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# Lint as: python2, python3
# Copyright 2019 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.
# ==============================================================================
"""Tests for test_utils."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from absl.testing import absltest
import numpy as np
from deeplab.evaluation import test_utils
class TestUtilsTest(absltest.TestCase):
def test_read_test_image(self):
image_array = test_utils.read_test_image('team_pred_class.png')
self.assertSequenceEqual(image_array.shape, (231, 345, 4))
def test_reads_segmentation_with_color_map(self):
rgb_to_semantic_label = {(0, 0, 0): 0, (0, 0, 255): 1, (255, 0, 0): 23}
labels = test_utils.read_segmentation_with_rgb_color_map(
'team_pred_class.png', rgb_to_semantic_label)
input_image = test_utils.read_test_image('team_pred_class.png')
np.testing.assert_array_equal(
labels == 0,
np.logical_and(input_image[:, :, 0] == 0, input_image[:, :, 2] == 0))
np.testing.assert_array_equal(labels == 1, input_image[:, :, 2] == 255)
np.testing.assert_array_equal(labels == 23, input_image[:, :, 0] == 255)
def test_reads_gt_segmentation(self):
instance_label_to_semantic_label = {
0: 0,
47: 1,
97: 1,
133: 1,
150: 1,
174: 1,
198: 23,
215: 1,
244: 1,
255: 1,
}
instances, classes = test_utils.panoptic_segmentation_with_class_map(
'team_gt_instance.png', instance_label_to_semantic_label)
expected_label_shape = (231, 345)
self.assertSequenceEqual(instances.shape, expected_label_shape)
self.assertSequenceEqual(classes.shape, expected_label_shape)
np.testing.assert_array_equal(instances == 0, classes == 0)
np.testing.assert_array_equal(instances == 198, classes == 23)
np.testing.assert_array_equal(
np.logical_and(instances != 0, instances != 198), classes == 1)
if __name__ == '__main__':
absltest.main()
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