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OpenCV学习之2


初次接触OpenCV


在用OpenCV做一些东西之前,要先配置一下开发环境,由于我的常使用的是Qt ,就以Qt作为例子。


这是我的pro配置:


#-------------------------------------------------
#
# Project created by QtCreator 2016-04-09T11:40:17
#
#-------------------------------------------------

QT       += core

QT       -= gui

TARGET = Example4
CONFIG   += console
CONFIG   -= app_bundle

TEMPLATE = app

INCLUDEPATH += -L D:\OpenSource\opencv\build\include \
               -L D:\OpenSource\opencv\build\include\opencv \
               -L D:\OpenSource\opencv\build\include\opencv2
LIBS += D:\OpenSource\opencv\build\x86\vc12\lib\opencv_core2410.lib
LIBS += D:\OpenSource\opencv\build\x86\vc12\lib\opencv_highgui2410.lib
LIBS += D:\OpenSource\opencv\build\x86\vc12\lib\opencv_imgproc2410.lib
LIBS += D:\OpenSource\opencv\build\x86\vc12\lib\opencv_photo2410.lib

SOURCES += main.cpp


INCLUDEPATH 中是必要的头文件包含,使用的是整体文件夹包含,LIBS是需要的LIB,使用的具体路径。


下面程序演示了对图片的一些简单处理,包括放大,缩小,平滑,和边缘检测并输出一个单通道的图像

#include <QCoreApplication>
#include "iostream"
#include "cxcore.h"
#include "cv.h"
#include "highgui.h"

//对图片进行缩操作
IplImage* doPyrDown(IplImage* in, int filter = IPL_GAUSSIAN_5x5)
{
    IplImage* out = cvCreateImage(cvSize(in->width/2,in->height/2),
                                  in->depth,
                                  in->nChannels);
    cvPyrDown(in,out);
    return out;
}
//对图片进行放操作
IplImage* doPyrUp(IplImage* in, int filter = IPL_GAUSSIAN_5x5)
{
    IplImage* out = cvCreateImage(cvSize(in->width * 2,in->height * 2),
                                  in->depth,
                                  in->nChannels);
    cvPyrUp(in,out);
    return out;
}
//进行边缘检测输出一个单通道图像(灰色)
IplImage* doCanny(IplImage* in,double lowThresh,double highThresh,double aperture)
{
    if(in->nChannels != 1)
        return 0;

    IplImage* out = cvCreateImage(cvGetSize(in),IPL_DEPTH_8U,1);

    cvCanny(in,out,lowThresh,highThresh,aperture);
    return out;
}

int main(int argc, char** argv)
{
    QCoreApplication a(argc, argv);

    //Create four windows to show our input image and output iamge
    cvNamedWindow("Example4_in",CV_WINDOW_AUTOSIZE);
    cvNamedWindow("Example4_out1",CV_WINDOW_AUTOSIZE);
    cvNamedWindow("Example4_out2",CV_WINDOW_AUTOSIZE);
    cvNamedWindow("Example4_out3",CV_WINDOW_AUTOSIZE);
    cvNamedWindow("Example4_out4",CV_WINDOW_AUTOSIZE);

    //show the input image
    IplImage* inImage = cvLoadImage("C:/Users/Administrator/Documents/Example4/debug/test.png");
    cvShowImage("Example4_in",inImage);

    //do the pyrdown and show the image
    IplImage* outImage1 = doPyrDown(inImage);
    cvShowImage("Example4_out1",outImage1);

    //do the pyrup and show the image
    IplImage* outImage2 = doPyrUp(inImage);
    cvShowImage("Example4_out2",outImage2);

    //do the smoothing and show the smoothed image
    IplImage* outImage3 = cvCreateImage(cvGetSize(inImage),IPL_DEPTH_8U,3);
    cvSmooth(inImage,outImage3,CV_GAUSSIAN,3,3);
    cvShowImage("Example4_out3",outImage3);

    //do the canny
    IplImage* outImage4 = doCanny(inImage,10,100,3);
    cvShowImage("Example4_out4",outImage4);

    //Be tidy
    cvWaitKey(0);
    cvReleaseImage(&outImage1);
    cvReleaseImage(&outImage2);
    cvReleaseImage(&outImage3);
    cvReleaseImage(&outImage4);
    cvDestroyWindow("Example4_in");
    cvDestroyWindow("Example4_out1");
    cvDestroyWindow("Example4_out2");
    cvDestroyWindow("Example4_out3");
    cvDestroyWindow("Example4_out4");

    return a.exec();
}


下面程序演示了对于视频的打开,并复制


#include <QCoreApplication>
#include "iostream"
//OpenCV
#include"cxcore.h"
#include "cv.h"
#include "highgui.h"

/****************************************************************

  首先打开一个视频文件,读取文件内容,将每一帧图像转化为对数
  极坐标格式(就像你的眼睛真正能看到的),最后将转化后的图像
  序列写入新的视频文件中

*****************************************************************/

int main(int argc, char *argv[])
{
    QCoreApplication a(argc, argv);

    CvCapture* capture = 0;
    capture = cvCreateFileCapture(argv[1]);//input video
    if(!capture)
    {
        return -1;
    }

    IplImage* bgr_frame = cvQueryFrame(capture);//init the video read
    double fps = cvGetCaptureProperty(capture,
                                      CV_CAP_PROP_FPS);
    CvSize size = cvSize(
                (int)cvGetCaptureProperty(capture,CV_CAP_PROP_FRAME_WIDTH),
                (int)cvGetCaptureProperty(capture,CV_CAP_PROP_FRAME_HEIGHT));
    CvVideoWriter* writer = cvCreateVideoWriter(argv[2],
                                                CV_FOURCC('M','J','P','G'),
                                                fps,
                                                size);
     IplImage* logpolar_frame = cvCreateImage(
                 size,
                 IPL_DEPTH_8U,
                 3);
/******************************************************************* 
     void cvLogPolar( const CvArr* src, 
                      CvArr* dst, 
                      CvPoint2D32f center, 
                      double M, 
                      int flags=CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS );
src 输入图像。 dst 输出图像。 center 变换的中心,输出图像在这里最精确。 M 幅度的尺度参数,见下面公式。 flags 插值方法和以下选择标志的结合
CV_WARP_FILL_OUTLIERS -填充输出图像所有像素,如果这些点有和外点对应的,则置零。
CV_WARP_INVERSE_MAP - 表示矩阵由输出图像到输入图像的逆变换,并且因此可以直接用于像素插值。否则,函数从map_matrix中寻找逆变换。
fillval 用于填充外点的值。

此函数模仿人类视网膜中央凹视力,并且对于目标跟踪等可用于快速尺度和旋转变换不变模板匹配。
************************************************************************/
                      
     while( bgr_frame != NULL)
     {
         cvLogPolar(bgr_frame,logpolar_frame,
                    cvPoint2D32f(bgr_frame->width/2,
                                bgr_frame->height/2),
                    40,
                    CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS);
         cvWriteFrame(writer,logpolar_frame);
     }
     cvReleaseVideoWriter(&writer);
     cvReleaseImage(&logpolar_frame);
     cvReleaseCapture(&capture);

    return a.exec();
}



在工程构建之后,要想运行成功,必须把DLL拷贝到debug中去。





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