基本信息
源码名称:C# OPENCV几何形状识别
源码大小:2.35M
文件格式:.7z
开发语言:C#
更新时间:2020-03-21
友情提示:(无需注册或充值,赞助后即可获取资源下载链接)
嘿,亲!知识可是无价之宝呢,但咱这精心整理的资料也耗费了不少心血呀。小小地破费一下,绝对物超所值哦!如有下载和支付问题,请联系我们QQ(微信同号):78630559
本次赞助数额为: 2 元×
微信扫码支付:2 元
×
请留下您的邮箱,我们将在2小时内将文件发到您的邮箱
源码介绍
//opencv2.4.13
#include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <opencv2/ml/ml.hpp>
#include <iostream>
using namespace cv;
using namespace std;
//全局变量
Size sampleSize(160,160);//样本的大小
int train_samples =10;
int classes = 4;
Mat trainData;
Mat trainClasses;
//申明全局函数
Mat readImageSaveContour(Mat src);
void getData();
int main()
{
Mat src = imread("5.png", 0);
getData();
//定义SVM
/*CvSVMParams params;
params.svm_type = CvSVM::C_SVC;
params.kernel_type = CvSVM::LINEAR;
params.term_crit = cvTermCriteria(CV_TERMCRIT_ITER, 100, 1e-6);*/
CvSVMParams SVM_params; // CvSVMParams结构用于定义基本参数
SVM_params.svm_type = CvSVM::C_SVC; // SVM类型
SVM_params.kernel_type = CvSVM::LINEAR; // 不做映射
SVM_params.degree = 0;
SVM_params.gamma = 1;
SVM_params.coef0 = 0;
SVM_params.C = 1;
SVM_params.nu = 0;
SVM_params.p = 0;
SVM_params.term_crit = cvTermCriteria(CV_TERMCRIT_ITER, 1000, 0.01);
CvSVM SVM;
SVM.train(trainData, trainClasses, Mat(), Mat(), SVM_params);
//得到图像进行预测
Mat show;
cvtColor(src,show,8);//8 表示灰度图到彩色图
Mat imageWhite;
threshold(src, imageWhite, 100, 255, 8);
imageWhite = 255 - imageWhite;
vector<vector<Point> > contours;
vector<Vec4i> hierarchy;
findContours(imageWhite, contours, hierarchy, RETR_EXTERNAL, CHAIN_APPROX_NONE);
for (int index = contours.size() - 1; index >= 0; index--)
{
Rect rectangleTem = boundingRect(contours[index]);
Mat image;
image = Mat::zeros(src.size(), CV_8UC1);
drawContours(image, contours, index, Scalar(255), 2, 8, hierarchy);
Mat tem = image(rectangleTem);
Mat imageNewSize;
resize(tem, imageNewSize, sampleSize, CV_INTER_LINEAR);
image.release();
image = imageNewSize.reshape(1, 1);
image.convertTo(image, CV_32FC1);
int response = (int)SVM.predict(image);
if (response == 0)
{
cout << " circle" << endl;
string str = "circle";
putText(show, str, Point(rectangleTem.x rectangleTem.width / 2, rectangleTem.y rectangleTem.height / 2),
FONT_HERSHEY_SIMPLEX, 0.5, Scalar(0, 0, 255), 1, 8);
}
else if (response == 1)
{
cout << " rectangle" << endl;
string str = "rectangle";
putText(show, str, Point(rectangleTem.x rectangleTem.width / 2, rectangleTem.y rectangleTem.height / 2),
FONT_HERSHEY_SIMPLEX, 0.5, Scalar(0, 0, 255), 1, 8);
}
else if (response == 2)
{
cout << " triangle" << endl;
string str = "triangle";
putText(show, str, Point(rectangleTem.x rectangleTem.width / 2, rectangleTem.y rectangleTem.height / 2),
FONT_HERSHEY_SIMPLEX, 0.5, Scalar(0, 0, 255), 1, 8);
}
else if (response == 3)
{
cout << " cross" << endl;
string str = "cross";
putText(show, str, Point(rectangleTem.x rectangleTem.width / 2, rectangleTem.y rectangleTem.height / 2),
FONT_HERSHEY_SIMPLEX, 0.5, Scalar(0, 0, 255), 1, 8);
}
}
imshow("result",show);
imwrite("result.png", show);
waitKey(0);
return 0;
}
void getData()
{
trainData.create(train_samples*classes, sampleSize.width*sampleSize.height, CV_32FC1);
trainClasses.create(train_samples*classes, 1, CV_32FC1);
Mat src_image;
char file[255];
int i, j;
for (i = 0; i<classes; i )
{
for (j = 0; j< train_samples; j )
{
sprintf(file, "samples/s%d/%d.png", i, j);
src_image = imread(file, 0);
if (src_image.empty())
{
printf("Error: Cant load image %s\n", file);
//exit(-1);
}
Mat image = readImageSaveContour(src_image);
Mat imageNewSize;
resize(image, imageNewSize, sampleSize, CV_INTER_LINEAR);
image.release();
image = imageNewSize.reshape(1, 1);
image.convertTo(trainData(Range(i*train_samples j, i*train_samples j 1), Range(0, trainData.cols)), CV_32FC1);
trainClasses.at<float>(i*train_samples j, 0) = i;
}
}
}
Mat readImageSaveContour(Mat src)
{
Mat imageWhite;
threshold(src, imageWhite, 100, 255, 8);
imageWhite = 255 - imageWhite;
vector<vector<Point> > contours;
vector<Vec4i> hierarchy;
findContours(imageWhite, contours, hierarchy, RETR_EXTERNAL, CHAIN_APPROX_NONE);
//最大轮廓
double maxarea = 0;
int maxAreaIdx = 0;
for (int index = contours.size() - 1; index >= 0; index--)
{
double tmparea = fabs(contourArea(contours[index]));
if (tmparea>maxarea)
{
maxarea = tmparea;
maxAreaIdx = index;
}
}
Rect rectangleTem = boundingRect(contours[maxAreaIdx]);
Mat image;
image = Mat::zeros(src.size(), CV_8UC1);
drawContours(image, contours, 0, Scalar(255), 2, 8, hierarchy);
//Rect newRectangleTem(rectangleTem.x - 1, rectangleTem.y - 1, rectangleTem.width 2, rectangleTem.height 2);
Mat tem = image(rectangleTem);
return tem;
}