def test_with_no_scores_field(self):
boxlist = np_box_list_ops.copy_boxlist(boxlist=self.boxlist)
max_output_size = 3
iou_threshold = 0.5
with self.assertRaises(ValueError):
np_box_list_ops.non_max_suppression3d(boxlist, max_output_size,
iou_threshold)
def test_multiclass_nms(self):
boxlist = np_box_list_ops.copy_boxlist(boxlist=self.boxlist)
scores = np.array([[-0.2, 0.1, 0.5, -0.4, 0.3], [0.7, -0.7, 0.6, 0.2, -0.9],
[0.4, 0.34, -0.9, 0.2, 0.31], [0.1, 0.2, 0.3, 0.4, 0.5],
[-0.1, 0.1, -0.1, 0.1, -0.1], [0.3, 0.2, 0.1, 0.0, -0.1],
[0.0, 0.0, 0.0, 0.0, 0.0]],
dtype=np.float32)
boxlist.add_field('scores', scores)
boxlist_clean = np_box_list_ops.multi_class_non_max_suppression3d(
boxlist, score_thresh=0.25, iou_thresh=0.1, max_output_size=3)
scores_clean = boxlist_clean.get_field('scores')
classes_clean = boxlist_clean.get_field('classes')
expected_scores = np.array([0.7, 0.6, 0.5, 0.4, 0.34, 0.3])
expected_classes = np.array([0, 2, 4, 3, 1, 0])
expected_boxes = np.array(
[[_degree_to_radians(10.0), 1.0, 1.0, 1.0, 0.0, 0.0, 0.0],
[_degree_to_radians(10.0), 1.0, 1.0, 1.0, 0.0, 0.0, 0.0],
[_degree_to_radians(-10.0), 1.0, 1.0, 1.0, 0.0, 0.0, 0.0],
[_degree_to_radians(-10.0), 1.0, 1.0, 1.0, 0.0, 0.0, 0.0],
[_degree_to_radians(20.0), 1.0, 1.0, 1.0, 0.0, 0.0, 0.0],
[_degree_to_radians(10.0), 1.0, 1.0, 1.0, 10.0, 0.0, 0.0]],
dtype=np.float32)
self.assertAllClose(scores_clean, expected_scores)
self.assertAllClose(classes_clean, expected_classes)
self._compare_boxlist_with_boxes(boxlist_clean, expected_boxes)
def test_filter_scores_greater_than(self):
boxlist = np_box_list_ops.copy_boxlist(boxlist=self.boxlist)
boxlist.add_field('scores', np.array([0.8, 0.2, 0.7, 0.4], np.float32))
boxlist_greater = np_box_list_ops.filter_scores_greater_than3d(boxlist, 0.5)
expected_boxes_greater = np.array(
[[_degree_to_radians(0.1), 1.0, 3.0, 4.0, 1.0, 6.0, 8.0],
[_degree_to_radians(0.1), 1.0, 4.0, 3.0, 2.0, 7.0, 5.0]],
dtype=np.float32)
self._compare_boxlist_with_boxes(boxlist_greater, expected_boxes_greater)