def gen_tfrecords(img_dir, label_file, output_dir, net, shuffle=False):
tfrecord_file = "{}/{}_bbox_landmark.tfrecord".format(output_dir, net)
if tf.gfile.Exists(tfrecord_file):
print(
"Dataset (tfrecord) files already exist. Exiting without recreating them."
)
return
labels = read_label_file2(label_file)
if shuffle:
tfrecord_file = tfrecord_file + "_shuffle"
random.shuffle(labels)
with tf.python_io.TFRecordWriter(tfrecord_file) as tfrecord_writer:
for i, data_unit in enumerate(labels):
if (i + 1) % 100 == 0:
sys.stdout.write('\r>> {}/{} images has been converted'.format(
i + 1, len(labels)))
sys.stdout.flush()
filename = data_unit['filename']
img_path = os.path.join(img_dir, filename)
image_data, height, width = _process_image_withoutcoder(img_path)
example = _convert_to_example_simple(data_unit, image_data)
tfrecord_writer.write(example.SerializeToString())
print('\nFinished converting the MTCNN dataset (tfrecords)!')
def _add_to_tfrecord(filename, image_example, tfrecord_writer):
"""Loads data from image and annotations files and add them to a TFRecord.
Args:
dataset_dir: Dataset directory;
name: Image name to add to the TFRecord;
tfrecord_writer: The TFRecord writer to use for writing.
"""
print('---',filename)
# filename = os.path.join('../data', filename)
image_data, height, width = _process_image_withoutcoder(filename)
example = _convert_to_example_simple(image_example, image_data)
tfrecord_writer.write(example.SerializeToString())
def _add_to_tfrecord(filename, image_example, tfrecord_writer):
"""Loads data from image and annotations files and add them to a TFRecord.
Args:
dataset_dir: Dataset directory;
name: Image name to add to the TFRecord;
tfrecord_writer: The TFRecord writer to use for writing.
"""
# print('---', filename)
# imaga_data:array to string
# height:original image's height
# width:original image's width
# image_example dict contains image's info
image_data, height, width = _process_image_withoutcoder(filename)
example = _convert_to_example_simple(image_example, image_data)
tfrecord_writer.write(example.SerializeToString())
def _add_to_tfrecord(filename, image_example, tfrecord_writer):
"""Loads data from image and annotations files and add them to a TFRecord.
Args:
dataset_dir: Dataset directory;
name: Image name to add to the TFRecord;
tfrecord_writer: The TFRecord writer to use for writing.
"""
print('---', filename)
#imaga_data:array to string
#height:original image's height
#width:original image's width
#image_example dict contains image's info
image_data, height, width = _process_image_withoutcoder(filename)
example = _convert_to_example_simple(image_example, image_data)
tfrecord_writer.write(example.SerializeToString())
def _add_to_tfrecord(filename, image_example, tfrecord_writer):
#从图片和注释中加载数据，并添加他们到tfrecord
image_data, height, width = _process_image_withoutcoder(filename)
example = _convert_to_example_simple(image_example, image_data)
tfrecord_writer.write(example.SerializeToString())
def _add_to_tfrecord(filename, image_example, tfrecord_writer):
print('---', filename)
image_data, height, width = _process_image_withoutcoder(filename)
example = _convert_to_example_simple(image_example, image_data)
tfrecord_writer.write(example.SerializeToString())
