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tf_convert_data.py
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tf_convert_data.py
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# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Convert a dataset to TFRecords format, which can be easily integrated into
a TensorFlow pipeline.
Usage:
```shell
python tf_convert_data.py \
--dataset_name=pascalvoc \
--dataset_dir=/tmp/pascalvoc \
--output_name=pascalvoc \
--output_dir=/tmp/
```
"""
import tensorflow as tf
from datasets import pascalvoc_to_tfrecords
FLAGS = tf.app.flags.FLAGS
tf.app.flags.DEFINE_string(
'dataset_name', 'pascalvoc',
'The name of the dataset to convert.')
tf.app.flags.DEFINE_string(
'dataset_dir', None,
'Directory where the original dataset is stored.')
tf.app.flags.DEFINE_string(
'output_name', 'pascalvoc',
'Basename used for TFRecords output files.')
tf.app.flags.DEFINE_string(
'output_dir', './',
'Output directory where to store TFRecords files.')
def main(_):
if not FLAGS.dataset_dir:
raise ValueError('You must supply the dataset directory with --dataset_dir')
print('Dataset directory:', FLAGS.dataset_dir)
print('Output directory:', FLAGS.output_dir)
if FLAGS.dataset_name == 'pascalvoc':
pascalvoc_to_tfrecords.run(FLAGS.dataset_dir, FLAGS.output_dir, FLAGS.output_name)
else:
raise ValueError('Dataset [%s] was not recognized.' % FLAGS.dataset_name)
if __name__ == '__main__':
tf.app.run()