python下安装opencv库

一时失言乱红尘 2022-05-14 07:08 421阅读 0赞

参考链接：

[https://blog.csdn.net/Toby\_Cho/article/details/81001382][https_blog.csdn.net_Toby_Cho_article_details_81001382]

opencv库的whl文件下载链接：

[https://www.lfd.uci.edu/~gohlke/pythonlibs/\#opencv][https_www.lfd.uci.edu_gohlke_pythonlibs_opencv]

对于opencv3.5，64位系统，下载如下红框文件即可：

![70][]

安装命令及安装成功截图：

![70 1][]

此时再pycharm中也可以用opencv库了！

实例参考：[https://blog.csdn.net/u014365862/article/details/78863756][https_blog.csdn.net_u014365862_article_details_78863756]

[http://www.cnblogs.com/herd/p/9205579.html][http_www.cnblogs.com_herd_p_9205579.html] 未成功

[https://blog.csdn.net/xiangxianghehe/article/details/78581251][https_blog.csdn.net_xiangxianghehe_article_details_78581251] 成功

#include <opencv2/opencv.hpp>
    #include <opencv2/core/core.hpp>
    #include <opencv2/highgui/highgui.hpp>
    #include <opencv2/imgproc/imgproc.hpp>
    
    using namespace std;
    using namespace cv;//包含cv命名空间
    
    
    int main()
    {
        //char *origin="Original";
        //char *window="Image";
        //char *str="F:\\opencv\\daily_learn\\3.jpg";
        namedWindow("Original",1);
        namedWindow("Image",1);
        Mat image=imread("F:\\opencv\\daily_learn\\3.jpg");
        if(!image.data)
        {
            cout<<"图像载入出现问题"<<endl;
            return 0;
        }
        Mat roi=image(Rect(20,20,20,20));
        Mat hsvImg;
        cvtColor(image, hsvImg, CV_BGR2HSV); //将图像转换到HSV颜色空间
        //分离HSV空间，v[0]为H色调，v[1]为S饱和度，v[2]为v灰度
        vector<Mat> v;
        split(hsvImg,v);
        Mat roiH=v[0](Rect(20,20,20,20));
        Mat roiS=v[1](Rect(20,20,20,20));
        int SumH=0;
        int SumS=0;
        int avgH, avgS;//蓝底的平均色调和平均饱和度
        //取一块蓝色背景，计算出它的平均色调和平均饱和度
        for(int i=0; i<20; i++)
        {
            for(int j=0; j<20; j++)
            {
                /*SumH=SumH+roiH(i,j);*/
                SumH=int(roiH.at<uchar>(j,i))+SumH;
                SumS=int(roiS.at<uchar>(j,i))+SumS;
            }
        }
        avgH=SumH/400;
        avgS=SumS/400;
        //遍历整个图像
        int nl=hsvImg.rows;
        int nc=hsvImg.cols;
        int step=10;
        for(int j=0; j<nl; j++)
        {
            for(int i=0; i<nc; i++)
            {
                //以H.S两个通道做阈值分割，把蓝色替换成红色
                if((v[0].at<uchar>(j,i))<=(avgH+5) && v[0].at<uchar>(j,i)>=(avgH-5)
                   &&(v[1].at<uchar>(j,i))<=(avgS+40) && v[1].at<uchar>(j,i)>=(avgS-40))
                {
                    //cout<<int(v[0].at<uchar>(j,i))<<endl;
                    //红色底
                    //v[0].at<uchar>(j,i)=0;
                    //白色底
                    v[0].at<uchar>(j,i)=0;
                    v[1].at<uchar>(j,i)=0;  //V[0]和V[1]全调成0就是变成白色
                    //绿色底
                    //v[0].at<uchar>(j,i)=60;
                    //蓝色底
                    //v[0].at<uchar>(j,i)=120;
                    /*cout<<int(v[0].at<uchar>(j,i))<<endl;*/
                }
            }
        }
        Mat finImg;
        merge(v,finImg);
        Mat rgbImg;
        cvtColor(finImg,rgbImg, CV_HSV2BGR); //将图像转换回RGB空间
        imshow("Original",image);
        imshow("Image",rgbImg);
        //加个滤波把边缘部分的值滤掉（此处应该用低通滤波器，但感觉不太好，还是不用了。）
        Mat result;
        GaussianBlur(rgbImg,result,Size(3,3),0.5);
        imshow("Image",result);
        imwrite("new.jpg",result);
        waitKey(0);
        //system("pause");
        return 0;
    }

可以实现！

[https_blog.csdn.net_Toby_Cho_article_details_81001382]: https://blog.csdn.net/Toby_Cho/article/details/81001382
[https_www.lfd.uci.edu_gohlke_pythonlibs_opencv]: https://www.lfd.uci.edu/~gohlke/pythonlibs/#opencv
[70]: /images/20220514/5a727667f48941029b30b9c72210b65a.png
[70 1]: /images/20220514/93af3ac63ee249d7a07589458915434c.png
[https_blog.csdn.net_u014365862_article_details_78863756]: https://blog.csdn.net/u014365862/article/details/78863756
[http_www.cnblogs.com_herd_p_9205579.html]: http://www.cnblogs.com/herd/p/9205579.html
[https_blog.csdn.net_xiangxianghehe_article_details_78581251]: https://blog.csdn.net/xiangxianghehe/article/details/78581251