e421e832883241bd7831bf77dc31d5fb31d7da58,mmdet/ops/nms/nms_wrapper.py,,nms,#Any#Any#Any#,9

Before Change

        inds = (gpu_nms(dets_np, iou_thr, device_id=device_id)
                if device_id is not None else cpu_nms(dets_np, iou_thr))

    if is_tensor:
        inds = dets.new_tensor(inds, dtype=torch.long)
    else:
        inds = np.array(inds, dtype=np.int64)
    return dets[inds, :], inds


def soft_nms(dets, iou_thr, method="linear", sigma=0.5, min_score=1e-3):

After Change

    elif isinstance(dets, np.ndarray):
        is_numpy = True
        device = "cpu" if device_id is None else "cuda:{}".format(device_id)
        dets_th = torch.from_numpy(dets).to(device)
    else:
        raise TypeError(
            "dets must be either a Tensor or numpy array, but got {}".format(
                type(dets)))

    // execute cpu or cuda nms
    if dets_th.shape[0] == 0:
        inds = dets_th.new_zeros(0, dtype=torch.long)
    else:
        if dets_th.is_cuda:
            inds = nms_cuda.nms(dets_th, iou_thr)
        else:
            inds = nms_cpu.nms(dets_th, iou_thr)

    if is_numpy:
        inds = inds.cpu().numpy()
    return dets[inds, :], inds


def soft_nms(dets, iou_thr, method="linear", sigma=0.5, min_score=1e-3):

Instances