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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. | |
| # ============================================================================== | |
| """Tests for object_detection.np_mask_ops.""" | |
| from __future__ import absolute_import | |
| from __future__ import division | |
| from __future__ import print_function | |
| import numpy as np | |
| import tensorflow.compat.v1 as tf | |
| from object_detection.utils import np_mask_ops | |
| class MaskOpsTests(tf.test.TestCase): | |
| def setUp(self): | |
| masks1_0 = np.array([[0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0], | |
| [1, 1, 1, 1, 0, 0, 0, 0], | |
| [1, 1, 1, 1, 0, 0, 0, 0]], | |
| dtype=np.uint8) | |
| masks1_1 = np.array([[1, 1, 1, 1, 1, 1, 1, 1], | |
| [1, 1, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0]], | |
| dtype=np.uint8) | |
| masks1 = np.stack([masks1_0, masks1_1]) | |
| masks2_0 = np.array([[0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0], | |
| [1, 1, 1, 1, 0, 0, 0, 0], | |
| [1, 1, 1, 1, 0, 0, 0, 0]], | |
| dtype=np.uint8) | |
| masks2_1 = np.array([[1, 1, 1, 1, 1, 1, 1, 0], | |
| [1, 1, 1, 1, 1, 0, 0, 0], | |
| [1, 1, 1, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0], | |
| [0, 0, 0, 0, 0, 0, 0, 0]], | |
| dtype=np.uint8) | |
| masks2_2 = np.array([[1, 1, 1, 1, 1, 0, 0, 0], | |
| [1, 1, 1, 1, 1, 0, 0, 0], | |
| [1, 1, 1, 1, 1, 0, 0, 0], | |
| [1, 1, 1, 1, 1, 0, 0, 0], | |
| [1, 1, 1, 1, 1, 0, 0, 0]], | |
| dtype=np.uint8) | |
| masks2 = np.stack([masks2_0, masks2_1, masks2_2]) | |
| self.masks1 = masks1 | |
| self.masks2 = masks2 | |
| def testArea(self): | |
| areas = np_mask_ops.area(self.masks1) | |
| expected_areas = np.array([8.0, 10.0], dtype=np.float32) | |
| self.assertAllClose(expected_areas, areas) | |
| def testIntersection(self): | |
| intersection = np_mask_ops.intersection(self.masks1, self.masks2) | |
| expected_intersection = np.array( | |
| [[8.0, 0.0, 8.0], [0.0, 9.0, 7.0]], dtype=np.float32) | |
| self.assertAllClose(intersection, expected_intersection) | |
| def testIOU(self): | |
| iou = np_mask_ops.iou(self.masks1, self.masks2) | |
| expected_iou = np.array( | |
| [[1.0, 0.0, 8.0/25.0], [0.0, 9.0 / 16.0, 7.0 / 28.0]], dtype=np.float32) | |
| self.assertAllClose(iou, expected_iou) | |
| def testIOA(self): | |
| ioa21 = np_mask_ops.ioa(self.masks1, self.masks2) | |
| expected_ioa21 = np.array([[1.0, 0.0, 8.0/25.0], | |
| [0.0, 9.0/15.0, 7.0/25.0]], | |
| dtype=np.float32) | |
| self.assertAllClose(ioa21, expected_ioa21) | |
| if __name__ == '__main__': | |
| tf.test.main() | |