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135 lines
5.1 KiB
135 lines
5.1 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.utils.np_box_list_test."""
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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_box_list
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class BoxListTest(tf.test.TestCase):
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def test_invalid_box_data(self):
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with self.assertRaises(ValueError):
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np_box_list.BoxList([0, 0, 1, 1])
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with self.assertRaises(ValueError):
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np_box_list.BoxList(np.array([[0, 0, 1, 1]], dtype=int))
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with self.assertRaises(ValueError):
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np_box_list.BoxList(np.array([0, 1, 1, 3, 4], dtype=float))
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with self.assertRaises(ValueError):
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np_box_list.BoxList(np.array([[0, 1, 1, 3], [3, 1, 1, 5]], dtype=float))
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def test_has_field_with_existed_field(self):
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boxes = np.array([[3.0, 4.0, 6.0, 8.0], [14.0, 14.0, 15.0, 15.0],
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[0.0, 0.0, 20.0, 20.0]],
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dtype=float)
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boxlist = np_box_list.BoxList(boxes)
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self.assertTrue(boxlist.has_field('boxes'))
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def test_has_field_with_nonexisted_field(self):
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boxes = np.array([[3.0, 4.0, 6.0, 8.0], [14.0, 14.0, 15.0, 15.0],
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[0.0, 0.0, 20.0, 20.0]],
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dtype=float)
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boxlist = np_box_list.BoxList(boxes)
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self.assertFalse(boxlist.has_field('scores'))
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def test_get_field_with_existed_field(self):
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boxes = np.array([[3.0, 4.0, 6.0, 8.0], [14.0, 14.0, 15.0, 15.0],
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[0.0, 0.0, 20.0, 20.0]],
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dtype=float)
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boxlist = np_box_list.BoxList(boxes)
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self.assertTrue(np.allclose(boxlist.get_field('boxes'), boxes))
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def test_get_field_with_nonexited_field(self):
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boxes = np.array([[3.0, 4.0, 6.0, 8.0], [14.0, 14.0, 15.0, 15.0],
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[0.0, 0.0, 20.0, 20.0]],
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dtype=float)
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boxlist = np_box_list.BoxList(boxes)
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with self.assertRaises(ValueError):
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boxlist.get_field('scores')
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class AddExtraFieldTest(tf.test.TestCase):
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def setUp(self):
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boxes = np.array([[3.0, 4.0, 6.0, 8.0], [14.0, 14.0, 15.0, 15.0],
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[0.0, 0.0, 20.0, 20.0]],
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dtype=float)
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self.boxlist = np_box_list.BoxList(boxes)
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def test_add_already_existed_field(self):
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with self.assertRaises(ValueError):
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self.boxlist.add_field('boxes', np.array([[0, 0, 0, 1, 0]], dtype=float))
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def test_add_invalid_field_data(self):
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with self.assertRaises(ValueError):
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self.boxlist.add_field('scores', np.array([0.5, 0.7], dtype=float))
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with self.assertRaises(ValueError):
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self.boxlist.add_field('scores',
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np.array([0.5, 0.7, 0.9, 0.1], dtype=float))
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def test_add_single_dimensional_field_data(self):
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boxlist = self.boxlist
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scores = np.array([0.5, 0.7, 0.9], dtype=float)
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boxlist.add_field('scores', scores)
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self.assertTrue(np.allclose(scores, self.boxlist.get_field('scores')))
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def test_add_multi_dimensional_field_data(self):
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boxlist = self.boxlist
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labels = np.array([[0, 0, 0, 1, 0], [0, 1, 0, 0, 0], [0, 0, 0, 0, 1]],
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dtype=int)
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boxlist.add_field('labels', labels)
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self.assertTrue(np.allclose(labels, self.boxlist.get_field('labels')))
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def test_get_extra_fields(self):
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boxlist = self.boxlist
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self.assertItemsEqual(boxlist.get_extra_fields(), [])
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scores = np.array([0.5, 0.7, 0.9], dtype=float)
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boxlist.add_field('scores', scores)
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self.assertItemsEqual(boxlist.get_extra_fields(), ['scores'])
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labels = np.array([[0, 0, 0, 1, 0], [0, 1, 0, 0, 0], [0, 0, 0, 0, 1]],
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dtype=int)
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boxlist.add_field('labels', labels)
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self.assertItemsEqual(boxlist.get_extra_fields(), ['scores', 'labels'])
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def test_get_coordinates(self):
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y_min, x_min, y_max, x_max = self.boxlist.get_coordinates()
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expected_y_min = np.array([3.0, 14.0, 0.0], dtype=float)
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expected_x_min = np.array([4.0, 14.0, 0.0], dtype=float)
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expected_y_max = np.array([6.0, 15.0, 20.0], dtype=float)
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expected_x_max = np.array([8.0, 15.0, 20.0], dtype=float)
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self.assertTrue(np.allclose(y_min, expected_y_min))
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self.assertTrue(np.allclose(x_min, expected_x_min))
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self.assertTrue(np.allclose(y_max, expected_y_max))
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self.assertTrue(np.allclose(x_max, expected_x_max))
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def test_num_boxes(self):
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boxes = np.array([[0., 0., 100., 100.], [10., 30., 50., 70.]], dtype=float)
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boxlist = np_box_list.BoxList(boxes)
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expected_num_boxes = 2
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self.assertEquals(boxlist.num_boxes(), expected_num_boxes)
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if __name__ == '__main__':
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tf.test.main()
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