transform into mxnet tensor,
    subtract pixel size and transform to correct format
    :param im: [height, width, channel] in BGR
    :param mean: [RGB pixel mean]
    :param std: [RGB pixel std var]
    :return: [batch, channel, height, width]

def transform(im, mean, std):
    """
    transform into mxnet tensor,
    subtract pixel size and transform to correct format
    :param im: [height, width, channel] in BGR
    :param mean: [RGB pixel mean]
    :param std: [RGB pixel std var]
    :return: [batch, channel, height, width]
    """
    im_tensor = np.zeros((3, im.shape[0], im.shape[1]))
    for i in range(3):
        im_tensor[i, :, :] = (im[:, :, 2 - i] - mean[i]) / std[i]
    return im_tensor