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| # Copyright (c) OpenMMLab. All rights reserved. | |
| import pytest | |
| import torch | |
| from mmdet.core.bbox.coder import (DeltaXYWHBBoxCoder, DistancePointBBoxCoder, | |
| TBLRBBoxCoder, YOLOBBoxCoder) | |
| def test_yolo_bbox_coder(): | |
| coder = YOLOBBoxCoder() | |
| bboxes = torch.Tensor([[-42., -29., 74., 61.], [-10., -29., 106., 61.], | |
| [22., -29., 138., 61.], [54., -29., 170., 61.]]) | |
| pred_bboxes = torch.Tensor([[0.4709, 0.6152, 0.1690, -0.4056], | |
| [0.5399, 0.6653, 0.1162, -0.4162], | |
| [0.4654, 0.6618, 0.1548, -0.4301], | |
| [0.4786, 0.6197, 0.1896, -0.4479]]) | |
| grid_size = 32 | |
| expected_decode_bboxes = torch.Tensor( | |
| [[-53.6102, -10.3096, 83.7478, 49.6824], | |
| [-15.8700, -8.3901, 114.4236, 50.9693], | |
| [11.1822, -8.0924, 146.6034, 50.4476], | |
| [41.2068, -8.9232, 181.4236, 48.5840]]) | |
| assert expected_decode_bboxes.allclose( | |
| coder.decode(bboxes, pred_bboxes, grid_size)) | |
| def test_delta_bbox_coder(): | |
| coder = DeltaXYWHBBoxCoder() | |
| rois = torch.Tensor([[0., 0., 1., 1.], [0., 0., 1., 1.], [0., 0., 1., 1.], | |
| [5., 5., 5., 5.]]) | |
| deltas = torch.Tensor([[0., 0., 0., 0.], [1., 1., 1., 1.], | |
| [0., 0., 2., -1.], [0.7, -1.9, -0.5, 0.3]]) | |
| expected_decode_bboxes = torch.Tensor([[0.0000, 0.0000, 1.0000, 1.0000], | |
| [0.1409, 0.1409, 2.8591, 2.8591], | |
| [0.0000, 0.3161, 4.1945, 0.6839], | |
| [5.0000, 5.0000, 5.0000, 5.0000]]) | |
| out = coder.decode(rois, deltas, max_shape=(32, 32)) | |
| assert expected_decode_bboxes.allclose(out, atol=1e-04) | |
| out = coder.decode(rois, deltas, max_shape=torch.Tensor((32, 32))) | |
| assert expected_decode_bboxes.allclose(out, atol=1e-04) | |
| batch_rois = rois.unsqueeze(0).repeat(2, 1, 1) | |
| batch_deltas = deltas.unsqueeze(0).repeat(2, 1, 1) | |
| batch_out = coder.decode(batch_rois, batch_deltas, max_shape=(32, 32))[0] | |
| assert out.allclose(batch_out) | |
| batch_out = coder.decode( | |
| batch_rois, batch_deltas, max_shape=[(32, 32), (32, 32)])[0] | |
| assert out.allclose(batch_out) | |
| # test max_shape is not equal to batch | |
| with pytest.raises(AssertionError): | |
| coder.decode( | |
| batch_rois, batch_deltas, max_shape=[(32, 32), (32, 32), (32, 32)]) | |
| rois = torch.zeros((0, 4)) | |
| deltas = torch.zeros((0, 4)) | |
| out = coder.decode(rois, deltas, max_shape=(32, 32)) | |
| assert rois.shape == out.shape | |
| # test add_ctr_clamp | |
| coder = DeltaXYWHBBoxCoder(add_ctr_clamp=True, ctr_clamp=2) | |
| rois = torch.Tensor([[0., 0., 6., 6.], [0., 0., 1., 1.], [0., 0., 1., 1.], | |
| [5., 5., 5., 5.]]) | |
| deltas = torch.Tensor([[1., 1., 2., 2.], [1., 1., 1., 1.], | |
| [0., 0., 2., -1.], [0.7, -1.9, -0.5, 0.3]]) | |
| expected_decode_bboxes = torch.Tensor([[0.0000, 0.0000, 27.1672, 27.1672], | |
| [0.1409, 0.1409, 2.8591, 2.8591], | |
| [0.0000, 0.3161, 4.1945, 0.6839], | |
| [5.0000, 5.0000, 5.0000, 5.0000]]) | |
| out = coder.decode(rois, deltas, max_shape=(32, 32)) | |
| assert expected_decode_bboxes.allclose(out, atol=1e-04) | |
| def test_tblr_bbox_coder(): | |
| coder = TBLRBBoxCoder(normalizer=15.) | |
| rois = torch.Tensor([[0., 0., 1., 1.], [0., 0., 1., 1.], [0., 0., 1., 1.], | |
| [5., 5., 5., 5.]]) | |
| deltas = torch.Tensor([[0., 0., 0., 0.], [1., 1., 1., 1.], | |
| [0., 0., 2., -1.], [0.7, -1.9, -0.5, 0.3]]) | |
| expected_decode_bboxes = torch.Tensor([[0.5000, 0.5000, 0.5000, 0.5000], | |
| [0.0000, 0.0000, 12.0000, 13.0000], | |
| [0.0000, 0.5000, 0.0000, 0.5000], | |
| [5.0000, 5.0000, 5.0000, 5.0000]]) | |
| out = coder.decode(rois, deltas, max_shape=(13, 12)) | |
| assert expected_decode_bboxes.allclose(out) | |
| out = coder.decode(rois, deltas, max_shape=torch.Tensor((13, 12))) | |
| assert expected_decode_bboxes.allclose(out) | |
| batch_rois = rois.unsqueeze(0).repeat(2, 1, 1) | |
| batch_deltas = deltas.unsqueeze(0).repeat(2, 1, 1) | |
| batch_out = coder.decode(batch_rois, batch_deltas, max_shape=(13, 12))[0] | |
| assert out.allclose(batch_out) | |
| batch_out = coder.decode( | |
| batch_rois, batch_deltas, max_shape=[(13, 12), (13, 12)])[0] | |
| assert out.allclose(batch_out) | |
| # test max_shape is not equal to batch | |
| with pytest.raises(AssertionError): | |
| coder.decode(batch_rois, batch_deltas, max_shape=[(13, 12)]) | |
| rois = torch.zeros((0, 4)) | |
| deltas = torch.zeros((0, 4)) | |
| out = coder.decode(rois, deltas, max_shape=(32, 32)) | |
| assert rois.shape == out.shape | |
| def test_distance_point_bbox_coder(): | |
| coder = DistancePointBBoxCoder() | |
| points = torch.Tensor([[74., 61.], [-29., 106.], [138., 61.], [29., 170.]]) | |
| gt_bboxes = torch.Tensor([[74., 61., 75., 62.], [0., 104., 0., 112.], | |
| [100., 90., 100., 120.], [0., 120., 100., 120.]]) | |
| expected_distance = torch.Tensor([[0., 0., 1., 1.], [0., 2., 29., 6.], | |
| [38., 0., 0., 50.], [29., 50., 50., 0.]]) | |
| out_distance = coder.encode(points, gt_bboxes, max_dis=50, eps=0) | |
| assert expected_distance.allclose(out_distance) | |
| distance = torch.Tensor([[0., 0, 1., 1.], [1., 2., 10., 6.], | |
| [22., -29., 138., 61.], [54., -29., 170., 61.]]) | |
| out_bbox = coder.decode(points, distance, max_shape=(120, 100)) | |
| assert gt_bboxes.allclose(out_bbox) | |