def METHOD_NAME(bounding_boxes, img, size=24):
    """Cut out boxes from the image.
    Arguments:
        bounding_boxes: a float numpy array of shape [n, 5].
        img: an instance of PIL.Image.
        size: an integer, size of cutouts.
    Returns:
        a float numpy array of shape [n, 3, size, size].
    """
    num_boxes = len(bounding_boxes)
    width, height = img.size
    [dy, edy, dx, edx, y, ey, x, ex, w,
     h] = correct_bboxes(bounding_boxes, width, height)
    img_boxes = np.zeros((num_boxes, 3, size, size), 'float32')
    for i in range(num_boxes):
        img_box = np.zeros((h[i], w[i], 3), 'uint8')
        img_array = np.asarray(img, 'uint8')
        img_box[dy[i]:(edy[i] + 1), dx[i]:(edx[i] + 1), :] =\
            img_array[y[i]:(ey[i] + 1), x[i]:(ex[i] + 1), :]
        # resize
        img_box = Image.fromarray(img_box)
        img_box = img_box.resize((size, size), Image.BILINEAR)
        img_box = np.asarray(img_box, 'float32')
        img_boxes[i, :, :, :] = _preprocess(img_box)
    return img_boxes