dd2907ed70a9f29ecbe2fba75de735e96daae3a2,mmdet/ops/nms/nms_wrapper.py,,nms,#Any#Any#Any#,9

Before Change

        inds = (gpu_nms(dets, thresh, device_id=device_id)
                if device_id is not None else cpu_nms(dets, thresh))

    if tensor_device:
        return torch.Tensor(inds).long().to(tensor_device)
    else:
        return np.array(inds, dtype=np.int)


def soft_nms(dets, Nt=0.3, method=1, sigma=0.5, min_score=0):
    if isinstance(dets, torch.Tensor):
        _dets = dets.detach().cpu().numpy()
    else:

After Change

        dets_np = dets.detach().cpu().numpy()
    elif isinstance(dets, np.ndarray):
        is_tensor = False
        dets_np = dets
    else:
        raise TypeError(
            "dets must be either a Tensor or numpy array, but got {}".format(
                type(dets)))

    if dets_np.shape[0] == 0:
        inds = []
    else:
        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

Instances