解读opencv-＞tensorrt的数据排列方式

b(0,0), g(0,0), r(0,0), b(0,1), g(0,1), r(0,1),......, b(h-1,w-1), g(h-1,w-1), r(h-1,w-1)

b(0,0), b(0,1),..., b(h-1,w-1), g(0,0), g(0,1)..., g(h-1,w-1), r(0,0),r(0,1), ..., r(h-1,w-1)

std::vector<float> prepareImage(std::vector<cv::Mat> &vec_img) {
    std::vector<float> result(BATCH_SIZE * IMAGE_WIDTH * IMAGE_HEIGHT * INPUT_CHANNEL);
    float *data = result.data();
    int index = 0;
    for (const cv::Mat &src_img : vec_img)
    {
        if (!src_img.data)
            continue;
        float ratio = float(IMAGE_WIDTH) / float(src_img.cols) < float(IMAGE_HEIGHT) / float(src_img.rows) ? float(IMAGE_WIDTH) / float(src_img.cols) : float(IMAGE_HEIGHT) / float(src_img.rows);
        cv::Mat flt_img = cv::Mat::zeros(cv::Size(IMAGE_WIDTH, IMAGE_HEIGHT), CV_8UC3);
        cv::Mat rsz_img;
        cv::resize(src_img, rsz_img, cv::Size(), ratio, ratio);
        rsz_img.copyTo(flt_img(cv::Rect(0, 0, rsz_img.cols, rsz_img.rows)));
        flt_img.convertTo(flt_img, CV_32FC3, 1.0 / 255);

        //HWC TO CHW
        int channelLength = IMAGE_WIDTH * IMAGE_HEIGHT;
        std::vector<cv::Mat> split_img = {
                cv::Mat(IMAGE_HEIGHT, IMAGE_WIDTH, CV_32FC1, data + channelLength * (index + 2)),     // Mat与result数据区域共享
                cv::Mat(IMAGE_HEIGHT, IMAGE_WIDTH, CV_32FC1, data + channelLength * (index + 1)),
                cv::Mat(IMAGE_HEIGHT, IMAGE_WIDTH, CV_32FC1, data + channelLength * index)
        };
        index += 3;
        cv::split(flt_img, split_img);		// 通道分离
    }
    return result;	// result与split_img的数据共享
}

std::vector<float> prepareImage(std::vector<cv::Mat> &vec_img) {
    std::vector<float> result(BATCH_SIZE * INPUT_CHANNEL * IMAGE_HEIGHT * IMAGE_WIDTH);
    float* data = result.data();
    int index = 0;
    int offset = IMAGE_WIDTH * IMAGE_HEIGHT;
    // 数据预处理
    for(const auto &img:vec_img){
        float ratio = IMAGE_WIDTH/float(img.cols) < IMAGE_HEIGHT/float(img.rows) ? IMAGE_WIDTH/float(img.cols) : IMAGE_HEIGHT/float(img.rows);
        cv::Mat rsz_img;
        cv::resize(img, rsz_img, cv::Size(), ratio, ratio, 0);
        cv::Mat flt_img(IMAGE_HEIGHT, IMAGE_WIDTH, CV_8UC3, cv::Scalar(128, 128, 128));
        rsz_img.copyTo(flt_img(cv::Rect(0, 0, rsz_img.cols, rsz_img.rows)));
        
        // 手撕三通道，填入data
        int i = 0;
        for (int row = 0; row < IMAGE_HEIGHT; ++row) {
            uchar* uc_pixel = flt_img.data + row * flt_img.step;
            for (int col = 0; col < IMAGE_WIDTH; ++col) {
                data[index * 3 * IMAGE_HEIGHT * IMAGE_WIDTH + i] = (float)uc_pixel[2]/255.;
                data[index * 3 * IMAGE_HEIGHT * IMAGE_WIDTH + i + IMAGE_HEIGHT * IMAGE_WIDTH] = (float)uc_pixel[1]/255.;
                data[index * 3 * IMAGE_HEIGHT * IMAGE_WIDTH+ i + 2 * IMAGE_HEIGHT * IMAGE_WIDTH] = (float)uc_pixel[0]/255.;
                uc_pixel += 3;
                ++i;
            }
        }
        index++;
    }
    return result;
}