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([127, 127, 127]).astype('float32')
    stddev_vec = np.array([0.0078, 0.0078, 0.0078]).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