从零开始的嵌入式图像图像处理(PI+QT+OpenCV)实战演练
1综述
http://www.cnblogs.com/jsxyhelu/p/7907241.html
2环境架设
http://www.cnblogs.com/jsxyhelu/p/7908226.html
3两个例子
http://www.cnblogs.com/jsxyhelu/p/8000804.html
4程序框架
http://www.cnblogs.com/jsxyhelu/p/7953805.html
5编译使用最新opencv
http://www.cnblogs.com/jsxyhelu/p/8000819.html
6综合实验
http://www.cnblogs.com/jsxyhelu/p/8000829.html
7拾遗
http://www.cnblogs.com/jsxyhelu/p/8007117.html
最后，我们必须完成一个综合实验，来验证前面所做的一切工作。为了达到这个目的，将实验设定为：使用实时根据图像的特征（包括
ORB/SHIFT/SURF/BRISK)，进行特征比对
。这样，就验证了opencv类库的编译（因为使用了contrib库，所以必须自己编译）、基本程序框架的运行（涉及摄像头操作）。并且我们是使用虚拟机（PC版本的PI系统）编译测试，而后移植到PI上面去的。
配置文件：
#
# Project created by QtCreator 2017 - 11 - 29T07 : 39 : 32
#
# -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -
QT += core gui
greaterThan(QT_MAJOR_VERSION, 4) : QT += widgets
TARGET = GOQTTemplate2
TEMPLATE = app
INCLUDEPATH += /usr /local / include /opencv \
/usr /local / include /opencv2
LIBS += /usr /local /lib /libopencv_world.so
SOURCES += main.cpp\
mainwindow.cpp \
clickedlabel.cpp
HEADERS += mainwindow.h \
clickedlabel.h
FORMS += mainwindow.ui
# Project created by QtCreator 2017 - 11 - 29T07 : 39 : 32
#
# -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -
QT += core gui
greaterThan(QT_MAJOR_VERSION, 4) : QT += widgets
TARGET = GOQTTemplate2
TEMPLATE = app
INCLUDEPATH += /usr /local / include /opencv \
/usr /local / include /opencv2
LIBS += /usr /local /lib /libopencv_world.so
SOURCES += main.cpp\
mainwindow.cpp \
clickedlabel.cpp
HEADERS += mainwindow.h \
clickedlabel.h
FORMS += mainwindow.ui
主程序文件,简单说明流程：程序一开始就打开默认的摄像头，而后截获显示摄像头获取的数据。当有点击图片的操作的时候，保存当前图片作为模板，而后开始特征点匹配，并且显示匹配结果。有一个按钮能够切换不同的特征点算法：
//by jsxyhelu 2017/12/6
# include "mainwindow.h"
# include "ui_mainwindow.h"
# include <QMouseEvent >
//全局变量
Mat src;
Mat gray;
Mat tmp;
Mat dst;
Mat matMatch; //template
double m_lastTime; //time
Mat grayLeft;
Mat grayRight;
Mat descriptorsLeft;
std : :vector <KeyPoint > keypointsLeft;
Mat descriptorsRight;
std : :vector <KeyPoint > keypointsRight;
std : :vector < DMatch > matches;
std : :vector < DMatch > good_matches;
Mat img_matches;
int imethod; //0-ORB 1-SIFT 2-SURF 3-BRISK
using namespace cv;
MainWindow : :MainWindow(QWidget *parent) :
QMainWindow(parent),
ui( new Ui : :MainWindow)
{
ui - >setupUi( this);
timer = new QTimer( this);
imag = new QImage(); // 初始化
connect(timer, SIGNAL(timeout()), this, SLOT(readFarme())); // 时间到，读取当前摄像头信息
bMethod = false; //是否使用算法
on_pushButton_clicked(); //main process
//take a picture
clickLabel = new ClickedLabel( this);
clickLabel - >setGeometry( 0, 0, 800, 400);
connect(clickLabel,SIGNAL(clicked(ClickedLabel *)), this,SLOT(on_pushButton_3_clicked()));
imethod = 0; //ORB
setWindowState(Qt : :WindowMaximized); //max
}
MainWindow : : ~MainWindow()
{
delete ui;
}
事件驱动///
//打开摄像头
void MainWindow : :on_pushButton_clicked()
{
//打开摄像头，从摄像头中获取视频
videocapture = new VideoCapture( 0);
// 开始计时，超时则发出timeout()信号
timer - >start( 33);
}
//main process 读取下一Frame图像 when timeout()
void MainWindow : :readFarme()
{
// 从摄像头中抓取并返回每一帧
videocapture - >read(matFrame);
src = matFrame.clone();
m_lastTime = ( double)getTickCount();
tmp = matFrame.clone();
//final
cv : :resize(tmp,tmp,Size( 200, 200));
dst = Mat(Size(tmp.cols * 2,tmp.rows),tmp.type(),Scalar( 255));
tmp.copyTo(dst(cv : :Rect( 0, 0, 200, 200)));
//生成特征点算法及其匹配方法
Ptr <Feature2D > extractor;
BFMatcher matcher;
switch (imethod)
{
case 1 : //"SIFT"
extractor = SIFT : :create();
matcher = BFMatcher(NORM_L2);
break;
case 2 : //"SURF"
extractor = SURF : :create();
matcher = BFMatcher(NORM_L2);
break;
case 3 : //"BRISK"
extractor = BRISK : :create();
matcher = BFMatcher(NORM_HAMMING);
break;
case 0 : //"ORB"
extractor = ORB : :create();
matcher = BFMatcher(NORM_HAMMING);
break;
}
if(matMatch.rows > 0)
{
//利用现有数据结构，对比对结构进行筛选
double max_dist = 0; double min_dist = 100;
//action
cv : :resize(matMatch,matMatch,Size( 200, 200));
//gray
cvtColor(tmp,grayLeft,COLOR_BGR2GRAY);
cvtColor(matMatch,grayRight,COLOR_BGR2GRAY);
//寻找到特征点
extractor - >detectAndCompute(grayLeft,Mat(),keypointsLeft,descriptorsLeft);
extractor - >detectAndCompute(grayRight,Mat(),keypointsRight,descriptorsRight);
matcher.match( descriptorsLeft, descriptorsRight, matches );
//对现有距离进行排序
for( int i = 0; i < descriptorsLeft.rows; i ++ )
{
double dist = matches[i].distance;
if( dist < min_dist ) min_dist = dist;
if( dist > max_dist ) max_dist = dist;
}
for( int i = 0; i < descriptorsLeft.rows; i ++ )
{
if( matches[i].distance < = max( 2 *min_dist, 0. 02) )
{
good_matches.push_back( matches[i]);
}
}
drawMatches( tmp, keypointsLeft, matMatch, keypointsRight, good_matches, dst );
//clear
good_matches.clear();
}
cv : :resize(dst,dst,Size( 800, 400));
switch (imethod)
{
case 0 :
putText(dst, "METHOD:ORB",Point( 10, 350),CV_FONT_HERSHEY_DUPLEX, 1.0f,Scalar( 0, 0, 255));
break;
case 1 :
putText(dst, "METHOD:SIFT",Point( 10, 350),CV_FONT_HERSHEY_DUPLEX, 1.0f,Scalar( 0, 0, 255));
break;
case 2 :
putText(dst, "METHOD:SURF",Point( 10, 350),CV_FONT_HERSHEY_DUPLEX, 1.0f,Scalar( 0, 0, 255));
break;
case 3 :
putText(dst, "METHOD:BRISK",Point( 10, 350),CV_FONT_HERSHEY_DUPLEX, 1.0f,Scalar( 0, 0, 255));
break;
}
// 格式转换
QPixmap qpixmap = Mat2QImage(dst);
// 将图片显示到label上
clickLabel - >setPixmap(qpixmap);
m_lastTime = ( double)getTickCount();
}
//method
void MainWindow : :on_pushButton_2_clicked()
{
if(imethod == 4)
{
imethod = 1;
} else
{
imethod += 1;
}
}
//action
void MainWindow : :on_pushButton_3_clicked()
{
matMatch = src.clone();
}
//exit
void MainWindow : :on_pushButton_4_clicked()
{
timer - >stop(); // 停止读取数据。
videocapture - >release();
//exit
QApplication * app;
app - >exit( 0);
}
//helper函数//
//格式转换
QPixmap Mat2QImage(Mat src)
{
QImage img;
//根据QT的显示方法进行转换
if(src.channels() == 3)
{
cvtColor( src, tmp, CV_BGR2RGB );
img = QImage( ( const unsigned char *)(tmp.data), tmp.cols, tmp.rows, QImage : :Format_RGB888 );
}
else
{
img = QImage( ( const unsigned char *)(src.data), src.cols, src.rows, QImage : :Format_Indexed8 );
}
QPixmap qimg = QPixmap : :fromImage(img) ;
return qimg;
}
# include "mainwindow.h"
# include "ui_mainwindow.h"
# include <QMouseEvent >
//全局变量
Mat src;
Mat gray;
Mat tmp;
Mat dst;
Mat matMatch; //template
double m_lastTime; //time
Mat grayLeft;
Mat grayRight;
Mat descriptorsLeft;
std : :vector <KeyPoint > keypointsLeft;
Mat descriptorsRight;
std : :vector <KeyPoint > keypointsRight;
std : :vector < DMatch > matches;
std : :vector < DMatch > good_matches;
Mat img_matches;
int imethod; //0-ORB 1-SIFT 2-SURF 3-BRISK
using namespace cv;
MainWindow : :MainWindow(QWidget *parent) :
QMainWindow(parent),
ui( new Ui : :MainWindow)
{
ui - >setupUi( this);
timer = new QTimer( this);
imag = new QImage(); // 初始化
connect(timer, SIGNAL(timeout()), this, SLOT(readFarme())); // 时间到，读取当前摄像头信息
bMethod = false; //是否使用算法
on_pushButton_clicked(); //main process
//take a picture
clickLabel = new ClickedLabel( this);
clickLabel - >setGeometry( 0, 0, 800, 400);
connect(clickLabel,SIGNAL(clicked(ClickedLabel *)), this,SLOT(on_pushButton_3_clicked()));
imethod = 0; //ORB
setWindowState(Qt : :WindowMaximized); //max
}
MainWindow : : ~MainWindow()
{
delete ui;
}
事件驱动///
//打开摄像头
void MainWindow : :on_pushButton_clicked()
{
//打开摄像头，从摄像头中获取视频
videocapture = new VideoCapture( 0);
// 开始计时，超时则发出timeout()信号
timer - >start( 33);
}
//main process 读取下一Frame图像 when timeout()
void MainWindow : :readFarme()
{
// 从摄像头中抓取并返回每一帧
videocapture - >read(matFrame);
src = matFrame.clone();
m_lastTime = ( double)getTickCount();
tmp = matFrame.clone();
//final
cv : :resize(tmp,tmp,Size( 200, 200));
dst = Mat(Size(tmp.cols * 2,tmp.rows),tmp.type(),Scalar( 255));
tmp.copyTo(dst(cv : :Rect( 0, 0, 200, 200)));
//生成特征点算法及其匹配方法
Ptr <Feature2D > extractor;
BFMatcher matcher;
switch (imethod)
{
case 1 : //"SIFT"
extractor = SIFT : :create();
matcher = BFMatcher(NORM_L2);
break;
case 2 : //"SURF"
extractor = SURF : :create();
matcher = BFMatcher(NORM_L2);
break;
case 3 : //"BRISK"
extractor = BRISK : :create();
matcher = BFMatcher(NORM_HAMMING);
break;
case 0 : //"ORB"
extractor = ORB : :create();
matcher = BFMatcher(NORM_HAMMING);
break;
}
if(matMatch.rows > 0)
{
//利用现有数据结构，对比对结构进行筛选
double max_dist = 0; double min_dist = 100;
//action
cv : :resize(matMatch,matMatch,Size( 200, 200));
//gray
cvtColor(tmp,grayLeft,COLOR_BGR2GRAY);
cvtColor(matMatch,grayRight,COLOR_BGR2GRAY);
//寻找到特征点
extractor - >detectAndCompute(grayLeft,Mat(),keypointsLeft,descriptorsLeft);
extractor - >detectAndCompute(grayRight,Mat(),keypointsRight,descriptorsRight);
matcher.match( descriptorsLeft, descriptorsRight, matches );
//对现有距离进行排序
for( int i = 0; i < descriptorsLeft.rows; i ++ )
{
double dist = matches[i].distance;
if( dist < min_dist ) min_dist = dist;
if( dist > max_dist ) max_dist = dist;
}
for( int i = 0; i < descriptorsLeft.rows; i ++ )
{
if( matches[i].distance < = max( 2 *min_dist, 0. 02) )
{
good_matches.push_back( matches[i]);
}
}
drawMatches( tmp, keypointsLeft, matMatch, keypointsRight, good_matches, dst );
//clear
good_matches.clear();
}
cv : :resize(dst,dst,Size( 800, 400));
switch (imethod)
{
case 0 :
putText(dst, "METHOD:ORB",Point( 10, 350),CV_FONT_HERSHEY_DUPLEX, 1.0f,Scalar( 0, 0, 255));
break;
case 1 :
putText(dst, "METHOD:SIFT",Point( 10, 350),CV_FONT_HERSHEY_DUPLEX, 1.0f,Scalar( 0, 0, 255));
break;
case 2 :
putText(dst, "METHOD:SURF",Point( 10, 350),CV_FONT_HERSHEY_DUPLEX, 1.0f,Scalar( 0, 0, 255));
break;
case 3 :
putText(dst, "METHOD:BRISK",Point( 10, 350),CV_FONT_HERSHEY_DUPLEX, 1.0f,Scalar( 0, 0, 255));
break;
}
// 格式转换
QPixmap qpixmap = Mat2QImage(dst);
// 将图片显示到label上
clickLabel - >setPixmap(qpixmap);
m_lastTime = ( double)getTickCount();
}
//method
void MainWindow : :on_pushButton_2_clicked()
{
if(imethod == 4)
{
imethod = 1;
} else
{
imethod += 1;
}
}
//action
void MainWindow : :on_pushButton_3_clicked()
{
matMatch = src.clone();
}
//exit
void MainWindow : :on_pushButton_4_clicked()
{
timer - >stop(); // 停止读取数据。
videocapture - >release();
//exit
QApplication * app;
app - >exit( 0);
}
//helper函数//
//格式转换
QPixmap Mat2QImage(Mat src)
{
QImage img;
//根据QT的显示方法进行转换
if(src.channels() == 3)
{
cvtColor( src, tmp, CV_BGR2RGB );
img = QImage( ( const unsigned char *)(tmp.data), tmp.cols, tmp.rows, QImage : :Format_RGB888 );
}
else
{
img = QImage( ( const unsigned char *)(src.data), src.cols, src.rows, QImage : :Format_Indexed8 );
}
QPixmap qimg = QPixmap : :fromImage(img) ;
return qimg;
}