OpenCV学习之2
时间：2019-06-11 16:28:01
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[导读]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：#------------------------------
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:OpenSourceopencvbuildinclude -L D:OpenSourceopencvbuildincludeopencv -L D:OpenSourceopencvbuildincludeopencv2 LIBS += D:OpenSourceopencvbuildx86vc12libopencv_core2410.lib LIBS += D:OpenSourceopencvbuildx86vc12libopencv_highgui2410.lib LIBS += D:OpenSourceopencvbuildx86vc12libopencv_imgproc2410.lib LIBS += D:OpenSourceopencvbuildx86vc12libopencv_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#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#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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