Spaces:
Sleeping
Sleeping
File size: 6,647 Bytes
d7e58f0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 |
# 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)
|