halcon和opencv的图像互转（C/C++）

简介：opencv开源的计算机视觉库，halcon是商业的视觉库，opencv的一些算子在一般的生产环境下是够用的，但是在对算法速度、精度都要求更高的环境下就有些吃力了。最近在研究halcon，抽几个算子粗略测试一下，效果和速度确实很好，以后可能会在对算法速度要求比较高的地方部署，这里先记录一下opencv和halcon图像数据互转的方法。
参考：

• opencv的图像像素访问方式
• halcon(C++) vs2017配置

#include "HalconCpp.h"
#include<opencv2/core/core.hpp>
#include<opencv2/highgui/highgui.hpp>
#include <opencv2/opencv.hpp>

//using namespace cv;
using namespace std;
//using namespace HalconCpp;


cv::Mat HImageToMat(HalconCpp::HObject &H_img)
{
    cv::Mat cv_img;
    HalconCpp::HTuple channels, w, h;

    HalconCpp::ConvertImageType(H_img, &H_img, "byte");
    HalconCpp::CountChannels(H_img, &channels);

    if (channels.I() == 1)
    {
        HalconCpp::HTuple pointer;
        GetImagePointer1(H_img, &pointer, nullptr, &w, &h);
        int width = w.I(), height = h.I();
        int size = width * height;
        cv_img = cv::Mat::zeros(height, width, CV_8UC1);
        memcpy(cv_img.data, (void*)(pointer.L()), size);
    }

    else if (channels.I() == 3)
    {
        HalconCpp::HTuple pointerR, pointerG, pointerB;
        HalconCpp::GetImagePointer3(H_img, &pointerR, &pointerG, &pointerB, nullptr, &w, &h);
        int width = w.I(), height = h.I();
        int size = width * height;
        cv_img = cv::Mat::zeros(height, width, CV_8UC3);
        uchar* R = (uchar*)(pointerR.L());
        uchar* G = (uchar*)(pointerG.L());
        uchar* B = (uchar*)(pointerB.L());
        for (int i = 0; i < height; ++i)
        {
            uchar *p = cv_img.ptr<uchar>(i);
            for (int j = 0; j < width; ++j)
            {
                p[3 * j] = B[i * width + j];
                p[3 * j + 1] = G[i * width + j];
                p[3 * j + 2] = R[i * width + j];
            }
        }
    }
    return cv_img;
}

HalconCpp::HObject MatToHImage(cv::Mat& cv_img)
{
    HalconCpp::HObject H_img;

    if (cv_img.channels() == 1)
    {
        int height = cv_img.rows, width = cv_img.cols;
        int size = height * width;
        uchar *temp = new uchar[size];

        memcpy(temp, cv_img.data, size);
        HalconCpp::GenImage1(&H_img, "byte", width, height, (Hlong)(temp));

        delete[] temp;
    }
    else if (cv_img.channels() == 3)
    {
        int height = cv_img.rows, width = cv_img.cols;
        int size = height * width;
        uchar *B = new uchar[size];
        uchar *G = new uchar[size];
        uchar *R = new uchar[size];

        for (int i = 0; i < height; i++)
        {
            uchar *p = cv_img.ptr<uchar>(i);
            for (int j = 0; j < width; j++)
            {
                B[i * width + j] = p[3 * j];
                G[i * width + j] = p[3 * j + 1];
                R[i * width + j] = p[3 * j + 2];
            }
        }
        HalconCpp::GenImage3(&H_img, "byte", width, height, (Hlong)(R), (Hlong)(G), (Hlong)(B));

        delete[] R;
        delete[] G;
        delete[] B;
    }
    return H_img;
}


int main()
{
    HalconCpp::HImage H_img("claudia"); //从halcon的自带资源中读入一张图片，用于测试3通道图的转换时间
    HalconCpp::HImage H_gray;
    HalconCpp::Rgb1ToGray(H_img, &H_gray);  //转灰度图，可用于测试单通道图的转换时间

    double start, seconds = 0;
    start = (double)cv::getTickCount();    //计时开始

    cv::Mat cv_img = HImageToMat(H_gray);

    seconds = ((double)cv::getTickCount() - start) / cv::getTickFrequency() * 1000;
    cout << "HImage to Mat time:  " << seconds << " ms" << endl;

    start = (double)cv::getTickCount();   //计时开始

    HalconCpp::HImage H_img_new = MatToHImage(cv_img);

    seconds = ((double)cv::getTickCount() - start) / cv::getTickFrequency() * 1000;
    cout << "Mat to HImage time:  " << seconds << " ms" << endl;


    Hlong width, height;

    //显示初始图片，HImage类型
    H_img.GetImageSize(&width, &height);
    HalconCpp::HWindow w1(0, 0, width, height);
    H_img.DispObj(w1);

    //显示从HImage转到Mat的图片
    cv::imshow("opencv_img", cv_img);

    //显示从Mat转到HImage的图片
    H_img_new.GetImageSize(&width, &height);
    HalconCpp::HWindow w2(0, 0, width, height);
    H_img_new.DispObj(w2);
    w2.Click();
    w2.ClearWindow();
}