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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. | |
| """Test for vip_deeplab.py.""" | |
| import numpy as np | |
| import tensorflow as tf | |
| from deeplab2.model.post_processor import vip_deeplab | |
| class PostProcessingTest(tf.test.TestCase): | |
| def test_stitch_video_panoptic_prediction(self): | |
| concat_semantic = np.array( | |
| [[[0, 0, 0, 0], | |
| [0, 1, 1, 0], | |
| [0, 2, 2, 0], | |
| [2, 2, 3, 3]]], dtype=np.int32) | |
| concat_instance = np.array( | |
| [[[1, 1, 2, 2], | |
| [1, 0, 0, 2], | |
| [1, 1, 1, 2], | |
| [2, 2, 1, 1]]], dtype=np.int32) | |
| next_semantic = np.array( | |
| [[[0, 1, 1, 0], | |
| [0, 1, 1, 0], | |
| [0, 2, 2, 0], | |
| [2, 2, 3, 3]]], dtype=np.int32) | |
| next_instance = np.array( | |
| [[[2, 0, 0, 1], | |
| [2, 0, 0, 1], | |
| [2, 4, 4, 1], | |
| [5, 5, 3, 3]]], dtype=np.int32) | |
| label_divisor = 1000 | |
| concat_panoptic = concat_semantic * label_divisor + concat_instance | |
| next_panoptic = next_semantic * label_divisor + next_instance | |
| new_panoptic = vip_deeplab.stitch_video_panoptic_prediction( | |
| concat_panoptic, | |
| next_panoptic, | |
| label_divisor) | |
| # The expected instance is manually computed. It should receive the IDs | |
| # propagated from concat_instance by IoU matching between concat_panoptic | |
| # and next_panoptic. | |
| expected_semantic = next_semantic | |
| expected_instance = np.array( | |
| [[[1, 0, 0, 2], | |
| [1, 0, 0, 2], | |
| [1, 1, 1, 2], | |
| [2, 2, 1, 1]]], dtype=np.int32) | |
| expected_panoptic = expected_semantic * label_divisor + expected_instance | |
| np.testing.assert_array_equal(expected_panoptic, new_panoptic) | |
| if __name__ == '__main__': | |
| tf.test.main() | |