【EmguCV】C#实现HOG与SVM的几个问题

 

关于SVM中的alpha、rho向量

由于EmguCV封装的更加彻底，在C#中并不能跟C++一样通过重载获得这两个中间变量

//继承自CvSVM的类，因为生成setSVMDetector()中用到的检测子参数时，需要用到训练好的SVM的decision_func参数，  

//但通过查看CvSVM源码可知decision_func参数是protected类型变量，无法直接访问到，只能继承之后通过函数访问  

class MySVM : public CvSVM  

{  

public:  

    //获得SVM的决策函数中的alpha数组  

    double * get_alpha_vector()  

    {  

        return this->decision_func->alpha;  

    }  

  

    //获得SVM的决策函数中的rho参数,即偏移量  

    float get_rho()  

    {  

        return this->decision_func->rho;  

    }  

};

见C++实例：训练SVM分类器进行HOG行人检测 http://blog.csdn.net/pb09013037/article/details/41256945）

---

为了获取这两个变量用于自定义HOG检测子，暂时想到的几种办法：

1、C#读取生成的XML文件

分类器训练好后一般需要进行保存，方便直接预测

SVM svm = new SVM();

bool trained = svm.Train(my_train.sampleFeatureMat, my_train.sampleLabelMat, null, null, p);

svm.Save(@"../HOG_SVM.xml");

这里给出我的C#提取SVM参数方式：

（只用于提取训练目标为1与-1两类的XML文件，如果类型大于2，则有多个rho与alpha数组，需要进一步组合）

using System;

using System.Text;

using System.Xml;

using System.IO;





namespace HOG_SVM

{

    class GetData

    {

        public double[] alpha;

        public double rho;



        XmlDocument doc;        

        StreamReader sr;

        int sv_count;

        string alpha_str;



        public GetData()

        {

            doc = new XmlDocument();

            doc.Load(Form1.LOAD_PATH);

            XmlNode nodes = doc.DocumentElement;

            get_rho(nodes);

            getAlpha_str(nodes);

            getSv_count(nodes);

            getAlpha(); 

        }



        public void get_rho(XmlNode nodes)

        {

            if (nodes.HasChildNodes)

            {

                foreach (XmlNode node in nodes.ChildNodes)

                {

                    if (nodes.Name == "rho")

                    {

                        rho = Double.Parse(nodes.InnerText);

                        return;

                    }

                    get_rho(node);

                }

            }

        }



        public void getAlpha_str(XmlNode nodes)

        {

            if (nodes.HasChildNodes)

            {

                foreach (XmlNode node in nodes.ChildNodes)

                {

                    if (nodes.Name == "alpha")

                    {

                        //sr = new StreamReader(new Stream(nodes.InnerText));

                        alpha_str = nodes.InnerText;

                        return;

                    }

                    getAlpha_str(node);

                }

            }

        }



        public void getSv_count(XmlNode nodes)

        {

            if (nodes.HasChildNodes)

            {

                foreach (XmlNode node in nodes.ChildNodes)

                {

                    if (nodes.Name == "sv_count")

                    {

                        sv_count = int.Parse(nodes.InnerText);

                        return;

                    }

                    getSv_count(node);

                }

            }

        }

        

        public void getAlpha()

        {

            byte[] array = Encoding.ASCII.GetBytes(alpha_str);

            MemoryStream stream = new MemoryStream(array);             //convert stream 2 string      

            sr = new StreamReader(stream);

            alpha = new double[sv_count];

            sr.ReadLine();

            int i = 0;

            while (true)

            {



                string tmp = sr.ReadLine();

                if (tmp == "")

                    continue;



                string[] tmp2 = tmp.Split(' ');

                foreach (string ele in tmp2)

                {

                    if (ele != "")

                    {

                        alpha[i] = double.Parse(ele);

                        i++;

                    }

                }



                if (i == sv_count)

                    break;

            }

        }        

    }

}

c#读取XML的方式比较多，还可以利用Linq操作xml，另外也可以参考以下链接：

c# 读取opencv 生成的svm训练好的xml分类器：http://blog.csdn.net/yeyang911/article/details/12905153

---

 

2、使用其他C#的SVM库

关于提取参数，自定义HOG Detector的问题，后来在网上搜到了这种方式

Training custom SVM to use with HOGDescriptor in OpenCV：

I was struggling with the same problem. Searching forums I have found, that the detector cannot be trained using CvSVM (I don't know the reason). I used LIBSVM for training the the detector. Here is the code to extract the detector for HOGDescriptor.setSVMDetector( w): For data details see LIBSVM documentation/header. I did all the training in C++, filling the LIBSVM training data from CV to LIBSVM; the code below extracts the detector vector needed for cv::HOGDescriptor. The w parameter is std::vector<float> w

const double * const *sv_coef = model.sv_coef; const svm_node * const *SV = model.SV; int l = model.l; model.label; const svm_node* p_tmp = SV[0]; int len = 0; while( p_tmp->index != -1 ) { len++; p_tmp++; } w.resize( len+1 ); for( int i=0; i<l; i++) { double svcoef = sv_coef[0][i]; const svm_node* p = SV[i]; while( p->index != -1 ) { w[p->index-1] += float(svcoef * p->value); p++; } } w[len] = float(-model.rho[0]);

来自: http://stackoverflow.com/questions/15339657/training-custom-svm-to-use-with-hogdescriptor-in-opencv

---

该回答提到的 LIBSVM 库就是比较好的替代手段，应该可以直接获取到这两个中间量，而不用再去解析XML。

可以去作者主页上下载LIBSVM库：http://www.csie.ntu.edu.tw/~cjlin/libsvm/#csharp

---

 

3、其他相关链接

• 前些天的【OpenCV】基于HOG与SVM的行人检测学习（原理小结）:

    http://www.cnblogs.com/KC-Mei/p/4534009.html

• training GPU HOGDescriptor for multi scale detection：

    http://answers.opencv.org/question/4351/training-gpu-hogdescriptor-for-multi-scale-detection/