def METHOD_NAME(img, input_shape):
    img = cv2.resize(img, input_shape,
                     interpolation=cv2.INTER_LINEAR).astype(np.uint8)
    img_data = np.array(img)
    img_data = np.transpose(img_data, (2, 0, 1))
    img_data = np.expand_dims(img_data, 0)
    mean_vec = np.array([123.675,116.28,103.53]).astype('float32')
    stddev_vec = np.array([0.0171,0.0175,0.0174]).astype('float32')
    norm_img_data = np.zeros(img_data.shape).astype('float32')
    for i in range(img_data.shape[1]):
        norm_img_data[:, i, :, :] = (
            img_data[:, i, :, :] - mean_vec[i]) * stddev_vec[i]
    return norm_img_data