def test_different_iou_threshold(self):
boxes = np.array([[0, 0, 20, 100], [0, 0, 20, 80],
[200, 200, 210, 300], [200, 200, 210, 250]],
dtype=float)
boxlist = np_box_list.BoxList(boxes)
boxlist.add_field('scores', np.array([0.9, 0.8, 0.7, 0.6]))
max_output_size = 4
iou_threshold = .4
expected_boxes = np.array([
[0, 0, 20, 100],
[200, 200, 210, 300],
],
dtype=float)
nms_boxlist = np_box_list_ops.non_max_suppression(
boxlist, max_output_size, iou_threshold)
self.assertAllClose(nms_boxlist.get(), expected_boxes)
iou_threshold = .5
expected_boxes = np.array(
[[0, 0, 20, 100], [200, 200, 210, 300], [200, 200, 210, 250]],
dtype=float)
nms_boxlist = np_box_list_ops.non_max_suppression(
boxlist, max_output_size, iou_threshold)
self.assertAllClose(nms_boxlist.get(), expected_boxes)
iou_threshold = .8
expected_boxes = np.array([[0, 0, 20, 100], [0, 0, 20, 80],
[200, 200, 210, 300], [200, 200, 210, 250]],
dtype=float)
nms_boxlist = np_box_list_ops.non_max_suppression(
boxlist, max_output_size, iou_threshold)
self.assertAllClose(nms_boxlist.get(), expected_boxes)
def test_with_no_scores_field(self):
boxlist = np_box_list.BoxList(self._boxes)
max_output_size = 3
iou_threshold = 0.5
with self.assertRaises(ValueError):
np_box_list_ops.non_max_suppression(boxlist, max_output_size,
iou_threshold)
def test_select_from_ten_indentical_boxes(self):
boxes = np.array(10 * [[0, 0, 1, 1]], dtype=float)
boxlist = np_box_list.BoxList(boxes)
boxlist.add_field('scores', np.array(10 * [0.8]))
iou_threshold = .5
max_output_size = 3
expected_boxes = np.array([[0, 0, 1, 1]], dtype=float)
nms_boxlist = np_box_list_ops.non_max_suppression(
boxlist, max_output_size, iou_threshold)
self.assertAllClose(nms_boxlist.get(), expected_boxes)
def test_select_at_most_two_from_three_clusters(self):
boxlist = np_box_list.BoxList(self._boxes)
boxlist.add_field('scores',
np.array([.9, .75, .6, .95, .5, .3], dtype=float))
max_output_size = 2
iou_threshold = 0.5
expected_boxes = np.array([[0, 10, 1, 11], [0, 0, 1, 1]], dtype=float)
nms_boxlist = np_box_list_ops.non_max_suppression(
boxlist, max_output_size, iou_threshold)
self.assertAllClose(nms_boxlist.get(), expected_boxes)
def test_nms_disabled_max_output_size_equals_three(self):
boxlist = np_box_list.BoxList(self._boxes)
boxlist.add_field('scores',
np.array([.9, .75, .6, .95, .2, .3], dtype=float))
max_output_size = 3
iou_threshold = 1. # No NMS
expected_boxes = np.array(
[[0, 10, 1, 11], [0, 0, 1, 1], [0, 0.1, 1, 1.1]], dtype=float)
nms_boxlist = np_box_list_ops.non_max_suppression(
boxlist, max_output_size, iou_threshold)
self.assertAllClose(nms_boxlist.get(), expected_boxes)