Wrong IoU calculation when corners are smaller than 0 about rotated_iou

[Eralien]

I have a simple solution for the corners problem: simply add a translation to all boxes if any of their corners coordinates is negative.

def cal_iou(box1: torch.Tensor, box2: torch.Tensor):
    """calculate iou
    Args:
        box1 (torch.Tensor): (B, N, 5) with x, y, w, h, alpha
        box2 (torch.Tensor): (B, N, 5) with x, y, w, h, alpha

    Returns:
        iou (torch.Tensor): (B, N)
        corners1 (torch.Tensor): (B, N, 4, 2)
        corners1 (torch.Tensor): (B, N, 4, 2)
        U (torch.Tensor): (B, N) area1 + area2 - inter_area
    """
    corners1 = box2corners_th(box1)
    corners2 = box2corners_th(box2)

    # calculate the min corner coordinates
    corners_min = torch.minimum(corners1, corners2).amin(-2) - 1e-5   # eps
    # if any element is negative, translate all coordinates to positive number
    if corners_min.lt(0).any():
        corners1_positive = corners1 - corners_min
        corners2_positive = corners2 - corners_min
        inter_area, _ = oriented_box_intersection_2d(corners1_positive, corners2_positive)    # (B, N)
    else:
        # if not, directly calculate the intersection area
        inter_area, _ = oriented_box_intersection_2d(corners1, corners2)    # (B, N)
    area1 = box1[:, :, 2] * box1[:, :, 3]
    area2 = box2[:, :, 2] * box2[:, :, 3]
    u = area1 + area2 - inter_area
    iou = inter_area / u
    return iou, corners1, corners2, u

I tested the results against the one implemented in detectron2, and the results difference for 1000 random tests are within 1e-3.

[rubbish001]

代码有问题，不知道怎么改，求作者更新代码

[lilanxiao]

hi, thank you for the issue and workaround.
I've just updated my code in the debug branch. I think the new version is probably more stable.
Please let me know if the problem persists.

[Eralien]

hi, thank you for the issue and workaround. I've just updated my code in the debug branch. I think the new version is probably more stable. Please let me know if the problem persists.

Thanks! Will test soon.

[rubbish001]

还是会出现nan

[xiazhiyi99]

same problem
Can we simply add a constant big value to the corners at the beginning like this?

def cal_iou(box1:Tensor, box2:Tensor):
    corners1 = box2corners_th(box1) + 100
    corners2 = box2corners_th(box2) + 100
    ...

I tried it and it seems fine.