pytorch transform数据处理转c++问题

import torch
from PIL import Image
from torchvision import transforms

data_transform = transforms.Compose(
     [transforms.Resize(256),
      transforms.CenterCrop(224),
      transforms.ToTensor(),
      transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])])

 img = Image.open(img_path)
 img = data_transform(img)

cv::Mat ClsSixPrivate::processImage(cv::Mat &img) {
    int inW = img.cols;
    int inH = img.rows;
    cv::Mat croped_image;
    if (inW > inH)
    {
        int newWidth = 256 * inW / inH;
        cv::resize(img, img, cv::Size(newWidth, 256), 0, 0, cv::INTER_LINEAR);
        croped_image = img(cv::Rect((newWidth - 224) / 2, 16, 224, 224)).clone();
    }
    else {
        int newHeight= 256 * inH / inW;
        cv::resize(img, img, cv::Size(256, newHeight), 0, 0, cv::INTER_LINEAR);
        croped_image = img(cv::Rect(16, (newHeight - 224) / 2, 224, 224)).clone();
    }
    
    std::vector<float> mean_value{ 0.485, 0.456,0.406 };
    std::vector<float> std_value{ 0.229, 0.224, 0.225 }; 
    cv::Mat dst;
    std::vector<cv::Mat> rgbChannels(3);
    cv::split(croped_image, rgbChannels);

    for (auto i = 0; i < rgbChannels.size(); i++)
    {
        rgbChannels[i].convertTo(rgbChannels[i], CV_32FC1, 1.0 / (std_value[i] * 255.0), (0.0 - mean_value[i]) / std_value[i]);
    }

    cv::merge(rgbChannels, dst);
    return dst;
}