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88 lines
3.4 KiB
88 lines
3.4 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.np_mask_ops."""
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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 np_mask_ops
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class MaskOpsTests(tf.test.TestCase):
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def setUp(self):
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masks1_0 = np.array([[0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0],
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[1, 1, 1, 1, 0, 0, 0, 0],
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[1, 1, 1, 1, 0, 0, 0, 0]],
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dtype=np.uint8)
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masks1_1 = np.array([[1, 1, 1, 1, 1, 1, 1, 1],
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[1, 1, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0]],
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dtype=np.uint8)
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masks1 = np.stack([masks1_0, masks1_1])
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masks2_0 = np.array([[0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0],
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[1, 1, 1, 1, 0, 0, 0, 0],
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[1, 1, 1, 1, 0, 0, 0, 0]],
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dtype=np.uint8)
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masks2_1 = np.array([[1, 1, 1, 1, 1, 1, 1, 0],
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[1, 1, 1, 1, 1, 0, 0, 0],
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[1, 1, 1, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0]],
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dtype=np.uint8)
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masks2_2 = np.array([[1, 1, 1, 1, 1, 0, 0, 0],
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[1, 1, 1, 1, 1, 0, 0, 0],
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[1, 1, 1, 1, 1, 0, 0, 0],
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[1, 1, 1, 1, 1, 0, 0, 0],
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[1, 1, 1, 1, 1, 0, 0, 0]],
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dtype=np.uint8)
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masks2 = np.stack([masks2_0, masks2_1, masks2_2])
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self.masks1 = masks1
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self.masks2 = masks2
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def testArea(self):
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areas = np_mask_ops.area(self.masks1)
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expected_areas = np.array([8.0, 10.0], dtype=np.float32)
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self.assertAllClose(expected_areas, areas)
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def testIntersection(self):
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intersection = np_mask_ops.intersection(self.masks1, self.masks2)
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expected_intersection = np.array(
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[[8.0, 0.0, 8.0], [0.0, 9.0, 7.0]], dtype=np.float32)
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self.assertAllClose(intersection, expected_intersection)
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def testIOU(self):
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iou = np_mask_ops.iou(self.masks1, self.masks2)
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expected_iou = np.array(
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[[1.0, 0.0, 8.0/25.0], [0.0, 9.0 / 16.0, 7.0 / 28.0]], dtype=np.float32)
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self.assertAllClose(iou, expected_iou)
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def testIOA(self):
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ioa21 = np_mask_ops.ioa(self.masks1, self.masks2)
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expected_ioa21 = np.array([[1.0, 0.0, 8.0/25.0],
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[0.0, 9.0/15.0, 7.0/25.0]],
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dtype=np.float32)
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self.assertAllClose(ioa21, expected_ioa21)
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if __name__ == '__main__':
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tf.test.main()
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