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test_box_iou_rotated.py 4.65 KB
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import numpy as np
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import pytest
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import torch


class TestBoxIoURotated(object):
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    def test_box_iou_rotated_cpu(self):
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        from mmcv.ops import box_iou_rotated
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        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)

    @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()

        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)
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        assert np.allclose(
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            ious.cpu().numpy(), np_expect_ious_aligned, atol=1e-4)
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    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)

        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)

    @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()

        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)