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89 lines
3.1 KiB
89 lines
3.1 KiB
# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Tests for object_detection.utils.test_utils."""
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import numpy as np
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import tensorflow as tf
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from object_detection.utils import test_utils
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class TestUtilsTest(tf.test.TestCase):
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def test_diagonal_gradient_image(self):
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"""Tests if a good pyramid image is created."""
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pyramid_image = test_utils.create_diagonal_gradient_image(3, 4, 2)
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# Test which is easy to understand.
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expected_first_channel = np.array([[3, 2, 1, 0],
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[4, 3, 2, 1],
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[5, 4, 3, 2]], dtype=np.float32)
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self.assertAllEqual(np.squeeze(pyramid_image[:, :, 0]),
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expected_first_channel)
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# Actual test.
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expected_image = np.array([[[3, 30],
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[2, 20],
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[1, 10],
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[0, 0]],
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[[4, 40],
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[3, 30],
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[2, 20],
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[1, 10]],
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[[5, 50],
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[4, 40],
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[3, 30],
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[2, 20]]], dtype=np.float32)
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self.assertAllEqual(pyramid_image, expected_image)
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def test_random_boxes(self):
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"""Tests if valid random boxes are created."""
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num_boxes = 1000
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max_height = 3
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max_width = 5
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boxes = test_utils.create_random_boxes(num_boxes,
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max_height,
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max_width)
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true_column = np.ones(shape=(num_boxes)) == 1
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self.assertAllEqual(boxes[:, 0] < boxes[:, 2], true_column)
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self.assertAllEqual(boxes[:, 1] < boxes[:, 3], true_column)
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self.assertTrue(boxes[:, 0].min() >= 0)
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self.assertTrue(boxes[:, 1].min() >= 0)
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self.assertTrue(boxes[:, 2].max() <= max_height)
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self.assertTrue(boxes[:, 3].max() <= max_width)
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def test_first_rows_close_as_set(self):
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a = [1, 2, 3, 0, 0]
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b = [3, 2, 1, 0, 0]
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k = 3
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self.assertTrue(test_utils.first_rows_close_as_set(a, b, k))
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a = [[1, 2], [1, 4], [0, 0]]
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b = [[1, 4 + 1e-9], [1, 2], [0, 0]]
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k = 2
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self.assertTrue(test_utils.first_rows_close_as_set(a, b, k))
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a = [[1, 2], [1, 4], [0, 0]]
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b = [[1, 4 + 1e-9], [2, 2], [0, 0]]
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k = 2
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self.assertFalse(test_utils.first_rows_close_as_set(a, b, k))
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if __name__ == '__main__':
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tf.test.main()
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