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import pytest
import torch
from mmdet.core.bbox.coder import (DeltaXYWHBBoxCoder, 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
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
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