OPENCV(7) —— HighGUI
包括函数createTrackbar、getTrackbarPos、setTrackbarPos、imshow、namedWindow、destroyWindow、destroyAllWindows、MoveWindow、ResizeWindow、SetMouseCallback、waitKey。这些函数保证了图像的基本处理、tarckbar的控制和鼠标键盘的响应
读写图像视频的函数:图像相关的函数有imdecode、imencode、imread、imwrite。读取视频相关为VideoCapture类,负责捕捉文件和摄像头的视频,该类内有成员函数VideoCapture、open、isOpened、release、grab、retrieve、read、get、set,写视频的类为VideoWriter,类内有成员函数VideoWriter、open、isOpened、write
void addWeighted(InputArray src1, double alpha, InputArray src2, double beta, double gamma, OutputArray dst, int dtype=-1)
Calculates the weighted sum of two arrays. 不同权重相加
int createTrackbar(const string& trackbarname, const string& winname, int* value, int count, TrackbarCallbackonChange=0, void* userdata=0)
Parameters:
- trackbarname – Name of the created trackbar.
- winname – Name of the window that will be used as a parent of the created trackbar.
- value – Optional pointer to an integer variable whose value reflects the position of the slider. Upon creation, the slider position is defined by this variable.
- count – Maximal position of the slider. The minimal position is always 0.
- onChange – Pointer to the function to be called every time the slider changes position. This function should be prototyped as void Foo(int,void*); , where the first parameter is the trackbar position and the second parameter is the user data (see the next parameter). If the callback is the NULL pointer, no callbacks are called, but only value is updated.
- userdata – User data that is passed as is to the callback. It can be used to handle trackbar events without using global variables.
#include "stdafx.h" #include <cv.h>
#include <highgui.h> using namespace cv; /// Global Variables
const int alpha_slider_max = 100;
int alpha_slider;
double alpha;
double beta; /// Matrices to store images
Mat src1;
Mat src2;
Mat dst; void on_trackbar( int, void* )
{
alpha = (double) alpha_slider/alpha_slider_max ;
beta = ( 1.0 - alpha ); addWeighted( src1, alpha, src2, beta, 0.0, dst); imshow( "Linear Blend", dst );
} int main( int argc, char** argv )
{
/// Read image ( same size, same type )
src1 = imread("lang.jpg");
src2 = imread("taitan.jpg"); if( !src1.data ) { printf("Error loading src1 \n"); return -1; }
if( !src2.data ) { printf("Error loading src2 \n"); return -1; } /// Initialize values
alpha_slider = 0; /// Create Windows
namedWindow("Linear Blend", 1); /// Create Trackbars
char TrackbarName[50];
sprintf( TrackbarName, "Alpha x %d", alpha_slider_max ); // 将格式化的数据写入某个字符串中 createTrackbar( TrackbarName, "Linear Blend", &alpha_slider, alpha_slider_max, on_trackbar );
// 滚动条名称,窗口名称,滑块位置,滑块最大值,回调函数 /// Show some stuff
on_trackbar( alpha_slider, 0 ); /// Wait until user press some key
waitKey(0);
return 0;
}
Video Stream
captRefrnc.set(CV_CAP_PROP_POS_MSEC, 1.2); // go to the 1.2 second in the video
captRefrnc.set(CV_CAP_PROP_POS_FRAMES, 10); // go to the 10th frame of the video
// now a read operation would read the frame at the set position
Image similarity - PSNR and SSIM
PSNR (aka Peak signal-to-noise ratio). The simplest definition of this starts out from the mean squad error. 计算两幅图像的均方误差 。 Let there be two images: I1 and I2; with a two dimensional size i and j, composed of c number of channels.
Then the PSNR is expressed as:
Here the is the maximum valid value for a pixel. In case of the simple single byte image per pixel per channel this is 255. When two images are the same the MSE will give zero, resulting in an invalid divide by zero operation in the PSNR formula.(差值为0的情况要区分对待) In this case the PSNR is undefined and as we’ll need to handle this case separately.
the source code presented at the start of the tutorial will perform the PSNR measurement for each frame, and the SSIM only for the frames where the PSNR falls below an input value.
Mat::convertTo
在缩放或不缩放的情况下转换为另一种数据类型。
void Mat::convertTo(OutputArray m,int rtype,double alpha=1,double beta=0)const
参数:
m – 目标矩阵。如果它的尺寸和类型不正确,在操作之前会重新分配。
rtype – 要求是目标矩阵的类型,或者在当前通道数与源矩阵通道数相同的情况下的depth。如果rtype 为负,目标矩阵与源矩阵类型相同。
beta – 可选的delta加到缩放值中去。
该方法将源像素值转化为目标类型saturate_cast<> 要放在最后以避免溢出
m( x;y) = saturate_cast < rType > ( α*( *this)( x;y) +β)
#include "stdafx.h" #include <iostream> // for standard I/O
#include <string> // for strings
#include <iomanip> // for controlling float print precision
#include <sstream> // string to number conversion #include <opencv2/imgproc/imgproc.hpp> // Gaussian Blur
#include <opencv2/core/core.hpp> // Basic OpenCV structures (cv::Mat, Scalar)
#include <opencv2/highgui/highgui.hpp> // OpenCV window I/O using namespace std;
using namespace cv; double getPSNR ( const Mat& I1, const Mat& I2);
Scalar getMSSIM( const Mat& I1, const Mat& I2); void help()
{
cout
<< "\n--------------------------------------------------------------------------" << endl
<< "This program shows how to read a video file with OpenCV. In addition, it tests the"
<< " similarity of two input videos first with PSNR, and for the frames below a PSNR " << endl
<< "trigger value, also with MSSIM."<< endl
<< "Usage:" << endl
<< "./video-source referenceVideo useCaseTestVideo PSNR_Trigger_Value Wait_Between_Frames " << endl
<< "--------------------------------------------------------------------------" << endl
<< endl;
}
int main(int argc, char *argv[], char *window_name)
{
help();
if (argc != 5)
{
cout << "Not enough parameters" << endl;
return -1;
}
stringstream conv; const string sourceReference = argv[1],sourceCompareWith = argv[2];
int psnrTriggerValue, delay;
conv << argv[3] << endl << argv[4]; // put in the strings
conv >> psnrTriggerValue >> delay; // take out the numbers string --- int char c;
int frameNum = -1; // Frame counter VideoCapture captRefrnc(sourceReference),
captUndTst(sourceCompareWith); if ( !captRefrnc.isOpened())
{
cout << "Could not open reference " << sourceReference << endl;
return -1;
} if( !captUndTst.isOpened())
{
cout << "Could not open case test " << sourceCompareWith << endl;
return -1;
} Size refS = Size((int) captRefrnc.get(CV_CAP_PROP_FRAME_WIDTH),
(int) captRefrnc.get(CV_CAP_PROP_FRAME_HEIGHT)), uTSi = Size((int) captUndTst.get(CV_CAP_PROP_FRAME_WIDTH),
(int) captUndTst.get(CV_CAP_PROP_FRAME_HEIGHT)); if (refS != uTSi)
{
cout << "Inputs have different size!!! Closing." << endl;
return -1;
} const char* WIN_UT = "Under Test"; // window name
const char* WIN_RF = "Reference"; // Windows
namedWindow(WIN_RF, CV_WINDOW_AUTOSIZE );
namedWindow(WIN_UT, CV_WINDOW_AUTOSIZE );
cvMoveWindow(WIN_RF, 400 , 0); //750, 2 (bernat =0)
cvMoveWindow(WIN_UT, refS.width, 0); //1500, 2 cout << "Reference frame resolution: Width=" << refS.width << " Height=" << refS.height
<< " of nr#: " << captRefrnc.get(CV_CAP_PROP_FRAME_COUNT) << endl; cout << "PSNR trigger value " <<
setiosflags(ios::fixed) << setprecision(3) << psnrTriggerValue << endl; Mat frameReference, frameUnderTest;
double psnrV;
Scalar mssimV; while( true) //Show the image captured in the window and repeat
{
captRefrnc >> frameReference; // 获取视频流中的一帧图像
captUndTst >> frameUnderTest; if( frameReference.empty() || frameUnderTest.empty()) // 视频流结束
{
cout << " < < < Game over! > > > ";
break;
} ++frameNum;
cout <<"Frame:" << frameNum <<"# "; ///////////////////////////////// PSNR ////////////////////////////////////////////////////
psnrV = getPSNR(frameReference,frameUnderTest); //get PSNR
cout << setiosflags(ios::fixed) << setprecision(3) << psnrV << "dB"; //////////////////////////////////// MSSIM /////////////////////////////////////////////////
if (psnrV < psnrTriggerValue && psnrV) // 基于效率考虑,只有PSNR低于一定阈值时考虑SSIM
{
mssimV = getMSSIM(frameReference,frameUnderTest); cout << " MSSIM: "
<< " R " << setiosflags(ios::fixed) << setprecision(2) << mssimV.val[2] * 100 << "%"
<< " G " << setiosflags(ios::fixed) << setprecision(2) << mssimV.val[1] * 100 << "%"
<< " B " << setiosflags(ios::fixed) << setprecision(2) << mssimV.val[0] * 100 << "%";
} cout << endl; ////////////////////////////////// Show Image /////////////////////////////////////////////
imshow( WIN_RF, frameReference);
imshow( WIN_UT, frameUnderTest); c = cvWaitKey(delay);
if (c == 27) break;
} return 0;
} double getPSNR(const Mat& I1, const Mat& I2)
{
Mat s1;
absdiff(I1, I2, s1); // |I1 - I2|
s1.convertTo(s1, CV_32F); // cannot make a square on 8 bits // 在缩放或不缩放的情况下转换为另一种数据类型
s1 = s1.mul(s1); // |I1 - I2|^2 // 执行两个矩阵按元素相乘或这两个矩阵的除法 Scalar s = sum(s1); // sum elements per channel double sse = s.val[0] + s.val[1] + s.val[2]; // sum channels if( sse <= 1e-10) // for small values return zero
return 0;
else
{
double mse =sse /(double)(I1.channels() * I1.total());
double psnr = 10.0*log10((255*255)/mse);
return psnr;
}
} Scalar getMSSIM( const Mat& i1, const Mat& i2)
{
const double C1 = 6.5025, C2 = 58.5225;
/***************************** INITS **********************************/
int d = CV_32F; Mat I1, I2;
i1.convertTo(I1, d); // cannot calculate on one byte large values
i2.convertTo(I2, d); Mat I2_2 = I2.mul(I2); // I2^2
Mat I1_2 = I1.mul(I1); // I1^2
Mat I1_I2 = I1.mul(I2); // I1 * I2 /*************************** END INITS **********************************/ Mat mu1, mu2; // PRELIMINARY COMPUTING
GaussianBlur(I1, mu1, Size(11, 11), 1.5);
GaussianBlur(I2, mu2, Size(11, 11), 1.5); Mat mu1_2 = mu1.mul(mu1);
Mat mu2_2 = mu2.mul(mu2);
Mat mu1_mu2 = mu1.mul(mu2); Mat sigma1_2, sigma2_2, sigma12; GaussianBlur(I1_2, sigma1_2, Size(11, 11), 1.5);
sigma1_2 -= mu1_2; GaussianBlur(I2_2, sigma2_2, Size(11, 11), 1.5);
sigma2_2 -= mu2_2; GaussianBlur(I1_I2, sigma12, Size(11, 11), 1.5);
sigma12 -= mu1_mu2; ///////////////////////////////// FORMULA ////////////////////////////////
Mat t1, t2, t3; t1 = 2 * mu1_mu2 + C1;
t2 = 2 * sigma12 + C2;
t3 = t1.mul(t2); // t3 = ((2*mu1_mu2 + C1).*(2*sigma12 + C2)) t1 = mu1_2 + mu2_2 + C1;
t2 = sigma1_2 + sigma2_2 + C2;
t1 = t1.mul(t2); // t1 =((mu1_2 + mu2_2 + C1).*(sigma1_2 + sigma2_2 + C2)) Mat ssim_map;
divide(t3, t1, ssim_map); // ssim_map = t3./t1; Scalar mssim = mean( ssim_map ); // mssim = average of ssim map
return mssim;
}
写video
For simple video outputs you can use the OpenCV built-in VideoWriter class, designed for this.
The type of the container is expressed in the files extension (for example avi, mov or mkv). This contains multiple elements like: video feeds, audio feeds or other tracks (like for example subtitles). How these feeds are stored is determined by the codec used for each one of them.
OPENCV的限制
Due to this OpenCV for video containers supports only the avi extension, its first version. A direct limitation of this is that you cannot save a video file larger than 2 GB. Furthermore you can only create and expand a single video track inside the container. No audio or other track editing support here.
VideoWriter::open(const string& filename, int fourcc, double fps, Size frameSize, bool isColor=true)
#include "stdafx.h"
#include <iostream> // for standard I/O
#include <string> // for strings #include <opencv2/core/core.hpp> // Basic OpenCV structures (cv::Mat)
#include <opencv2/highgui/highgui.hpp> // Video write using namespace std;
using namespace cv; static void help()
{
cout
<< "------------------------------------------------------------------------------" << endl
<< "This program shows how to write video files." << endl
<< "You can extract the R or G or B color channel of the input video." << endl
<< "Usage:" << endl
<< "./video-write inputvideoName [ R | G | B] [Y | N]" << endl
<< "------------------------------------------------------------------------------" << endl
<< endl;
} int main(int argc, char *argv[])
{
help(); // 命令行参数:video文件名,要提取的通道,是否使用与原video相同的codec
if (argc != 4)
{
cout << "Not enough parameters" << endl;
return -1;
} const string source = argv[1]; // the source file name
const bool askOutputType = argv[3][0] =='Y'; // If false it will use the inputs codec type VideoCapture inputVideo(source); // Open input
if (!inputVideo.isOpened())
{
cout << "Could not open the input video: " << source << endl;
return -1;
} string::size_type pAt = source.find_last_of('.'); // Find extension point
const string NAME = source.substr(0, pAt) + argv[2][0] + ".avi"; // Form the new name with container string 可以直接拼接
int ex = static_cast<int>(inputVideo.get(CV_CAP_PROP_FOURCC)); // Get Codec Type- Int form // Transform from int to char via Bitwise operators
char EXT[] = {(char)(ex & 0XFF) , (char)((ex & 0XFF00) >> 8),(char)((ex & 0XFF0000) >> 16),(char)((ex & 0XFF000000) >> 24), 0}; Size S = Size((int) inputVideo.get(CV_CAP_PROP_FRAME_WIDTH), // Acquire input size
(int) inputVideo.get(CV_CAP_PROP_FRAME_HEIGHT)); VideoWriter outputVideo; // Open the output
if (askOutputType)
outputVideo.open(NAME, ex=-1, inputVideo.get(CV_CAP_PROP_FPS), S, true);
else
outputVideo.open(NAME, ex, inputVideo.get(CV_CAP_PROP_FPS), S, true); if (!outputVideo.isOpened())
{
cout << "Could not open the output video for write: " << source << endl;
return -1;
} cout << "Input frame resolution: Width=" << S.width << " Height=" << S.height
<< " of nr#: " << inputVideo.get(CV_CAP_PROP_FRAME_COUNT) << endl;
cout << "Input codec type: " << EXT << endl; int channel = 2; // Select the channel to save
switch(argv[2][0])
{
case 'R' : channel = 2; break;
case 'G' : channel = 1; break;
case 'B' : channel = 0; break;
}
Mat src, res;
vector<Mat> spl; for(;;) //Show the image captured in the window and repeat
{
inputVideo >> src; // read
if (src.empty()) break; // check if at end split(src, spl); // process - extract only the correct channel // 将图像拆成单通道
for (int i =0; i < 3; ++i)
if (i != channel)
spl[i] = Mat::zeros(S, spl[0].type()); // 其他通道置零
merge(spl, res); // 合并不同通道 //outputVideo.write(res); //save or
outputVideo << res;
} cout << "Finished writing" << endl;
return 0;
}
OPENCV(7) —— HighGUI的更多相关文章
- opencv学习HighGUI图形用户界面初步【1】
HighGUI是图形用户界面模块.包括:1.输入与输出:2.视频捕捉:3.图形和视频的解码编码:4.图形交界面与接口. 由于opencv.hpp包含了core.objdetect.ingproc.ph ...
- opencv 1 HighGUI图形用户界面初步
1图像载入 显示和输出到文件 Opencv的命名空间 Mat类 图像的载入:imread()函数 图片的显示:imshow()函数 创建窗口:namedWindow()函数 输出图像到文件:imwri ...
- 解决“cv2.error: OpenCV(3.4.2) C:\projects\opencv-python\opencv\modules\highgui\src\window.cpp:356:...”
主要是图片路径中“文件夹分隔符”使用的错误 将“\”改成“/”就好了 修改后的测试代码如下:x.py #导入cv模块 import cv2 as cv #读取图像,支持 bmp.jpg.png.tif ...
- 从HighGUI的一段代码中看OpenCV打开视频的方式
OpenCV的HighGUI提供了视频和摄像头的直接打开.那么它是如何实现的了?这里进行初步分析. ; switch(apiPreference) { default: ...
- opencv 人脸识别
背景知识 OpenCV 是一个开源的计算机视觉和机器学习库.它包含成千上万优化过的算法,为各种计算机视觉应用提供了一个通用工具包.根据这个项目的关于页面,OpenCV 已被广泛运用在各种项目上,从 ...
- 【OpenCV入门教程之一】 安装OpenCV:OpenCV 3.0 +VS 2013 开发环境配置
图片太多,具体过程参照: [OpenCV入门教程之一] 安装OpenCV:OpenCV 3.0.OpenCV 2.4.8.OpenCV 2.4.9 +VS 开发环境配置 说下我这边的设置: 选择deb ...
- opencv载入,显示及保存图像
1.声明一个表示图像的变量,在OpenCV2中,这个变量是cv::Mat类型,该类是用于保存图像以及其他矩阵数据的数据结构.默认情况下它们的尺寸为0. cv::Mat image; // ...
- OpenCV学习 物体检测 人脸识别 填充颜色
介绍 OpenCV是开源计算机视觉和机器学习库.包含成千上万优化过的算法.项目地址:http://opencv.org/about.html.官方文档:http://docs.opencv.org/m ...
- matlab调用opencv函数的配置
环境: VS2010 活动解决方案平台x64 WIN 8.1 Opencv 2.4.3 Matlab 2012a 1. 首先保证vs2010能正确调用opencv函数, 2. Matlab中选择编 ...
随机推荐
- python set元素访问
python中集合set主要利用其唯一性,及并集|.交集&等操作,但不可以直接通过下标进行访问,必须访问时可以将其转换成list再访问 x={1,2,5} y=list(x) a=y[1] a ...
- 洛谷 P1702 突击考试
P1702 突击考试 题目描述 一日,老师决定进行一次突击考试.已知每个学生都有一个考试能力等级,教室里一共有N个课桌,按照顺序排成一列,每张课桌可以坐两个人,第i张课桌坐的两个人的能力等级为(A[i ...
- echarts 地图 动态 展示 结合css+js
echarts地图展示功能非常强大,官网上静态展示的样例非常多了,动态的资料少.研究了下.我眼下实现的通过ajax从server获取数据动态展示地图. 另外,我们有时候希望在地图之上做些自己定义的东西 ...
- rtmutex赏析
[摘要] rtmutex作为futex的底层实现,有两个比較重要的特性.一个是优先级继承,一个是死锁检測.本文对这两个特性的实现进行说明. 一.优先级继承 2007年火星探路者号的vxworks上发生 ...
- [学习笔记]AJAX学习
AJAX学习 ——在w3cschool学习AJAX的学习笔记 参考网站:w3cschool XMLHttpRequest 是 AJAX 的基础. XMLHttpRequest 对象 所有现代浏览器均支 ...
- kali 2.0 linux中的Nmap的主机探测
不多说,直接上干货! 如果是第一次接触Nmap,推荐在MSF终端中输入不加任何参数的Nmap命令,以查看其使用方法. 更多,其实, msf > nmap -h [*] exec: nmap -h ...
- nodejs 通过 get获取数据修改redis数据
如下代码是没有报错的正确代码 我通过https获取到数据 想用redis set一个键值存储 现在我掉入了回调陷阱res.on 里面接收到的数据是data 里面如果放入 client.on('conn ...
- PostgreSQL Replication之第四章 设置异步复制(3)
4.3 slave到master的切换 如果您想扩展读或您想做一个数据备份,一个 slave是件美好的事情.但是,slave可能不会一直是slave.在有些时候,您可能需要把slave转换为maste ...
- RMAN备份脚本
单机环境全备 export ORACLE_BASE=/oracle export ORACLE_HOME=$ORACLE_BASE/product/10.2.0/db_1 export ORA ...
- Percona Monitoring and Management (PMM)安装使用
一.docker安装 参考:http://www.cnblogs.com/liuyongsheng/articles/6595353.html 二.Percona Monitoring and Man ...