<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def center_crop(src, size, interp=2):
 """Crops the image `src` to the given `size` by trimming on all four sides and preserving the center of the image. Upsamples if `src` is smaller than `size`. .. note:: This requires MXNet to be compiled with USE_OPENCV. Parameters src : NDArray Binary source image data. size : list or tuple of int The desired output image size. interp : int, optional, default=2 Interpolation method. See resize_short for details. Returns ------- NDArray The cropped image. Tuple (x, y, width, height) where x, y are the positions of the crop in the original image and width, height the dimensions of the crop. Example ------- <NDArray 2321x3482x3 @cpu(0)> <NDArray 500x1000x3 @cpu(0)> (1241, 910, 1000, 500) """


    h, w, _ = src.shape
    new_w, new_h = scale_down((w, h), size)

    x0 = int((w - new_w) / 2)
    y0 = int((h - new_h) / 2)

    out = fixed_crop(src, x0, y0, new_w, new_h, size, interp)
    return out, (x0, y0, new_w, new_h)