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"""Tests for object_detection.core.box_list.""" |
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import tensorflow as tf |
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from object_detection.core import box_list |
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class BoxListTest(tf.test.TestCase): |
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"""Tests for BoxList class.""" |
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def test_num_boxes(self): |
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data = tf.constant([[0, 0, 1, 1], [1, 1, 2, 3], [3, 4, 5, 5]], tf.float32) |
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expected_num_boxes = 3 |
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boxes = box_list.BoxList(data) |
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with self.test_session() as sess: |
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num_boxes_output = sess.run(boxes.num_boxes()) |
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self.assertEquals(num_boxes_output, expected_num_boxes) |
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def test_get_correct_center_coordinates_and_sizes(self): |
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boxes = [[10.0, 10.0, 20.0, 15.0], [0.2, 0.1, 0.5, 0.4]] |
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boxes = box_list.BoxList(tf.constant(boxes)) |
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centers_sizes = boxes.get_center_coordinates_and_sizes() |
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expected_centers_sizes = [[15, 0.35], [12.5, 0.25], [10, 0.3], [5, 0.3]] |
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with self.test_session() as sess: |
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centers_sizes_out = sess.run(centers_sizes) |
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self.assertAllClose(centers_sizes_out, expected_centers_sizes) |
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def test_create_box_list_with_dynamic_shape(self): |
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data = tf.constant([[0, 0, 1, 1], [1, 1, 2, 3], [3, 4, 5, 5]], tf.float32) |
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indices = tf.reshape(tf.where(tf.greater([1, 0, 1], 0)), [-1]) |
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data = tf.gather(data, indices) |
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assert data.get_shape().as_list() == [None, 4] |
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expected_num_boxes = 2 |
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boxes = box_list.BoxList(data) |
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with self.test_session() as sess: |
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num_boxes_output = sess.run(boxes.num_boxes()) |
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self.assertEquals(num_boxes_output, expected_num_boxes) |
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def test_transpose_coordinates(self): |
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boxes = [[10.0, 10.0, 20.0, 15.0], [0.2, 0.1, 0.5, 0.4]] |
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boxes = box_list.BoxList(tf.constant(boxes)) |
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boxes.transpose_coordinates() |
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expected_corners = [[10.0, 10.0, 15.0, 20.0], [0.1, 0.2, 0.4, 0.5]] |
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with self.test_session() as sess: |
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corners_out = sess.run(boxes.get()) |
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self.assertAllClose(corners_out, expected_corners) |
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def test_box_list_invalid_inputs(self): |
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data0 = tf.constant([[[0, 0, 1, 1], [3, 4, 5, 5]]], tf.float32) |
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data1 = tf.constant([[0, 0, 1], [1, 1, 2], [3, 4, 5]], tf.float32) |
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data2 = tf.constant([[0, 0, 1], [1, 1, 2], [3, 4, 5]], tf.int32) |
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with self.assertRaises(ValueError): |
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_ = box_list.BoxList(data0) |
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with self.assertRaises(ValueError): |
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_ = box_list.BoxList(data1) |
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with self.assertRaises(ValueError): |
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_ = box_list.BoxList(data2) |
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def test_num_boxes_static(self): |
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box_corners = [[10.0, 10.0, 20.0, 15.0], [0.2, 0.1, 0.5, 0.4]] |
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boxes = box_list.BoxList(tf.constant(box_corners)) |
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self.assertEquals(boxes.num_boxes_static(), 2) |
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self.assertEquals(type(boxes.num_boxes_static()), int) |
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def test_num_boxes_static_for_uninferrable_shape(self): |
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placeholder = tf.placeholder(tf.float32, shape=[None, 4]) |
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boxes = box_list.BoxList(placeholder) |
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self.assertEquals(boxes.num_boxes_static(), None) |
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def test_as_tensor_dict(self): |
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boxlist = box_list.BoxList( |
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tf.constant([[0.1, 0.1, 0.4, 0.4], [0.1, 0.1, 0.5, 0.5]], tf.float32)) |
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boxlist.add_field('classes', tf.constant([0, 1])) |
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boxlist.add_field('scores', tf.constant([0.75, 0.2])) |
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tensor_dict = boxlist.as_tensor_dict() |
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expected_boxes = [[0.1, 0.1, 0.4, 0.4], [0.1, 0.1, 0.5, 0.5]] |
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expected_classes = [0, 1] |
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expected_scores = [0.75, 0.2] |
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with self.test_session() as sess: |
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tensor_dict_out = sess.run(tensor_dict) |
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self.assertAllEqual(3, len(tensor_dict_out)) |
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self.assertAllClose(expected_boxes, tensor_dict_out['boxes']) |
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self.assertAllEqual(expected_classes, tensor_dict_out['classes']) |
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self.assertAllClose(expected_scores, tensor_dict_out['scores']) |
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def test_as_tensor_dict_with_features(self): |
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boxlist = box_list.BoxList( |
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tf.constant([[0.1, 0.1, 0.4, 0.4], [0.1, 0.1, 0.5, 0.5]], tf.float32)) |
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boxlist.add_field('classes', tf.constant([0, 1])) |
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boxlist.add_field('scores', tf.constant([0.75, 0.2])) |
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tensor_dict = boxlist.as_tensor_dict(['boxes', 'classes', 'scores']) |
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expected_boxes = [[0.1, 0.1, 0.4, 0.4], [0.1, 0.1, 0.5, 0.5]] |
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expected_classes = [0, 1] |
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expected_scores = [0.75, 0.2] |
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with self.test_session() as sess: |
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tensor_dict_out = sess.run(tensor_dict) |
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self.assertAllEqual(3, len(tensor_dict_out)) |
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self.assertAllClose(expected_boxes, tensor_dict_out['boxes']) |
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self.assertAllEqual(expected_classes, tensor_dict_out['classes']) |
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self.assertAllClose(expected_scores, tensor_dict_out['scores']) |
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def test_as_tensor_dict_missing_field(self): |
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boxlist = box_list.BoxList( |
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tf.constant([[0.1, 0.1, 0.4, 0.4], [0.1, 0.1, 0.5, 0.5]], tf.float32)) |
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boxlist.add_field('classes', tf.constant([0, 1])) |
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boxlist.add_field('scores', tf.constant([0.75, 0.2])) |
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with self.assertRaises(ValueError): |
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boxlist.as_tensor_dict(['foo', 'bar']) |
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if __name__ == '__main__': |
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tf.test.main() |
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