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
- caioj 1157 线性筛选素数
注意这道题开得非常大,有2*1e7 自己可以养成一种习惯,如果数据是很容易的话,可以自己手动输入极限数据来测试自己的程序 #include<cstdio> #include<algo ...
- 洛谷 P1220 关路灯 (贪心+区间dp)
这一道题我一直在想时间该怎么算. 看题解发现有个隐藏的贪心. 路径一定是左右扩展的,左右端点最多加+1(我竟然没发现!!) 这个性质非常重要!! 因此这道题用区间dp f[i][j]表示关完i到j的路 ...
- 简单搭建zookeeper集群分布式/伪分布式
分布式搭建 一.下载zookeeper安装包 自行下载:我用的是 zookeeper-3.5.4-beta.tar.gz 二.环境准备 1. 我的虚拟机自带的java是1.7的,这个版本要求java1 ...
- MongoDB count distinct group by JavaAPI查询
import java.net.UnknownHostException; import com.mongodb.BasicDBList; import com.mongodb.BasicDBObje ...
- 在KVM中执行windows 10虚机(by quqi99)
作者:张华 发表于:2015-12-22版权声明:能够随意转载.转载时请务必以超链接形式标明文章原始出处和作者信息及本版权声明 ( http://blog.csdn.net/quqi99 ) KVM ...
- OpenCASCADE License FAQs
OpenCASCADE License FAQs 经常用人问我使用OpenCASCADE开发商业软件是否需要付费,下面从OpenCASCADE的官方网站上截取其回答翻译成中文,官方网址:https:/ ...
- 利用 border 实现的图片选区效果,只需一层图一蒙层
<html> <style> #p { background: url("http://soso5.gtimg.cn/sosopic_j/0/436416703332 ...
- pyspark import 可以通过 --py-files
公用函数的放到了 common.py 文件中. 通过 --py-files 可以在pyspark中可以顺利导入: pyspark --py-files lib/common.py > impor ...
- BZOJ 1797 网络流的可行边&必须边
求完网络流以后 tarjan一发 判一判 //By SiriusRen #include <queue> #include <bitset> #include <cstd ...
- nginx 代理https后,应用redirect https变成http --转
原文地址:http://blog.sina.com.cn/s/blog_56d8ea900101hlhv.html 情况说明nginx配置https,tomcat正常http接受nginx转发.ngi ...



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.