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opencv 重用代码块记录

Created on 2013-8-7
URL : http://blog.sina.com.cn/s/blog_a502f1a30101mfj4.html
@author: zhxfl

转载请说明出处

一从视频中提取帧并且保存图片

#include <iostream>
#include <stdio.h>
#include "opencv2/highgui/highgui.hpp"
using namespace std;
using namespace cv;

bool VedioToImage(char *from, char *to)
{
        CvCapture *capture = cvCreateFileCapture(from);
        if(!capture)
                return false;
        IplImage  *frame = 0;
        for(int i = 0, j = 0;; j++)
        {
                frame = cvQueryFrame( capture );
                if(frame)
                {
                        if(j % 5 == 0)
                        {
                                char str[1024];
                                sprintf(str,"%s/%d.png",to,i);
                                cvSaveImage(str,frame);
                                printf("%d.png
",i++);
                        }
                }
                else
                {
                        break;
                }
        }

        return true;
}

int main()
{
        VedioToImage("../fly.mp4","../fly");
        return 0;
}

从视频中提取帧并且保存成图片

GINC=$(shell pkg-config --cflags opencv)
GLIB=$(shell pkg-config --libs opencv)
all:build
build:a.out
a.o:a.cpp
        g++ $(GINC) -c a.cpp
a:a.o
        g++ -o  a a.o $(GLIB)
clean:
        rm *.o
run:build
        ./a.out

Makefile

二对一系列图片进行处理，去掉没有检测到人脸的照片

#include <iostream>
#include <iomanip>
#include "opencv2/core/core.hpp"
#include "opencv2/contrib/contrib.hpp"
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc_c.h"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/gpu/gpu.hpp"
#include <stdio.h>
#include <time.h>
using namespace std;
using namespace cv;
using namespace cv::gpu;

std::string getWorkspace()
{
#if (defined _WIN32 || defined _WIN64) && defined _MSC_VER
    std::string workspace = std::string("E:/Resources");
#else
    std::string workspace = std::string("/data/ubuntu/Resources");
#endif
    return workspace;
}

string path = getWorkspace() + "/haarcascade_frontalface_alt.xml";
CascadeClassifier cascade_cpu;//使用cpu的分类器器
CascadeClassifier cascade_gpu;//使用cpu的分类器器
int detectFaceCpu(std::string file)
{
    string input = getWorkspace() + string("/image/") + file;
    Mat frame_cpu = cv::imread(input.c_str());

    Mat gray_cpu;
    //转化成灰度图
    if (frame_cpu.channels() == 3)
    {
        cvtColor(frame_cpu, gray_cpu, CV_BGR2GRAY );
    }
    else
    {
        gray_cpu = frame_cpu;
    }
    vector<Rect> facesBuf_cpu;

    cascade_cpu.detectMultiScale(gray_cpu, facesBuf_cpu);
    
    for(size_t i = 0; i < facesBuf_cpu.size();i++)
    {
        rectangle(frame_cpu, facesBuf_cpu[i], Scalar(255));
    }

    if(facesBuf_cpu.size())
    {
        string path = getWorkspace() + string("/image_output/") + file;
        IplImage tmp (frame_cpu);
        cvSaveImage(path.c_str(), &tmp); 
    }
    return true;
}

int detectFaceGpu(std::string file)
{
    string input = getWorkspace() + string("/image/") + file;
    Mat frame_gpu = cv::imread(input.c_str());
    Mat gray_gpu;
    //转化成灰度图
    if (frame_gpu.channels() == 3)
    {
        cvtColor(frame_gpu, gray_gpu, CV_BGR2GRAY );
    }
    else
    {
        gray_gpu = frame_gpu;
    }
    vector<Rect> facesBuf_gpu;

    cascade_gpu.detectMultiScale(gray_gpu, facesBuf_gpu);

    for(size_t i = 0; i < facesBuf_gpu.size();i++)
    {
        rectangle(frame_gpu, facesBuf_gpu[i], Scalar(255));
    }

    if(facesBuf_gpu.size())
    {
        string path = getWorkspace() + string("/image_output/") + file;
        IplImage tmp (frame_gpu);
        cvSaveImage(path.c_str(), &tmp); 
    }
    return true;
}

int main(int argc, unsigned char* argv[])
{
    if (!cascade_cpu.load(path))
    {
        printf("error cpu
");
        return 0;
    }

    if (!cascade_gpu.load(path))
    {
        printf("errror gpu
");
        return 0;
    }

    for(int i = 180; i < 569;i++)
    {
        char str[125];
        sprintf(str, "%03d.tif", i);
        float start = clock();
        detectFaceGpu(string(str));
        float end = clock();
        printf("%03d.tif time = %f
",i ,(end - start) / 1000);
    }
    return 0;
}

View Code

三使用摄像头录制视频

#include <iostream>
#include <iomanip>
#include "opencv2/core/core.hpp"
#include "opencv2/contrib/contrib.hpp"
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc_c.h"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/gpu/gpu.hpp"
#include <stdio.h>
#include <time.h>
using namespace std;
using namespace cv;
using namespace cv::gpu;

std::string getWorkspace()
{
#if (defined _WIN32 || defined _WIN64) && defined _MSC_VER
    std::string workspace = std::string("E:/Resources");
#else
    std::string workspace = std::string("/data/ubuntu/Resources");
#endif
    return workspace;
}

int main(int argc, unsigned char* argv[])
{
    for(int k = 16; k < 100; k++)
    {
        char str[125];
        sprintf(str, "/%d.avi",k);
        string path = getWorkspace() + string(str);
        CvVideoWriter * writer = cvCreateVideoWriter(path.c_str(),CV_FOURCC('X','V','I','D'),20,cvSize(640,480));  // 需要安装xvid编码器

        CvCapture* capture1 = cvCaptureFromCAM(0);
        int w = 640, h = 480;
        cvSetCaptureProperty ( capture1, CV_CAP_PROP_FRAME_WIDTH,  w );
        cvSetCaptureProperty ( capture1, CV_CAP_PROP_FRAME_HEIGHT, h );
        cvNamedWindow( "Camera_1", CV_WINDOW_AUTOSIZE );
        IplImage* frame1;
        int n = 2;
        int i =0;
        while(1)
        {
            frame1 = cvQueryFrame( capture1 );
            if( !frame1 ) break;
            {
                cvShowImage( "Camera_1", frame1 );
                cvWriteFrame(writer,frame1); //写入文件
            }
            int key = cvWaitKey(10);
            if( key == 27 ) break;
            if(i >=500 )break;
            else i++;
            printf("%d
",i);
        }
        cvReleaseVideoWriter(&writer);
        cvReleaseCapture( &capture1 );
        cvDestroyWindow( "Camera_1" );
    }
    return 0;
}

View Code

四将视频流分成两部分，一部分是能够圈到人脸，一部分不能。

#include <iostream>
#include <iomanip>
#include "opencv2/core/core.hpp"
#include "opencv2/contrib/contrib.hpp"
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc_c.h"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/gpu/gpu.hpp"
#include <stdio.h>
#include <time.h>
using namespace std;
using namespace cv;
using namespace cv::gpu;

std::string getWorkspace()
{
#if (defined _WIN32 || defined _WIN64) && defined _MSC_VER
    std::string workspace = std::string("E:/Resources");
#else
    std::string workspace = std::string("/data/hadoop/Resources");
#endif
    return workspace;
}

CascadeClassifier cascade_cpu;//使用cpu的分类器器
CascadeClassifier_GPU cascade_gpu;//使用cpu的分类器器

bool detectFaceCpu(Mat &frame_cpu)
{
    Mat gray_cpu;
    //转化成灰度图
    if (frame_cpu.channels() == 3)
    {
        cvtColor(frame_cpu, gray_cpu, CV_BGR2GRAY );
    }
    else
    {
        gray_cpu = frame_cpu;
    }
    vector<Rect> facesBuf_cpu;

    cascade_cpu.detectMultiScale(gray_cpu, facesBuf_cpu, 1.2, 4);


    for(size_t i = 0; i < facesBuf_cpu.size();i++)
    {
        rectangle(frame_cpu, facesBuf_cpu[i], Scalar(255));
    }
    if(facesBuf_cpu.size())
    {
        return true;
    }
    else
    {
        return false;
    }
}

int detectFaceGpu(Mat &frame)
{
    GpuMat frame_gpu(frame);
    GpuMat gray_gpu;
    //转化成灰度图
    if (frame_gpu.channels() == 3)
    {
        cvtColor(frame_gpu, gray_gpu, CV_BGR2GRAY );
    }
    else
    {
        gray_gpu = frame_gpu;
    }
    GpuMat facesBuf_gpu;
    Mat faces_downloaded;

    cascade_gpu.findLargestObject = true;
    int detections_num = 
        cascade_gpu.detectMultiScale(gray_gpu, facesBuf_gpu, 1.2, 4);

    facesBuf_gpu.colRange(0, detections_num).download(faces_downloaded);

    for (int i = 0; i < detections_num; ++i)
    {
        rectangle(frame, faces_downloaded.ptr<cv::Rect>()[i], Scalar(255));
    }

    if(detections_num)
    {
        return true;
    }
    else 
    {
        return false;
    }
}

void decompound_cpu(string in,string out_1, string out_2)
{
    //摄像头对象
    CvCapture *capture = cvCreateFileCapture(in.c_str());
    int w = 640, h = 480;
    cvSetCaptureProperty ( capture, CV_CAP_PROP_FRAME_WIDTH,  w );
    cvSetCaptureProperty ( capture, CV_CAP_PROP_FRAME_HEIGHT, h );

    CvVideoWriter * writer1 = 
        cvCreateVideoWriter(out_1.c_str(),CV_FOURCC('X','V','I','D'),20,cvSize(w,h));
    CvVideoWriter * writer2 = 
        cvCreateVideoWriter(out_2.c_str(),CV_FOURCC('X','V','I','D'),20,cvSize(w,h));
    IplImage* frame;
    cvNamedWindow("Camera_1", CV_WINDOW_AUTOSIZE );
    cvNamedWindow("Camera_2", CV_WINDOW_AUTOSIZE );
    static int i = 0;
    while(1)
    {
        frame = cvQueryFrame(capture);
        Mat mat(frame);
        if(mat.empty())
        {
            printf("finish !!!
");
            break;
        }

        if(detectFaceGpu(mat))
        {
            cvShowImage("Camera_1", frame);
            printf("y = %d
", i++);
            cvWriteFrame(writer1, frame); //写入文件
        }
        else 
        {
            printf("n = %d
", i++);
            cvShowImage( "Camera_2", frame);
            cvWriteFrame(writer2, frame); //写入文件
        }

        int key = cvWaitKey(2);
        if( key == 27 ) break;
    }
    cvReleaseVideoWriter(&writer1);
    cvReleaseVideoWriter(&writer2);
    cvReleaseCapture(&capture);
    cvDestroyWindow("Camera_1");
    cvDestroyWindow("Camera_2");
}

bool init()
{
    string path = getWorkspace() + "/haarcascade_frontalface_alt.xml";
    if (!cascade_cpu.load(path))
    {
        printf("error cascade_cpu load
");
        return 0;
    }

    if (!cascade_gpu.load(path))
    {
        printf("errror cascade_gpu load
");
        return 0;
    }
    return true;
}

int main(int argc, char* argv[])
{
    init();
    string x1 = getWorkspace() + string("/4.avi");
    string x2 = getWorkspace() + string("/image_output/4_1.avi");
    string x3 = getWorkspace() + string("/image_output/4_2.avi");
    decompound_cpu(x1,x2,x3);
    return 0;
}

View Code

五从视频流中提取出某个人的视频来

#include <iostream>
#include <iomanip>
#include "opencv2/core/core.hpp"
#include "opencv2/contrib/contrib.hpp"
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc_c.h"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/gpu/gpu.hpp"
#include <stdio.h>
#include <time.h>
#include "personName.h"
#include "util.h"

using namespace std;
using namespace cv;
using namespace cv::gpu;

CascadeClassifier cascade_cpu;//使用cpu的分类器器
CascadeClassifier_GPU cascade_gpu;//使用cpu的分类器器
int predict_id = -10;
float s_confidence = 2000;
IplImage * getFace(IplImage *img, CvRect rect)
{
    static int id = 1;
    cvSetImageROI(img,rect);  
    IplImage *tmp;
    tmp=cvCreateImage(cvSize(80,80),IPL_DEPTH_8U,1);
    cvResize(img,tmp,CV_INTER_LINEAR); 
    cvResetImageROI(img);  
    return tmp;
}

int predict(Mat &mat)
{
    static bool init = true;
    static Ptr<FaceRecognizer> model;
    if(init)
    {
        model = createEigenFaceRecognizer(200);
        string str = getWorkspace() + string("/face.xml");
        model->load(str.c_str());
        init = false;
    }

    int predictedLabel = -1;
    double confidence = 0.0;

    model->predict(mat, predictedLabel, confidence);

    string result_message = format("%10s confidence = %lf", PersonName::build()->getName(predictedLabel).c_str(), confidence);
    printf("%s
",result_message.c_str());
    if(confidence < s_confidence) return predictedLabel;
    else return -1;
}

bool detectFaceCpu(Mat &frame_cpu)
{
    Mat gray_cpu;
    //转化成灰度图
    if (frame_cpu.channels() == 3)
    {
        cvtColor(frame_cpu, gray_cpu, CV_BGR2GRAY );
    }
    else
    {
        gray_cpu = frame_cpu;
    }
    vector<Rect> facesBuf_cpu;

    cascade_cpu.detectMultiScale(gray_cpu, facesBuf_cpu, 1.2, 4);

    IplImage img(gray_cpu);
    for(size_t i = 0; i < facesBuf_cpu.size();i++)
    {
        rectangle(frame_cpu, facesBuf_cpu[i], Scalar(255));
        Mat tmp(getFace(&img, facesBuf_cpu[i]));
        int id = predict(tmp);
        if(id != predict_id)continue;
        return true;
    }
    return false;
}

int detectFaceGpu(Mat &frame)
{
    GpuMat frame_gpu(frame);
    GpuMat gray_gpu;
    Mat gray_cpu;
    //转化成灰度图
    if (frame_gpu.channels() == 3)
    {
        cvtColor(frame_gpu, gray_gpu, CV_BGR2GRAY);
        cvtColor(frame, gray_cpu, CV_BGR2GRAY);
    }
    else
    {
        gray_gpu = frame_gpu;
        gray_cpu = frame;
    }
    GpuMat facesBuf_gpu;
    Mat faces_downloaded;

    cascade_gpu.findLargestObject = true;
    int detections_num = 
        cascade_gpu.detectMultiScale(gray_gpu, facesBuf_gpu, 1.2, 4);

    facesBuf_gpu.colRange(0, detections_num).download(faces_downloaded);

    IplImage img(gray_cpu);
    for (int i = 0; i < detections_num; ++i)
    {
        rectangle(frame, faces_downloaded.ptr<cv::Rect>()[i], Scalar(255));
        Mat tmp(getFace(&img, faces_downloaded.ptr<cv::Rect>()[i]));
        int id = predict(tmp);
        if(id != predict_id)continue;
        return true;
    }
    return false;
}

void decompound_cpu(string in,string out_1, string out_2)
{
    //摄像头对象
    CvCapture *capture = cvCreateFileCapture(in.c_str());
    int w = 640, h = 480;
    cvSetCaptureProperty ( capture, CV_CAP_PROP_FRAME_WIDTH,  w );
    cvSetCaptureProperty ( capture, CV_CAP_PROP_FRAME_HEIGHT, h );

    CvVideoWriter * writer1 = 
        cvCreateVideoWriter(out_1.c_str(),CV_FOURCC('X','V','I','D'),20,cvSize(w,h));
    CvVideoWriter * writer2 = 
        cvCreateVideoWriter(out_2.c_str(),CV_FOURCC('X','V','I','D'),20,cvSize(w,h));
    IplImage* frame;
    cvNamedWindow("Camera_1", CV_WINDOW_AUTOSIZE );
    cvNamedWindow("Camera_2", CV_WINDOW_AUTOSIZE );
    static int i = 0;
    while(1)
    {
        frame = cvQueryFrame(capture);
        Mat mat(frame);
        if(mat.empty())
        {
            printf("finish !!!
");
            break;
        }

        if(detectFaceGpu(mat))
        {
            cvShowImage("Camera_1", frame);
            printf("y = %d
", i++);
            cvWriteFrame(writer1, frame); //写入文件
        }
        else 
        {
            printf("n = %d
", i++);
            cvShowImage( "Camera_2", frame);
            cvWriteFrame(writer2, frame); //写入文件
        }

        int key = cvWaitKey(2);
        if( key == 27 ) break;
    }
    cvReleaseVideoWriter(&writer1);
    cvReleaseVideoWriter(&writer2);
    cvReleaseCapture(&capture);
    cvDestroyWindow("Camera_1");
    cvDestroyWindow("Camera_2");
}

bool init()
{
    predict_id = 1;
    s_confidence = 2000;
    string path = getWorkspace() + "/haarcascade_frontalface_alt.xml";
    if (!cascade_cpu.load(path))
    {
        printf("error cascade_cpu load
");
        return 0;
    }

    if (!cascade_gpu.load(path))
    {
        printf("errror cascade_gpu load
");
        return 0;
    }
    return true;
}

int main(int argc, char* argv[])
{
    init();
    string x1 = getWorkspace() + string("/17.avi");
    string x2 = getWorkspace() + string("/image_output/17_1.avi");
    string x3 = getWorkspace() + string("/image_output/17_2.avi");
    decompound_cpu(x1,x2,x3);
    return 0;
}

View Code

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原文地址：https://www.cnblogs.com/zhxfl/p/3243614.html