data.maybe_download(
TEST_IMAGES, FLAGS.directory)
test_labels_filename = input_data.maybe_download(
TEST_LABELS, FLAGS.directory)
# Extract it into numpy arrays.
train_images = input_data.extract_images(train_images_filename)
train_labels = input_data.extract_labels(train_labels_filename)
test_images = input_data.extract_images(test_images_filename)
test_labels = input_data.extract_labels(test_labels_filename)
# Generate a validation set.
validation_images = train_images[:FLAGS.validation_size, :, :, :]
validation_labels = train_labels[:FLAGS.validation_size]
train_images = train_images[FLAGS.validation_size:, :, :, :]
train_labels = train_labels[FLAGS.validation_size:]
# Convert to Examples and write the result to TFRecords.
convert_to(train_images, train_labels, 'train')
convert_to(validation_images, validation_labels, 'validation')
convert_to(test_images, test_labels, 'test')
def main(argv):
# Get the data.
train_images_filename = input_data.maybe_download(
TRAIN_IMAGES, FLAGS.directory)
train_labels_filename = input_data.maybe_download(
TRAIN_LABELS, FLAGS.directory)
test_images_filename = input_data.maybe_download(
TEST_IMAGES, FLAGS.directory)
test_labels_filename = input_data.maybe_download(
TEST_LABELS, FLAGS.directory)
# Extract it into numpy arrays.
train_images = input_data.extract_images(train_images_filename)
train_labels = input_data.extract_labels(train_labels_filename)
test_images = input_data.extract_images(test_images_filename)
test_labels = input_data.extract_labels(test_labels_filename)
# Generate a validation set.
validation_images = train_images[:FLAGS.validation_size, :, :, :]
validation_labels = train_labels[:FLAGS.validation_size]
train_images = train_images[FLAGS.validation_size:, :, :, :]
train_labels = train_labels[FLAGS.validation_size:]
# Convert to Examples and write the result to TFRecords.
convert_to(train_images, train_labels, 'train')
convert_to(validation_images, validation_labels, 'validation')
convert_to(test_images, test_labels, 'test')