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# Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import pytest
import torch
class TestBoxIoURotated:
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)
# 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)
@pytest.mark.skipif(
not torch.cuda.is_available(), reason='requires CUDA support')
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)
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)
@pytest.mark.skipif(
not torch.cuda.is_available(), reason='requires CUDA support')
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()
# 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)
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