OpenCV SVM训练数据

OpenCV SVM Training Data

本文关键字:数据 SVM OpenCV      更新时间:2023-10-16

我想通过使用c++和Visual Studio 2013中的opencv 3.00库来学习svm的实现。我的代码:

#include<stdio.h>
#include<math.h>
#include<opencvcv.h>
#include<opencvhighgui.h>
#include<opencv2objdetectobjdetect.hpp>
#include<opencv2highguihighgui.hpp>
#include<opencv2imgprocimgproc.hpp>
#include<vector>
#include <windows.h>
#include <atlstr.h>
#include <iostream>
#include <sstream>
#include <iomanip>
#include <opencv2imgprocimgproc.hpp>
#include <opencv2corecore.hpp>
#include <opencv2highguihighgui.hpp>
#include <opencvcvaux.hpp>
using namespace cv;
using namespace std;
#include <opencv2ml.hpp>
using namespace cv;
int main()
{
    // Data for visual representation
    int width = 512, height = 512;
    Mat image = Mat::zeros(height, width, CV_8UC3);
    // Set up training data
    float labels[4] = { 1.0, -1.0, -1.0, -1.0 };
    Mat labelsMat(4, 1, CV_32FC1, labels);
    float trainingData[4][2] = { { 501, 10 }, { 255, 10 }, { 501, 255 }, { 10, 501 } };
    Mat trainingDataMat(4, 2, CV_32FC1, trainingData);
    // Set up SVM's parameters
    Ptr<ml::SVM> svm = ml::SVM::create();
    // edit: the params struct got removed,
    // we use setter/getter now:
    svm->setType(ml::SVM::C_SVC);
    svm->setKernel(ml::SVM::LINEAR);
    svm->setGamma(3);
    svm->train(trainingDataMat, ml::ROW_SAMPLE, labelsMat);
    Mat res;   // output

    Vec3b green(0, 255, 0), blue(255, 0, 0);
    // Show the decision regions given by the SVM
    for (int i = 0; i < image.rows; ++i)
        for (int j = 0; j < image.cols; ++j)
        {
        Mat sampleMat = (Mat_<float>(1, 2) << j, i);
        float response = svm->predict(sampleMat, res);
        if (response == 1)
            image.at<Vec3b>(i, j) = green;
        else if (response == -1)
            image.at<Vec3b>(i, j) = blue;
        }
    // Show the training data
    int thickness = -1;
    int lineType = 8;
    circle(image, Point(501, 10), 5, Scalar(0, 0, 0), thickness, lineType);
    circle(image, Point(255, 10), 5, Scalar(255, 255, 255), thickness, lineType);
    circle(image, Point(501, 255), 5, Scalar(255, 255, 255), thickness, lineType);
    circle(image, Point(10, 501), 5, Scalar(255, 255, 255), thickness, lineType);
    // Show support vectors
    thickness = 2;
    lineType = 8;
    Mat sv = svm->getSupportVectors();
    for (int i = 0; i < sv.rows; ++i)
    {
        const float* v = sv.ptr<float>(i);
        circle(image, Point((int)v[0], (int)v[1]), 6, Scalar(128, 128, 128), thickness, lineType);
    }
    imwrite("result.png", image);        // save the image
    imshow("SVM Simple Example", image); // show it to the user
    waitKey(0);
} 

运行这段代码后,我得到了这个错误:

OpenCV Error: Bad argument < in the case of classification problem the responses must be categorical; 
either specify varType when creating TrainData, or pass integer responses > in cv::ml::SVMImpl::train, 
file C:buildsmaster_PackSlave-win64-vc12-sharedopencvmodulesmlsrcsvm.cpp, line 1610

我调试了那个代码。调试器停在这一行:svm->train(trainingDataMat, ml::ROW_SAMPLE, labelsMat);

它说:

 First-chance exception at 0x000007FEFDA5AAAD in train.exe: Microsoft C++ exception: cv::Exception at memory location 0x00000000001CEE50.
    Unhandled exception at 0x000007FEFDA5AAAD in train.exe: Microsoft C++ exception: cv::Exception at memory location 0x00000000001CEE50.

此外,它说:

(Win32): Loaded 'C:OpenCV3.0.0opencvbuildx64vc12binopencv_world300d.dll'. Cannot find or open the PDB file.

实际上,我所理解的是这个问题与记忆有关。

responses的类型不能为floatdouble

改变
float labels[4] = { 1.0, -1.0, -1.0, -1.0 };
Mat labelsMat(4, 1, CV_32FC1, labels);

int labels[4] = { 1, -1, -1, -1 };
Mat labelsMat(4, 1, CV_32S, labels);

BTW,如果你使用的是线性内核,唯一的参数是C,所以你不需要setGamma


另一个问题是如何获得预测响应。由于每次只有一个样本需要预测,如果您想使用返回值作为响应,则不应该将res传递给predict

你可以修改

float response = svm->predict(sampleMat, res);

float response = svm->predict(sampleMat);

否则,如果您想使用res,那么返回值不再是响应值。但是您可以从res获得响应。

你可以修改

if (response == 1)
    image.at<Vec3b>(i, j) = green;
else if (response == -1)
    image.at<Vec3b>(i, j) = blue;
}

if (res.at<float>(0) == 1)
    image.at<Vec3b>(i, j) = green;
else if (res.at<float>(0) == -1)
    image.at<Vec3b>(i, j) = blue;
}