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"""Tests for object_detection.utils.np_box_mask_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_mask_list |
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class BoxMaskListTest(tf.test.TestCase): |
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def test_invalid_box_mask_data(self): |
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with self.assertRaises(ValueError): |
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np_box_mask_list.BoxMaskList( |
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box_data=[0, 0, 1, 1], |
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mask_data=np.zeros([1, 3, 3], dtype=np.uint8)) |
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with self.assertRaises(ValueError): |
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np_box_mask_list.BoxMaskList( |
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box_data=np.array([[0, 0, 1, 1]], dtype=int), |
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mask_data=np.zeros([1, 3, 3], dtype=np.uint8)) |
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with self.assertRaises(ValueError): |
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np_box_mask_list.BoxMaskList( |
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box_data=np.array([0, 1, 1, 3, 4], dtype=float), |
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mask_data=np.zeros([1, 3, 3], dtype=np.uint8)) |
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with self.assertRaises(ValueError): |
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np_box_mask_list.BoxMaskList( |
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box_data=np.array([[0, 1, 1, 3], [3, 1, 1, 5]], dtype=float), |
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mask_data=np.zeros([2, 3, 3], dtype=np.uint8)) |
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with self.assertRaises(ValueError): |
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np_box_mask_list.BoxMaskList( |
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box_data=np.array([[0, 1, 1, 3], [1, 1, 1, 5]], dtype=float), |
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mask_data=np.zeros([3, 5, 5], dtype=np.uint8)) |
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with self.assertRaises(ValueError): |
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np_box_mask_list.BoxMaskList( |
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box_data=np.array([[0, 1, 1, 3], [1, 1, 1, 5]], dtype=float), |
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mask_data=np.zeros([2, 5], dtype=np.uint8)) |
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with self.assertRaises(ValueError): |
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np_box_mask_list.BoxMaskList( |
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box_data=np.array([[0, 1, 1, 3], [1, 1, 1, 5]], dtype=float), |
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mask_data=np.zeros([2, 5, 5, 5], dtype=np.uint8)) |
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with self.assertRaises(ValueError): |
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np_box_mask_list.BoxMaskList( |
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box_data=np.array([[0, 1, 1, 3], [1, 1, 1, 5]], dtype=float), |
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mask_data=np.zeros([2, 5, 5], dtype=np.int32)) |
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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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box_mask_list = np_box_mask_list.BoxMaskList( |
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box_data=boxes, mask_data=np.zeros([3, 5, 5], dtype=np.uint8)) |
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self.assertTrue(box_mask_list.has_field('boxes')) |
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self.assertTrue(box_mask_list.has_field('masks')) |
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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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box_mask_list = np_box_mask_list.BoxMaskList( |
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box_data=boxes, mask_data=np.zeros([3, 3, 3], dtype=np.uint8)) |
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self.assertFalse(box_mask_list.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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masks = np.zeros([3, 3, 3], dtype=np.uint8) |
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box_mask_list = np_box_mask_list.BoxMaskList( |
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box_data=boxes, mask_data=masks) |
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self.assertTrue(np.allclose(box_mask_list.get_field('boxes'), boxes)) |
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self.assertTrue(np.allclose(box_mask_list.get_field('masks'), masks)) |
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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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masks = np.zeros([3, 3, 3], dtype=np.uint8) |
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box_mask_list = np_box_mask_list.BoxMaskList( |
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box_data=boxes, mask_data=masks) |
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with self.assertRaises(ValueError): |
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box_mask_list.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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masks = np.zeros([3, 3, 3], dtype=np.uint8) |
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self.box_mask_list = np_box_mask_list.BoxMaskList( |
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box_data=boxes, mask_data=masks) |
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def test_add_already_existed_field_bbox(self): |
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with self.assertRaises(ValueError): |
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self.box_mask_list.add_field('boxes', |
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np.array([[0, 0, 0, 1, 0]], dtype=float)) |
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def test_add_already_existed_field_mask(self): |
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with self.assertRaises(ValueError): |
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self.box_mask_list.add_field('masks', |
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np.zeros([3, 3, 3], dtype=np.uint8)) |
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def test_add_invalid_field_data(self): |
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with self.assertRaises(ValueError): |
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self.box_mask_list.add_field('scores', np.array([0.5, 0.7], dtype=float)) |
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with self.assertRaises(ValueError): |
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self.box_mask_list.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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box_mask_list = self.box_mask_list |
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scores = np.array([0.5, 0.7, 0.9], dtype=float) |
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box_mask_list.add_field('scores', scores) |
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self.assertTrue(np.allclose(scores, self.box_mask_list.get_field('scores'))) |
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def test_add_multi_dimensional_field_data(self): |
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box_mask_list = self.box_mask_list |
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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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box_mask_list.add_field('labels', labels) |
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self.assertTrue(np.allclose(labels, self.box_mask_list.get_field('labels'))) |
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def test_get_extra_fields(self): |
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box_mask_list = self.box_mask_list |
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self.assertItemsEqual(box_mask_list.get_extra_fields(), ['masks']) |
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scores = np.array([0.5, 0.7, 0.9], dtype=float) |
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box_mask_list.add_field('scores', scores) |
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self.assertItemsEqual(box_mask_list.get_extra_fields(), ['masks', '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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box_mask_list.add_field('labels', labels) |
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self.assertItemsEqual(box_mask_list.get_extra_fields(), |
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['masks', 'scores', 'labels']) |
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def test_get_coordinates(self): |
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y_min, x_min, y_max, x_max = self.box_mask_list.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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masks = np.zeros([2, 5, 5], dtype=np.uint8) |
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box_mask_list = np_box_mask_list.BoxMaskList( |
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box_data=boxes, mask_data=masks) |
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expected_num_boxes = 2 |
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self.assertEquals(box_mask_list.num_boxes(), expected_num_boxes) |
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if __name__ == '__main__': |
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tf.test.main() |
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