(point, in_size, out_size)
return out_point
Adapt point coordinates to the rescaled image space.

    Args:
        point (~numpy.ndarray or list of arrays): See the table below.
        in_size (tuple): A tuple of length 2. The height and the width
            of the image before resized.
        out_size (tuple): A tuple of length 2. The height and the width
            of the image after resized.

    .. csv-table::
        :header: name, shape, dtype, format

        :obj:`point`, ":math:`(R, K, 2)` or :math:`[(K, 2)]`", \
        :obj:`float32`, ":math:`(y, x)`"

    Returns:
        ~numpy.ndarray or list of arrays:
        Points rescaled according to the given image shapes.
Adapt point coordinates to the rescaled image space.
Adapt point coordinates to the rescaled image space .
def resize_point(point, in_size, out_size):
    """Adapt point coordinates to the rescaled image space.

    Args:
        point (~numpy.ndarray or list of arrays): See the table below.
        in_size (tuple): A tuple of length 2. The height and the width
            of the image before resized.
        out_size (tuple): A tuple of length 2. The height and the width
            of the image after resized.

    .. csv-table::
        :header: name, shape, dtype, format

        :obj:`point`, ":math:`(R, K, 2)` or :math:`[(K, 2)]`", \
        :obj:`float32`, ":math:`(y, x)`"

    Returns:
        ~numpy.ndarray or list of arrays:
        Points rescaled according to the given image shapes.

    """
    y_scale = float(out_size[0]) / in_size[0]
    x_scale = float(out_size[1]) / in_size[1]
    if isinstance(point, np.ndarray):
        out_point = point.copy()
        out_point[:, :, 0] = y_scale * point[:, :, 0]
        out_point[:, :, 1] = x_scale * point[:, :, 1]
    else:
        out_point = []
        for pnt in point:
            out_pnt = pnt.copy()
            out_pnt[:, 0] = y_scale * pnt[:, 0]
            out_pnt[:, 1] = x_scale * pnt[:, 1]
            out_point.append(out_pnt)
    return out_point
def resize_point ( point , in_size , out_size ) : y_scale = float ( out_size [ 0 ] ) / in_size [ 0 ] x_scale = float ( out_size [ 1 ] ) / in_size [ 1 ] if isinstance ( point , np . ndarray ) : out_point = point . copy ( ) out_point [ : , : , 0 ] = y_scale * point [ : , : , 0 ] out_point [ : , : , 1 ] = x_scale * point [ : , : , 1 ] else : out_point = [ ] for pnt in point : out_pnt = pnt . copy ( ) out_pnt [ : , 0 ] = y_scale * pnt [ : , 0 ] out_pnt [ : , 1 ] = x_scale * pnt [ : , 1 ] out_point . append ( out_pnt ) return out_point