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| # Copyright 2023 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 box_matcher.py.""" | |
| import tensorflow as tf, tf_keras | |
| from official.vision.ops import box_matcher | |
| class BoxMatcherTest(tf.test.TestCase): | |
| def test_box_matcher_unbatched(self): | |
| sim_matrix = tf.constant( | |
| [[0.04, 0, 0, 0], | |
| [0, 0, 1., 0]], | |
| dtype=tf.float32) | |
| fg_threshold = 0.5 | |
| bg_thresh_hi = 0.2 | |
| bg_thresh_lo = 0.0 | |
| matcher = box_matcher.BoxMatcher( | |
| thresholds=[bg_thresh_lo, bg_thresh_hi, fg_threshold], | |
| indicators=[-3, -2, -1, 1]) | |
| match_indices, match_indicators = matcher(sim_matrix) | |
| positive_matches = tf.greater_equal(match_indicators, 0) | |
| negative_matches = tf.equal(match_indicators, -2) | |
| self.assertAllEqual( | |
| positive_matches.numpy(), [False, True]) | |
| self.assertAllEqual( | |
| negative_matches.numpy(), [True, False]) | |
| self.assertAllEqual( | |
| match_indices.numpy(), [0, 2]) | |
| self.assertAllEqual( | |
| match_indicators.numpy(), [-2, 1]) | |
| def test_box_matcher_batched(self): | |
| sim_matrix = tf.constant( | |
| [[[0.04, 0, 0, 0], | |
| [0, 0, 1., 0]]], | |
| dtype=tf.float32) | |
| fg_threshold = 0.5 | |
| bg_thresh_hi = 0.2 | |
| bg_thresh_lo = 0.0 | |
| matcher = box_matcher.BoxMatcher( | |
| thresholds=[bg_thresh_lo, bg_thresh_hi, fg_threshold], | |
| indicators=[-3, -2, -1, 1]) | |
| match_indices, match_indicators = matcher(sim_matrix) | |
| positive_matches = tf.greater_equal(match_indicators, 0) | |
| negative_matches = tf.equal(match_indicators, -2) | |
| self.assertAllEqual( | |
| positive_matches.numpy(), [[False, True]]) | |
| self.assertAllEqual( | |
| negative_matches.numpy(), [[True, False]]) | |
| self.assertAllEqual( | |
| match_indices.numpy(), [[0, 2]]) | |
| self.assertAllEqual( | |
| match_indicators.numpy(), [[-2, 1]]) | |
| if __name__ == '__main__': | |
| tf.test.main() | |