def test_iou_ignore_index(pred, target, ignore_index, num_classes, reduction, expected):
iou_val = iou(
preds=tensor(pred),
target=tensor(target),
ignore_index=ignore_index,
num_classes=num_classes,
reduction=reduction,
)
assert torch.allclose(iou_val, tensor(expected).to(iou_val))
def test_iou_absent_score(pred, target, ignore_index, absent_score, num_classes, expected):
iou_val = iou(
preds=tensor(pred),
target=tensor(target),
ignore_index=ignore_index,
absent_score=absent_score,
num_classes=num_classes,
reduction='none',
)
assert torch.allclose(iou_val, tensor(expected).to(iou_val))
def test_iou(half_ones, reduction, ignore_index, expected):
pred = (torch.arange(120) % 3).view(-1, 1)
target = (torch.arange(120) % 3).view(-1, 1)
if half_ones:
pred[:60] = 1
iou_val = iou(
pred=pred,
target=target,
ignore_index=ignore_index,
reduction=reduction,
)
assert torch.allclose(iou_val, expected, atol=1e-9)