def intrinsics_like(focal: float, input: Tensor) -> Tensor:
    r"""Return a 3x3 intrinsics matrix, with same size as the input.

    The center of projection will be based in the input image size.

    Args:
        focal: the focal length for the camera matrix.
        input: image tensor that will determine the batch size and image height
          and width. It is assumed to be a tensor in the shape of :math:`(B, C, H, W)`.

    Returns:
        The camera matrix with the shape of :math:`(B, 3, 3)`.

    """
    if len(input.shape) != 4:
        raise AssertionError(input.shape)
    if focal <= 0:
        raise AssertionError(focal)

    _, _, H, W = input.shape

    intrinsics = eye_like(3, input)
    intrinsics[..., 0, 0] *= focal
    intrinsics[..., 1, 1] *= focal
    intrinsics[..., 0, 2] += 1.0 * W / 2
    intrinsics[..., 1, 2] += 1.0 * H / 2
    return intrinsics
Return a 3x3 intrinsics matrix, with same size as the input.

    The center of projection will be based in the input image size.

    Args:
        focal: the focal length for the camera matrix.
        input: image tensor that will determine the batch size and image height
          and width. It is assumed to be a tensor in the shape of :math:`(B, C, H, W)`.

    Returns:
        The camera matrix with the shape of :math:`(B, 3, 3)`.

    
kornia/geometry/epipolar/projection.py