def test_box_iou_rotated_cpu(self):
from mmcv.ops import box_iou_rotated
np_boxes1 = np.asarray(
[[1.0, 1.0, 3.0, 4.0, 0.5], [2.0, 2.0, 3.0, 4.0, 0.6],
[7.0, 7.0, 8.0, 8.0, 0.4]],
dtype=np.float32)
np_boxes2 = np.asarray(
[[0.0, 2.0, 2.0, 5.0, 0.3], [2.0, 1.0, 3.0, 3.0, 0.5],
[5.0, 5.0, 6.0, 7.0, 0.4]],
dtype=np.float32)
np_expect_ious = np.asarray(
[[0.3708, 0.4351, 0.0000], [0.1104, 0.4487, 0.0424],
[0.0000, 0.0000, 0.3622]],
dtype=np.float32)
np_expect_ious_aligned = np.asarray([0.3708, 0.4487, 0.3622],
dtype=np.float32)
boxes1 = torch.from_numpy(np_boxes1)
boxes2 = torch.from_numpy(np_boxes2)
ious = box_iou_rotated(boxes1, boxes2)
assert np.allclose(ious.cpu().numpy(), np_expect_ious, atol=1e-4)
ious = box_iou_rotated(boxes1, boxes2, aligned=True)
assert np.allclose(ious.cpu().numpy(),
np_expect_ious_aligned,
atol=1e-4)
def check_installation():
"""Check whether mmcv-full has been installed successfully."""
np_boxes1 = np.asarray(
[[1.0, 1.0, 3.0, 4.0, 0.5], [2.0, 2.0, 3.0, 4.0, 0.6],
[7.0, 7.0, 8.0, 8.0, 0.4]],
dtype=np.float32)
np_boxes2 = np.asarray(
[[0.0, 2.0, 2.0, 5.0, 0.3], [2.0, 1.0, 3.0, 3.0, 0.5],
[5.0, 5.0, 6.0, 7.0, 0.4]],
dtype=np.float32)
boxes1 = torch.from_numpy(np_boxes1)
boxes2 = torch.from_numpy(np_boxes2)
# test mmcv-full with CPU ops
box_iou_rotated(boxes1, boxes2)
print('CPU ops were compiled successfully.')
# test mmcv-full with both CPU and CUDA ops
if torch.cuda.is_available():
boxes1 = boxes1.cuda()
boxes2 = boxes2.cuda()
box_iou_rotated(boxes1, boxes2)
print('CUDA ops were compiled successfully.')
else:
print('No CUDA runtime is found, skipping the checking of CUDA ops.')
def test_box_iou_rotated_iof_cuda(self):
from mmcv.ops import box_iou_rotated
np_boxes1 = np.asarray(
[[1.0, 1.0, 3.0, 4.0, 0.5], [2.0, 2.0, 3.0, 4.0, 0.6],
[7.0, 7.0, 8.0, 8.0, 0.4]],
dtype=np.float32)
np_boxes2 = np.asarray(
[[0.0, 2.0, 2.0, 5.0, 0.3], [2.0, 1.0, 3.0, 3.0, 0.5],
[5.0, 5.0, 6.0, 7.0, 0.4]],
dtype=np.float32)
np_expect_ious = np.asarray(
[[0.4959, 0.5306, 0.0000], [0.1823, 0.5420, 0.1832],
[0.0000, 0.0000, 0.4404]],
dtype=np.float32)
np_expect_ious_aligned = np.asarray([0.4959, 0.5420, 0.4404],
dtype=np.float32)
boxes1 = torch.from_numpy(np_boxes1).cuda()
boxes2 = torch.from_numpy(np_boxes2).cuda()
ious = box_iou_rotated(boxes1, boxes2, mode='iof')
assert np.allclose(ious.cpu().numpy(), np_expect_ious, atol=1e-4)
ious = box_iou_rotated(boxes1, boxes2, mode='iof', aligned=True)
assert np.allclose(ious.cpu().numpy(),
np_expect_ious_aligned,
atol=1e-4)
def test_box_iou_rotated_iof_cpu(self):
from mmcv.ops import box_iou_rotated
np_boxes1 = np.asarray(
[[1.0, 1.0, 3.0, 4.0, 0.5], [2.0, 2.0, 3.0, 4.0, 0.6],
[7.0, 7.0, 8.0, 8.0, 0.4]],
dtype=np.float32)
np_boxes2 = np.asarray(
[[0.0, 2.0, 2.0, 5.0, 0.3], [2.0, 1.0, 3.0, 3.0, 0.5],
[5.0, 5.0, 6.0, 7.0, 0.4]],
dtype=np.float32)
np_expect_ious = np.asarray(
[[0.4959, 0.5306, 0.0000], [0.1823, 0.5420, 0.1832],
[0.0000, 0.0000, 0.4404]],
dtype=np.float32)
np_expect_ious_aligned = np.asarray([0.4959, 0.5420, 0.4404],
dtype=np.float32)
boxes1 = torch.from_numpy(np_boxes1)
boxes2 = torch.from_numpy(np_boxes2)
# test cw angle definition
ious = box_iou_rotated(boxes1, boxes2, mode='iof')
assert np.allclose(ious.cpu().numpy(), np_expect_ious, atol=1e-4)
ious = box_iou_rotated(boxes1, boxes2, mode='iof', aligned=True)
assert np.allclose(ious.cpu().numpy(),
np_expect_ious_aligned,
atol=1e-4)
# test ccw angle definition
boxes1[..., -1] *= -1
boxes2[..., -1] *= -1
ious = box_iou_rotated(boxes1, boxes2, mode='iof', clockwise=False)
assert np.allclose(ious.cpu().numpy(), np_expect_ious, atol=1e-4)
ious = box_iou_rotated(boxes1,
boxes2,
mode='iof',
aligned=True,
clockwise=False)
assert np.allclose(ious.cpu().numpy(),
np_expect_ious_aligned,
atol=1e-4)
def check_installation():
"""Check whether mmcv-full has been installed successfully."""
np_boxes1 = np.asarray(
[[1.0, 1.0, 3.0, 4.0, 0.5], [2.0, 2.0, 3.0, 4.0, 0.6],
[7.0, 7.0, 8.0, 8.0, 0.4]],
dtype=np.float32)
np_boxes2 = np.asarray(
[[0.0, 2.0, 2.0, 5.0, 0.3], [2.0, 1.0, 3.0, 3.0, 0.5],
[5.0, 5.0, 6.0, 7.0, 0.4]],
dtype=np.float32)
boxes1 = torch.from_numpy(np_boxes1)
boxes2 = torch.from_numpy(np_boxes2)
# test mmcv-full with CPU ops
box_iou_rotated(boxes1, boxes2)
# test mmcv-full with both CPU and CUDA ops
if torch.cuda.is_available():
boxes1 = boxes1.cuda()
boxes2 = boxes2.cuda()
box_iou_rotated(boxes1, boxes2)
def test_box_iou_rotated_cuda(self):
from mmcv.ops import box_iou_rotated
np_boxes1 = np.asarray(
[[1.0, 1.0, 3.0, 4.0, 0.5], [2.0, 2.0, 3.0, 4.0, 0.6],
[7.0, 7.0, 8.0, 8.0, 0.4]],
dtype=np.float32)
np_boxes2 = np.asarray(
[[0.0, 2.0, 2.0, 5.0, 0.3], [2.0, 1.0, 3.0, 3.0, 0.5],
[5.0, 5.0, 6.0, 7.0, 0.4]],
dtype=np.float32)
np_expect_ious = np.asarray(
[[0.3708, 0.4351, 0.0000], [0.1104, 0.4487, 0.0424],
[0.0000, 0.0000, 0.3622]],
dtype=np.float32)
np_expect_ious_aligned = np.asarray([0.3708, 0.4487, 0.3622],
dtype=np.float32)
boxes1 = torch.from_numpy(np_boxes1).cuda()
boxes2 = torch.from_numpy(np_boxes2).cuda()
# test cw angle definition
ious = box_iou_rotated(boxes1, boxes2)
assert np.allclose(ious.cpu().numpy(), np_expect_ious, atol=1e-4)
ious = box_iou_rotated(boxes1, boxes2, aligned=True)
assert np.allclose(ious.cpu().numpy(),
np_expect_ious_aligned,
atol=1e-4)
# test ccw angle definition
boxes1[..., -1] *= -1
boxes2[..., -1] *= -1
ious = box_iou_rotated(boxes1, boxes2, clockwise=False)
assert np.allclose(ious.cpu().numpy(), np_expect_ious, atol=1e-4)
ious = box_iou_rotated(boxes1, boxes2, aligned=True, clockwise=False)
assert np.allclose(ious.cpu().numpy(),
np_expect_ious_aligned,
atol=1e-4)