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# Copyright 2017 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.
# ==============================================================================
"""Test for create_kitti_tf_record.py."""
import os
import numpy as np
import PIL.Image
import tensorflow as tf
from object_detection.dataset_tools import create_kitti_tf_record
class CreateKittiTFRecordTest(tf.test.TestCase):
def _assertProtoEqual(self, proto_field, expectation):
"""Helper function to assert if a proto field equals some value.
Args:
proto_field: The protobuf field to compare.
expectation: The expected value of the protobuf field.
"""
proto_list = [p for p in proto_field]
self.assertListEqual(proto_list, expectation)
def test_dict_to_tf_example(self):
image_file_name = 'tmp_image.jpg'
image_data = np.random.rand(256, 256, 3)
save_path = os.path.join(self.get_temp_dir(), image_file_name)
image = PIL.Image.fromarray(image_data, 'RGB')
image.save(save_path)
annotations = {}
annotations['2d_bbox_left'] = np.array([64])
annotations['2d_bbox_top'] = np.array([64])
annotations['2d_bbox_right'] = np.array([192])
annotations['2d_bbox_bottom'] = np.array([192])
annotations['type'] = ['car']
annotations['truncated'] = np.array([1])
annotations['alpha'] = np.array([2])
annotations['3d_bbox_height'] = np.array([10])
annotations['3d_bbox_width'] = np.array([11])
annotations['3d_bbox_length'] = np.array([12])
annotations['3d_bbox_x'] = np.array([13])
annotations['3d_bbox_y'] = np.array([14])
annotations['3d_bbox_z'] = np.array([15])
annotations['3d_bbox_rot_y'] = np.array([4])
label_map_dict = {
'background': 0,
'car': 1,
}
example = create_kitti_tf_record.prepare_example(
save_path,
annotations,
label_map_dict)
self._assertProtoEqual(
example.features.feature['image/height'].int64_list.value, [256])
self._assertProtoEqual(
example.features.feature['image/width'].int64_list.value, [256])
self._assertProtoEqual(
example.features.feature['image/filename'].bytes_list.value,
[save_path])
self._assertProtoEqual(
example.features.feature['image/source_id'].bytes_list.value,
[save_path])
self._assertProtoEqual(
example.features.feature['image/format'].bytes_list.value, ['png'])
self._assertProtoEqual(
example.features.feature['image/object/bbox/xmin'].float_list.value,
[0.25])
self._assertProtoEqual(
example.features.feature['image/object/bbox/ymin'].float_list.value,
[0.25])
self._assertProtoEqual(
example.features.feature['image/object/bbox/xmax'].float_list.value,
[0.75])
self._assertProtoEqual(
example.features.feature['image/object/bbox/ymax'].float_list.value,
[0.75])
self._assertProtoEqual(
example.features.feature['image/object/class/text'].bytes_list.value,
['car'])
self._assertProtoEqual(
example.features.feature['image/object/class/label'].int64_list.value,
[1])
self._assertProtoEqual(
example.features.feature['image/object/truncated'].float_list.value,
[1])
self._assertProtoEqual(
example.features.feature['image/object/alpha'].float_list.value,
[2])
self._assertProtoEqual(example.features.feature[
'image/object/3d_bbox/height'].float_list.value, [10])
self._assertProtoEqual(
example.features.feature['image/object/3d_bbox/width'].float_list.value,
[11])
self._assertProtoEqual(example.features.feature[
'image/object/3d_bbox/length'].float_list.value, [12])
self._assertProtoEqual(
example.features.feature['image/object/3d_bbox/x'].float_list.value,
[13])
self._assertProtoEqual(
example.features.feature['image/object/3d_bbox/y'].float_list.value,
[14])
self._assertProtoEqual(
example.features.feature['image/object/3d_bbox/z'].float_list.value,
[15])
self._assertProtoEqual(
example.features.feature['image/object/3d_bbox/rot_y'].float_list.value,
[4])
if __name__ == '__main__':
tf.test.main()
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