我是 OpenCV 的初学者。我正在尝试做一个示例 android 应用程序来使用 OpenCV 检测给定图像中的嘴巴。我在互联网上搜索，但找不到满足我要求的合适的 android 或 java 代码。但我有 C++ 代码。我不知道如何翻译它。
http://opencvfacedetect.blogspot.com/2010/10/face-detectionfollowed-by-eyesnose.html
你能帮我找到合适的 java 或 android 代码吗？或者请帮助我将此 C++ 代码翻译成 java，我可以在 android 应用程序中使用它。
提前谢谢你。
C++代码
/* program to detect facial features using opencv*/
/* detectFacialfeatures() is the main function that detects the face followed by Eyes,nose and mouth detection.*/
#include "stdafx.h"
/**
* Loads static images from database and detect faces
*/
#include <stdio.h>
#include<conio.h>
#include "cv.h"
#include "highgui.h"
#include "cvaux.h"
CvHaarClassifierCascade *cascade,*cascade_e,*cascade_nose,*cascade_mouth;
CvMemStorage *storage;
char *face_cascade="haarcascade_frontalface_alt2.xml";
char *eye_cascade="haarcascade_mcs_eyepair_big.xml";
char *nose_cascade="haarcascade_mcs_nose.xml";
char *mouth_cascade="haarcascade_mcs_mouth.xml";
/*Mouth detect ion*/
void detectMouth( IplImage *img,CvRect *r)
{
CvSeq *mouth;
//mouth detecetion - set ROI
cvSetImageROI(img,/* the source image */
cvRect(r->x, /* x = start from leftmost */
r->y+(r->height *2/3), /* y = a few pixels from the top */
r->width, /* width = same width with the face */
r->height/3 /* height = 1/3 of face height */
)
);
mouth = cvHaarDetectObjects(img,/* the source image, with the estimated location defined */
cascade_mouth, /* the eye classifier */
storage, /* memory buffer */
1.15, 4, 0, /* tune for your app */
cvSize(25, 15) /* minimum detection scale */
);
for( int i = 0; i < (mouth ? mouth->total : 0); i++ )
{
CvRect *mouth_cord = (CvRect*)cvGetSeqElem(mouth, i);
/* draw a red rectangle */
cvRectangle(img,
cvPoint(mouth_cord->x, mouth_cord->y),
cvPoint(mouth_cord->x + mouth_cord->width, mouth_cord->y + mouth_cord->height),
CV_RGB(255,255, 255),
1, 8, 0
);
}
//end mouth detection
}
/*Nose detection*/
void detectNose( IplImage *img,CvRect *r)
{
CvSeq *nose;
//nose detection- set ROI
cvSetImageROI(img, /* the source image */
cvRect(r->x, /* x = start from leftmost */
r->y , /* y = a few pixels from the top */
r->width, /* width = same width with the face */
r->height /* height = 1/3 of face height */
)
);
nose = cvHaarDetectObjects(img, /* the source image, with the estimated location defined */
cascade_nose, /* the eye classifier */
storage, /* memory buffer */
1.15, 3, 0, /* tune for your app */
cvSize(25, 15) /* minimum detection scale */
);
for( int i = 0; i < (nose ? nose->total : 0); i++ )
{
CvRect *nose_cord = (CvRect*)cvGetSeqElem(nose, i);
/* draw a red rectangle */
cvRectangle(img,
cvPoint(nose_cord->x, nose_cord->y),
cvPoint(nose_cord->x + nose_cord->width, nose_cord->y + nose_cord->height),
CV_RGB(0,255, 0),
1, 8, 0
);
}
}
/*Eyes detection*/
void detectEyes( IplImage *img,CvRect *r)
{
char *eyecascade;
CvSeq *eyes;
int eye_detect=0;
//eye detection starts
/* Set the Region of Interest: estimate the eyes' position */
cvSetImageROI(img, /* the source image */
cvRect
(
r->x, /* x = start from leftmost */
r->y + (r->height/5.5), /* y = a few pixels from the top */
r->width, /* width = same width with the face */
r->height/3.0 /* height = 1/3 of face height */
)
);
/* detect the eyes */
eyes = cvHaarDetectObjects( img, /* the source image, with the estimated location defined */
cascade_e, /* the eye classifier */
storage, /* memory buffer */
1.15, 3, 0, /* tune for your app */
cvSize(25, 15) /* minimum detection scale */
);
printf("\no of eyes detected are %d",eyes->total);
/* draw a rectangle for each detected eye */
for( int i = 0; i < (eyes ? eyes->total : 0); i++ )
{
eye_detect++;
/* get one eye */
CvRect *eye = (CvRect*)cvGetSeqElem(eyes, i);
/* draw a red rectangle */
cvRectangle(img,
cvPoint(eye->x, eye->y),
cvPoint(eye->x + eye->width, eye->y + eye->height),
CV_RGB(0, 0, 255),
1, 8, 0
);
}
}
void detectFacialFeatures( IplImage *img,IplImage *temp_img,int img_no)
{
char image[100],msg[100],temp_image[100];
float m[6];
double factor = 1;
CvMat M = cvMat( 2, 3, CV_32F, m );
int w = (img)->width;
int h = (img)->height;
CvSeq* faces;
CvRect *r;
m[0] = (float)(factor*cos(0.0));
m[1] = (float)(factor*sin(0.0));
m[2] = w*0.5f;
m[3] = -m[1];
m[4] = m[0];
m[5] = h*0.5f;
cvGetQuadrangleSubPix(img, temp_img, &M);
CvMemStorage* storage=cvCreateMemStorage(0);
cvClearMemStorage( storage );
if( cascade )
faces = cvHaarDetectObjects(img,cascade, storage, 1.2, 2, CV_HAAR_DO_CANNY_PRUNING, cvSize(20, 20));
else
printf("\nFrontal face cascade not loaded\n");
printf("\n no of faces detected are %d",faces->total);
/* for each face found, draw a red box */
for(int i = 0 ; i < ( faces ? faces->total : 0 ) ; i++ )
{
r = ( CvRect* )cvGetSeqElem( faces, i );
cvRectangle( img,cvPoint( r->x, r->y ),cvPoint( r->x + r->width, r->y + r->height ),
CV_RGB( 255, 0, 0 ), 1, 8, 0 );
printf("\n face_x=%d face_y=%d wd=%d ht=%d",r->x,r->y,r->width,r->height);
detectEyes(img,r);
/* reset region of interest */
cvResetImageROI(img);
detectNose(img,r);
cvResetImageROI(img);
detectMouth(img,r);
cvResetImageROI(img);
}
/* reset region of interest */
cvResetImageROI(img);
if(faces->total>0)
{
sprintf(image,"D:\\face_output\\%d.jpg",img_no);
cvSaveImage( image, img );
}
}
int main( int argc, char** argv )
{
CvCapture *capture;
IplImage *img,*temp_img;
int key;
char image[100],temp_image[100];
/* load the classifier
note that I put the file in the same directory with
this code */
storage = cvCreateMemStorage( 0 );
cascade = ( CvHaarClassifierCascade* )cvLoad( face_cascade, 0, 0, 0 );
cascade_e = ( CvHaarClassifierCascade* )cvLoad( eye_cascade, 0, 0, 0 );
cascade_nose = ( CvHaarClassifierCascade* )cvLoad( nose_cascade, 0, 0, 0 );
cascade_mouth = ( CvHaarClassifierCascade* )cvLoad( mouth_cascade, 0, 0, 0 );
if( !(cascade || cascade_e ||cascade_nose||cascade_mouth) )
{
fprintf( stderr, "ERROR: Could not load classifier cascade\n" );
return -1;
}
for(int j=20;j<27;j++)
{
sprintf(image,"D:\\ptz images\\%d.jpg",j);
img=cvLoadImage(image);
temp_img=cvLoadImage(image);
if(!img)
{
printf("Could not load image file and trying once again: %s\n",image);
}
printf("\n curr_image = %s",image);
detectFacialFeatures(img,temp_img,j);
}
cvReleaseHaarClassifierCascade( &cascade );
cvReleaseHaarClassifierCascade( &cascade_e );
cvReleaseHaarClassifierCascade( &cascade_nose );
cvReleaseHaarClassifierCascade( &cascade_mouth );
cvReleaseMemStorage( &storage );
cvReleaseImage(&img);
cvReleaseImage(&temp_img);
return 0;
}
最佳答案
有一个 Opencv 3.0 的 android 预建端口。 http://opencv.org/downloads.html
opencv 中的大部分工作都是在 C++ 上编程的。
有Java的例子，比如(相当简单)中的face Detector。我不确定是否有口眼检测器。
此外，您还可以使用您的代码，通过 JNI 编写 android 应用程序。
一开始(JNI)相当复杂，但却是获得应用程序最大性能的最优雅的方式。此外，您几乎可以确定 opencv 桌面功能在 android 上。
检查此链接: https://github.com/googlesamples/android-ndk/tree/master/hello-jni
https://developer.android.com/ndk/samples/sample_hellojni.html?hl=es 希望此引用资料有所帮助。
干杯。
关于java - Android 中用于人脸检测(随后是眼睛、 Nose 和嘴巴检测)的 OpenCV 代码，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/37692655/