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deeplab2 / data /build_cityscapes_data_test.py

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	# coding=utf-8
	# Copyright 2021 The Deeplab2 Authors.
	#
	# 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.

	"""Tests for build_cityscapes_data."""

	import os

	from absl import flags
	import numpy as np
	from PIL import Image
	import tensorflow as tf

	from deeplab2.data import build_cityscapes_data


	FLAGS = flags.FLAGS
	_TEST_DATA_DIR = 'deeplab2/data/testdata'
	_TEST_FILE_PREFIX = 'dummy_000000_000000'


	class BuildCityscapesDataTest(tf.test.TestCase):

	def test_read_segments(self):
	cityscapes_root = os.path.join(_TEST_DATA_DIR)
	segments_dict = build_cityscapes_data._read_segments(
	cityscapes_root, dataset_split='dummy')
	self.assertIn(_TEST_FILE_PREFIX, segments_dict)
	_, segments = segments_dict[_TEST_FILE_PREFIX]
	self.assertLen(segments, 10)

	def test_generate_panoptic_label(self):
	FLAGS.treat_crowd_as_ignore = False # Test a more complicated setting
	cityscapes_root = os.path.join(_TEST_DATA_DIR)
	segments_dict = build_cityscapes_data._read_segments(
	cityscapes_root, dataset_split='dummy')
	annotation_file_name, segments = segments_dict[_TEST_FILE_PREFIX]
	panoptic_annotation_file = build_cityscapes_data._get_panoptic_annotation(
	cityscapes_root, dataset_split='dummy',
	annotation_file_name=annotation_file_name)
	panoptic_label = build_cityscapes_data._generate_panoptic_label(
	panoptic_annotation_file, segments)

	# Check panoptic label matches golden file.
	golden_file_path = os.path.join(_TEST_DATA_DIR,
	'dummy_gt_for_vps.png')
	with tf.io.gfile.GFile(golden_file_path, 'rb') as f:
	golden_label = Image.open(f)
	# The PNG file is encoded by:
	# color = [segmentId % 256, segmentId // 256, segmentId // 256 // 256]
	golden_label = np.dot(np.asarray(golden_label), [1, 256, 256 * 256])

	np.testing.assert_array_equal(panoptic_label, golden_label)

	if __name__ == '__main__':
	tf.test.main()