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81 lines
3.3 KiB
81 lines
3.3 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.core.bipartite_matcher."""
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import tensorflow as tf
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from object_detection.matchers import bipartite_matcher
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class GreedyBipartiteMatcherTest(tf.test.TestCase):
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def test_get_expected_matches_when_all_rows_are_valid(self):
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similarity_matrix = tf.constant([[0.50, 0.1, 0.8], [0.15, 0.2, 0.3]])
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valid_rows = tf.ones([2], dtype=tf.bool)
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expected_match_results = [-1, 1, 0]
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matcher = bipartite_matcher.GreedyBipartiteMatcher()
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match = matcher.match(similarity_matrix, valid_rows=valid_rows)
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with self.test_session() as sess:
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match_results_out = sess.run(match._match_results)
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self.assertAllEqual(match_results_out, expected_match_results)
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def test_get_expected_matches_with_all_rows_be_default(self):
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similarity_matrix = tf.constant([[0.50, 0.1, 0.8], [0.15, 0.2, 0.3]])
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expected_match_results = [-1, 1, 0]
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matcher = bipartite_matcher.GreedyBipartiteMatcher()
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match = matcher.match(similarity_matrix)
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with self.test_session() as sess:
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match_results_out = sess.run(match._match_results)
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self.assertAllEqual(match_results_out, expected_match_results)
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def test_get_no_matches_with_zero_valid_rows(self):
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similarity_matrix = tf.constant([[0.50, 0.1, 0.8], [0.15, 0.2, 0.3]])
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valid_rows = tf.zeros([2], dtype=tf.bool)
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expected_match_results = [-1, -1, -1]
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matcher = bipartite_matcher.GreedyBipartiteMatcher()
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match = matcher.match(similarity_matrix, valid_rows)
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with self.test_session() as sess:
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match_results_out = sess.run(match._match_results)
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self.assertAllEqual(match_results_out, expected_match_results)
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def test_get_expected_matches_with_only_one_valid_row(self):
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similarity_matrix = tf.constant([[0.50, 0.1, 0.8], [0.15, 0.2, 0.3]])
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valid_rows = tf.constant([True, False], dtype=tf.bool)
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expected_match_results = [-1, -1, 0]
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matcher = bipartite_matcher.GreedyBipartiteMatcher()
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match = matcher.match(similarity_matrix, valid_rows)
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with self.test_session() as sess:
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match_results_out = sess.run(match._match_results)
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self.assertAllEqual(match_results_out, expected_match_results)
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def test_get_expected_matches_with_only_one_valid_row_at_bottom(self):
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similarity_matrix = tf.constant([[0.15, 0.2, 0.3], [0.50, 0.1, 0.8]])
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valid_rows = tf.constant([False, True], dtype=tf.bool)
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expected_match_results = [-1, -1, 0]
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matcher = bipartite_matcher.GreedyBipartiteMatcher()
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match = matcher.match(similarity_matrix, valid_rows)
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with self.test_session() as sess:
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match_results_out = sess.run(match._match_results)
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self.assertAllEqual(match_results_out, expected_match_results)
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if __name__ == '__main__':
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tf.test.main()
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