text: # Copyright 2017 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 object_detection.utils.np_box_list_test."""
  
  import numpy as np
  import tensorflow as tf
  
  from object_detection.utils import np_box_list
  
  
  class BoxListTest(tf.test.TestCase):
  
    def test_invalid_box_data(self):
      with self.assertRaises(ValueError):
        np_box_list.BoxList([0, 0, 1, 1])
  
      with self.assertRaises(ValueError):
        np_box_list.BoxList(np.array([[0, 0, 1, 1]], dtype=int))
  
      with self.assertRaises(ValueError):
        np_box_list.BoxList(np.array([0, 1, 1, 3, 4], dtype=float))
  
      with self.assertRaises(ValueError):
        np_box_list.BoxList(np.array([[0, 1, 1, 3], [3, 1, 1, 5]], dtype=float))
  
    def test_has_field_with_existed_field(self):
      boxes = np.array([[3.0, 4.0, 6.0, 8.0], [14.0, 14.0, 15.0, 15.0],
                        [0.0, 0.0, 20.0, 20.0]],
                       dtype=float)
      boxlist = np_box_list.BoxList(boxes)
      self.assertTrue(boxlist.has_field('boxes'))
  
    def test_has_field_with_nonexisted_field(self):
      boxes = np.array([[3.0, 4.0, 6.0, 8.0], [14.0, 14.0, 15.0, 15.0],
                        [0.0, 0.0, 20.0, 20.0]],
                       dtype=float)
      boxlist = np_box_list.BoxList(boxes)
      self.assertFalse(boxlist.has_field('scores'))
  
    def test_get_field_with_existed_field(self):
      boxes = np.array([[3.0, 4.0, 6.0, 8.0], [14.0, 14.0, 15.0, 15.0],
                        [0.0, 0.0, 20.0, 20.0]],
                       dtype=float)
      boxlist = np_box_list.BoxList(boxes)
      self.assertTrue(np.allclose(boxlist.get_field('boxes'), boxes))
  
    def test_get_field_with_nonexited_field(self):
      boxes = np.array([[3.0, 4.0, 6.0, 8.0], [14.0, 14.0, 15.0, 15.0],
                        [0.0, 0.0, 20.0, 20.0]],
                       dtype=float)
      boxlist = np_box_list.BoxList(boxes)
      with self.assertRaises(ValueError):
        boxlist.get_field('scores')
  
  
  class AddExtraFieldTest(tf.test.TestCase):
  
    def setUp(self):
      boxes = np.array([[3.0, 4.0, 6.0, 8.0], [14.0, 14.0, 15.0, 15.0],
                        [0.0, 0.0, 20.0, 20.0]],
                       dtype=float)
      self.boxlist = np_box_list.BoxList(boxes)
  
    def test_add_already_existed_field(self):
      with self.assertRaises(ValueError):
        self.boxlist.add_field('boxes', np.array([[0, 0, 0, 1, 0]], dtype=float))
  
    def test_add_invalid_field_data(self):
      with self.assertRaises(ValueError):
        self.boxlist.add_field('scores', np.array([0.5, 0.7], dtype=float))
      with self.assertRaises(ValueError):
        self.boxlist.add_field('scores',
                               np.array([0.5, 0.7, 0.9, 0.1], dtype=float))
  
    def test_add_single_dimensional_field_data(self):
      boxlist = self.boxlist
      scores = np.array([0.5, 0.7, 0.9], dtype=float)
      boxlist.add_field('scores', scores)
      self.assertTrue(np.allclose(scores, self.boxlist.get_field('scores')))
  
    def test_add_multi_dimensional_field_data(self):
      boxlist = self.boxlist
      labels = np.array([[0, 0, 0, 1, 0], [0, 1, 0, 0, 0], [0, 0, 0, 0, 1]],
                        dtype=int)
      boxlist.add_field('labels', labels)
      self.assertTrue(np.allclose(labels, self.boxlist.get_field('labels')))
  
    def test_get_extra_fields(self):
      boxlist = self.boxlist
      self.assertSameElements(boxlist.get_extra_fields(), [])
  
      scores = np.array([0.5, 0.7, 0.9], dtype=float)
      boxlist.add_field('scores', scores)
      self.assertSameElements(boxlist.get_extra_fields(), ['scores'])
  
      labels = np.array([[0, 0, 0, 1, 0], [0, 1, 0, 0, 0], [0, 0, 0, 0, 1]],
                        dtype=int)
      boxlist.add_field('labels', labels)
      self.assertSameElements(boxlist.get_extra_fields(), ['scores', 'labels'])
  
    def test_get_coordinates(self):
      y_min, x_min, y_max, x_max = self.boxlist.get_coordinates()
  
      expected_y_min = np.array([3.0, 14.0, 0.0], dtype=float)
      expected_x_min = np.array([4.0, 14.0, 0.0], dtype=float)
      expected_y_max = np.array([6.0, 15.0, 20.0], dtype=float)
      expected_x_max = np.array([8.0, 15.0, 20.0], dtype=float)
  
      self.assertTrue(np.allclose(y_min, expected_y_min))
      self.assertTrue(np.allclose(x_min, expected_x_min))
      self.assertTrue(np.allclose(y_max, expected_y_max))
      self.assertTrue(np.allclose(x_max, expected_x_max))
  
    def test_num_boxes(self):
      boxes = np.array([[0., 0., 100., 100.], [10., 30., 50., 70.]], dtype=float)
      boxlist = np_box_list.BoxList(boxes)
      expected_num_boxes = 2
      self.assertEquals(boxlist.num_boxes(), expected_num_boxes)
  
  
  if __name__ == '__main__':
    tf.test.main()
  