opencv使用,人臉識別,java使用opencv

遇到opencv，使用後，列一下。

(當然據說目前挺火的 綠壩 用的就是這個)

 

opencv是個圖形函數庫，內容豐富。是Intel資助的開源計算機視覺庫。

由一系列 C 函數和少量 C++ 類構成，實現了圖像處理和計算機視覺方面的很多通用算法。
OpenCV 對非商業應用和商業應用都是免費（FREE）的。

 

 

相關網站：

 

http://www.opencv.org.cn

 

http://sourceforge.net/projects/opencvlibrary/

 

http://tech.groups.yahoo.com/group/OpenCV/

 

 

下載下來後，例子直接運行。

 

有些情況，比如提供的例子運行出錯，需要重新編譯。

 

 

 

windows下，vc6，重編譯時有錯誤，是源程序裏有個註釋寫錯了位置，改了可以了，編譯有順序，一般提示...d文件找不到，順藤摸瓜的找到源文件，編譯就可以。

 

 

有個face檢測的程序有意思：

可以檢測人臉。

直接調用人臉檢測函數。非常簡單

人臉檢測時2002年的論文？後來加入了側臉檢測？

 

#include "cv.h"
#include "highgui.h"

#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <assert.h>
#include <math.h>
#include <float.h>
#include <limits.h>
#include <time.h>
#include <ctype.h>

#ifdef _EiC
#define WIN32
#endif

static CvMemStorage* storage = 0;
static CvHaarClassifierCascade* cascade = 0;
static CvHaarClassifierCascade* nested_cascade = 0;
int use_nested_cascade = 0;

void detect_and_draw( IplImage* image );

const char* cascade_name ="1.xml";
   // "../../data/haarcascades/haarcascade_frontalface_alt_tree.xml";
/*    "";haarcascade_profileface.xml*/
const char* nested_cascade_name ="2.xml";
 //   "../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml";
//    "../../data/haarcascades/";
double scale = 1;

int main( int argc, char** argv )
{
    CvCapture* capture = 0;
    IplImage *frame, *frame_copy = 0;
    IplImage *image = 0;
    const char* scale_opt = "--scale=";
    int scale_opt_len = (int)strlen(scale_opt);
    const char* cascade_opt = "--cascade=";
    int cascade_opt_len = (int)strlen(cascade_opt);
    const char* nested_cascade_opt = "--nested-cascade";
    int nested_cascade_opt_len = (int)strlen(nested_cascade_opt);
    int i;
    const char* input_name = 0;

            input_name = argv[1];
  

    cascade = (CvHaarClassifierCascade*)cvLoad( cascade_name, 0, 0, 0 );

    if( !cascade )
    {
        fprintf( stderr, "ERROR: Could not load classifier cascade/n" );
        fprintf( stderr,
        "Usage: facedetect [--cascade=/"<cascade_path>/"]/n"
        "   [--nested-cascade[=/"nested_cascade_path/"]]/n"
        "   [--scale[=<image scale>/n"
        "   [filename|camera_index]/n" );
        return -1;
    }
   
    if( !input_name || (isdigit(input_name[0]) && input_name[1] == '/0') )
        capture = cvCaptureFromCAM( !input_name ? 0 : input_name[0] - '0' );
    else if( input_name )
    {

    storage = cvCreateMemStorage(0);        image = cvLoadImage( input_name, 1 );
        if( !image )
            capture = cvCaptureFromAVI( input_name );
    }
    else
        image = cvLoadImage( "lena.jpg", 1 );

    cvNamedWindow( "result", 1 );

    if( capture )
    {
        for(;;)
        {
            if( !cvGrabFrame( capture ))
                break;
            frame = cvRetrieveFrame( capture );
            if( !frame )
                break;
            if( !frame_copy )
                frame_copy = cvCreateImage( cvSize(frame->width,frame->height),
                                            IPL_DEPTH_8U, frame->nChannels );
            if( frame->origin == IPL_ORIGIN_TL )
                cvCopy( frame, frame_copy, 0 );
            else
                cvFlip( frame, frame_copy, 0 );
           
            detect_and_draw( frame_copy );

            if( cvWaitKey( 10 ) >= 0 )
                goto _cleanup_;
        }

        cvWaitKey(0);
_cleanup_:
        cvReleaseImage( &frame_copy );
        cvReleaseCapture( &capture );
    }
    else
    {
        if( image )
        {
  
            detect_and_draw( image );
           cvShowImage( "result", image );
            cvWaitKey(0);
            cvReleaseImage( &image );
        }
        else if( input_name )
        {
            /* assume it is a text file containing the
               list of the image filenames to be processed - one per line */
            FILE* f = fopen( input_name, "rt" );
            if( f )
            {
                char buf[1000+1];
                while( fgets( buf, 1000, f ) )
                {
                    int len = (int)strlen(buf), c;
                    while( len > 0 && isspace(buf[len-1]) )
                        len--;
                    buf[len] = '/0';
                    printf( "file %s/n", buf );
                    image = cvLoadImage( buf, 1 );
                    if( image )
                    {
                        detect_and_draw( image );
                        c = cvWaitKey(0);
                        if( c == 27 || c == 'q' || c == 'Q' )
                            break;
                        cvReleaseImage( &image );
                    }
                }
                fclose(f);
            }
        }
    }
   
    cvDestroyWindow("result");

    return 0;
}

void detect_and_draw( IplImage* img )
{
    static CvScalar colors[] =
    {
        {{0,0,255}},
        {{0,128,255}},
        {{0,255,255}},
        {{0,255,0}},
        {{255,128,0}},
        {{255,255,0}},
        {{255,0,0}},
        {{255,0,255}}
    };

    IplImage *gray, *small_img;
    int i, j;

    gray = cvCreateImage( cvSize(img->width,img->height), 8, 1 );
    small_img = cvCreateImage( cvSize( cvRound (img->width/scale),
                         cvRound (img->height/scale)), 8, 1 );

    cvCvtColor( img, gray, CV_BGR2GRAY );
    cvResize( gray, small_img, CV_INTER_LINEAR );
    cvEqualizeHist( small_img, small_img );
    cvClearMemStorage( storage );

    if( cascade )
    {
        double t = (double)cvGetTickCount();
        CvSeq* faces = cvHaarDetectObjects( small_img, cascade, storage,
                                            1.1, 2, 0
                                            //|CV_HAAR_FIND_BIGGEST_OBJECT
                                            //|CV_HAAR_DO_ROUGH_SEARCH
                                            |CV_HAAR_DO_CANNY_PRUNING
                                            //|CV_HAAR_SCALE_IMAGE
                                            ,
                                            cvSize(30, 30) );
        t = (double)cvGetTickCount() - t;
        printf( "detection time = %gms/n", t/((double)cvGetTickFrequency()*1000.) );
        for( i = 0; i < (faces ? faces->total : 0); i++ )
        {
            CvRect* r = (CvRect*)cvGetSeqElem( faces, i );
            CvMat small_img_roi;
            CvSeq* nested_objects;
            CvPoint center;
            CvScalar color = colors[i%8];
            int radius;
            center.x = cvRound((r->x + r->width*0.5)*scale);
            center.y = cvRound((r->y + r->height*0.5)*scale);
            radius = cvRound((r->width + r->height)*0.25*scale);
  
            cvCircle( img, center, radius, color, 3, 8, 0 );
   

            if( !nested_cascade )
                continue;
            cvGetSubRect( small_img, &small_img_roi, *r );
            nested_objects = cvHaarDetectObjects( &small_img_roi, nested_cascade, storage,
                                        1.1, 2, 0
                                        //|CV_HAAR_FIND_BIGGEST_OBJECT
                                        //|CV_HAAR_DO_ROUGH_SEARCH
                                        //|CV_HAAR_DO_CANNY_PRUNING
                                        //|CV_HAAR_SCALE_IMAGE
                                        ,
                                        cvSize(0, 0) );
            for( j = 0; j < (nested_objects ? nested_objects->total : 0); j++ )
            {
                CvRect* nr = (CvRect*)cvGetSeqElem( nested_objects, j );
                center.x = cvRound((r->x + nr->x + nr->width*0.5)*scale);
                center.y = cvRound((r->y + nr->y + nr->height*0.5)*scale);
                radius = cvRound((nr->width + nr->height)*0.25*scale);
                cvCircle( img, center, radius, color, 3, 8, 0 );

            }
        }
    }

    cvShowImage( "result", img );
    cvReleaseImage( &gray );
    cvReleaseImage( &small_img );
}

 

 

相關數據。

haarcascade_frontalface_alt1.xml等

是人臉檢測用的人的眼睛，鼻子等數據。

當然可以改名或使用你自己的。

 

 

java使用opencv

用JNI2OpenCV.dll:

FaceDetection.java

 

class JNIOpenCV {
    static {
        System.loadLibrary("JNI2OpenCV");
    }
    public native int[] detectFace(int minFaceWidth, int minFaceHeight, String cascade, String filename);
}

public class FaceDetection {
 private JNIOpenCV myJNIOpenCV;
 private FaceDetection myFaceDetection;
 
 public FaceDetection() {
  myJNIOpenCV = new JNIOpenCV();
  String filename = "5.jpg";
  String cascade = "haarcascade_frontalface_default.xml";
  
    int[] detectedFaces = myJNIOpenCV.detectFace(40, 40, cascade, filename);
    int numFaces = detectedFaces.length / 4;
   
     System.out.println("numFaces = " + numFaces);
     for (int i = 0; i < numFaces; i++) {
      System.out.println("Face " + i + ": " + detectedFaces[4 * i + 0] + " " + detectedFaces[4 * i + 1] + " " + detectedFaces[4 * i + 2] + " " + detectedFaces[4 * i + 3]);
     }
 }
   
    public static void main(String args[]) {
        FaceDetection myFaceDetection = new FaceDetection();  
    }
}

就可以在java中實現人臉識別了。

 

 

第一副圖是c語言的人臉識別效果。

 

 

第二幅圖是java版的效果。

 

 

 

 

 

相關文件備份：

http://www.namipan.com/d/a0d6b376810bf6b02c977435be95fb9d55a95fe4540d3c00

有運行不了的情況，是要重編譯opencv

 

題外話：(當然據說目前挺火的綠壩用的就是這個)

“從XFImage.xml可觀察到，綠霸使用了OpenCV的haar分類器進行人臉檢測。綠霸附帶的cximage.dll、CImage.dll、xcore.dll和Xcv.dll也來自OpenCV的庫文件。都反映出綠霸主要使用了OpenCV來進行圖像方面的處理。綠霸也無視了OpenCV的BSD許可證。”