def test_center_region_assigner_with_ignore():
self = CenterRegionAssigner(
pos_scale=0.5,
neg_scale=1,
)
bboxes = torch.FloatTensor([
[0, 0, 10, 10],
[10, 10, 20, 20],
])
gt_bboxes = torch.FloatTensor([
[0, 0, 10, 10], # match bboxes[0]
[10, 10, 20, 20], # match bboxes[1]
])
gt_bboxes_ignore = torch.FloatTensor([
[0, 0, 10, 10], # match bboxes[0]
])
gt_labels = torch.LongTensor([1, 2])
assign_result = self.assign(bboxes,
gt_bboxes,
gt_bboxes_ignore=gt_bboxes_ignore,
gt_labels=gt_labels)
assert len(assign_result.gt_inds) == 2
assert len(assign_result.labels) == 2
expected_gt_inds = torch.LongTensor([-1, 2])
assert torch.all(assign_result.gt_inds == expected_gt_inds)
def test_center_region_assigner_with_empty_bboxes():
self = CenterRegionAssigner(
pos_scale=0.5,
neg_scale=1,
)
bboxes = torch.empty((0, 4)).float()
gt_bboxes = torch.FloatTensor([
[0, 0, 10, 10], # match bboxes[0]
[10, 10, 20, 20], # match bboxes[1]
])
gt_labels = torch.LongTensor([1, 2])
assign_result = self.assign(bboxes, gt_bboxes, gt_labels=gt_labels)
assert assign_result.gt_inds is None or assign_result.gt_inds.numel() == 0
assert assign_result.labels is None or assign_result.labels.numel() == 0
def test_center_region_assigner_with_empty_gts():
self = CenterRegionAssigner(
pos_scale=0.5,
neg_scale=1,
)
bboxes = torch.FloatTensor([
[0, 0, 10, 10],
[10, 10, 20, 20],
])
gt_bboxes = torch.empty((0, 4)).float()
gt_labels = torch.empty((0, )).long()
assign_result = self.assign(bboxes, gt_bboxes, gt_labels=gt_labels)
assert len(assign_result.gt_inds) == 2
expected_gt_inds = torch.LongTensor([0, 0])
assert torch.all(assign_result.gt_inds == expected_gt_inds)
def test_center_region_assigner():
self = CenterRegionAssigner(pos_scale=0.3, neg_scale=1)
bboxes = torch.FloatTensor([[0, 0, 10, 10], [10, 10, 20, 20], [8, 8, 9,
9]])
gt_bboxes = torch.FloatTensor([
[0, 0, 11, 11], # match bboxes[0]
[10, 10, 20, 20], # match bboxes[1]
[4.5, 4.5, 5.5, 5.5], # match bboxes[0] but area is too small
[0, 0, 10, 10], # match bboxes[1] and has a smaller area than gt[0]
])
gt_labels = torch.LongTensor([2, 3, 4, 5])
assign_result = self.assign(bboxes, gt_bboxes, gt_labels=gt_labels)
assert len(assign_result.gt_inds) == 3
assert len(assign_result.labels) == 3
expected_gt_inds = torch.LongTensor([4, 2, 0])
assert torch.all(assign_result.gt_inds == expected_gt_inds)
shadowed_labels = assign_result.get_extra_property('shadowed_labels')
# [8, 8, 9, 9] in the shadowed region of [0, 0, 11, 11] (label: 2)
assert torch.any(shadowed_labels == torch.LongTensor([[2, 2]]))
# [8, 8, 9, 9] in the shadowed region of [0, 0, 10, 10] (label: 5)
assert torch.any(shadowed_labels == torch.LongTensor([[2, 5]]))
# [0, 0, 10, 10] is already assigned to [4.5, 4.5, 5.5, 5.5].
# Therefore, [0, 0, 11, 11] (label: 2) is shadowed
assert torch.any(shadowed_labels == torch.LongTensor([[0, 2]]))