原文链接 https://jamling.github.io/2011/08/01/Android-Android-Complie-OpenCV/
注：以下为加速网络访问所做的原文缓存，经过重新格式化，可能存在格式方面的问题，或偶有遗漏信息，请以原文为准。
简介
在linuxt系统下使用OpenCV2.3 + NDK R6编译 OpenCV人脸检测应用 <!-- more -->
准备
- Android NDK ( r5或更高版本) 下载地址：http://developer.android.com/sdk/ndk/index.html
- OpenCV Android包 http://sourceforge.net/projects/opencvlibrary/files/opencv-android/2.3/
- cmake(可选，替代NDK) 参考：http://www.cmake.org/
注：http://code.google.com/p/android-opencv/网站上说要使用crystax ndk r4代替NDK。估计可能是对于较旧的Android版本需要这样。如果NDK无法编译，请尝试使用crystax ndk r4编译。
OpenCV设置
从网站上下载OpenCV 2.3.0 for Android 后，解压到某个目录，如~/目录下
设置OPENCV_PACKAGE_DIR环境变量
$ export OPENCV_PACKAGE_DIR=~/enCV-2.3.0/
步骤
新建一个Android工程
在eclipse中新建一个android 工程如study.opencv，并且在工程根目录下新建一个名为jni的目录。将下载的android-ndk-r6解压到某个目录下，如~/ 从~/android-ndk-r6/sample下某个sample中拷贝Android.mk, Application.mk到study.opencv/jni目录
设置编译脚本
在Android.mk中，include $(CLEAR_VARS)后面，加入下行
include $(OPENCV_PACKAGE_DIR)/$(TARGET_ARCH_ABI)/share/opencv/OpenCV.mk
如果应用支持ARM NEON那么还需要加入以下行
include $(OPENCV_PACKAGE_DIR)/armeabi-v7a-neon/share/opencv/OpenCV.mk
LOCAL_ARM_NEON := true
在Application.mk中加入以下行
APP_STL := gnustl_static
APP_CPPFLAGS := -frtti -fexceptions
注：关于Android.mk与Application.mk的详细说明，请参考ndk/docs下Android-mk.html和Application-mk.html。
Java层定义native接口
新建study.opencv.FaceRec类，定义一个人脸检测的本地接口
/**
* detect front face from image.
*
* @param xml
* opencv haarcascade xml file path
* @param infile
* input image file path
* @param outfile
* output image file path
*/
public native void detect(String xml, String infile, String outfile);
生成jni头文件
使用javah命令生成jni头文件
$ cd ~/workspace/study.opencv/bin
$ javah study.opencv.FaceRec
会在bin目录生成一个study_opencv_FaceRec.h文件。将此文件拷贝到../jni目录中
注：如果接口有变更，请先手动删除生成的.h文件。以防止一些意外的错误。
在c层实现图像人脸检测
在jni目录中使用文本编辑器新建一个facedetect.cpp，实现图像人脸检测
#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>
#include <android/log.h>
#include <study_opencv_FaceRec.h>
#include <jni.h>
#define LOG_TAG "opencv_face_detect"
#define LOGI(...) __android_log_print(ANDROID_LOG_INFO,LOG_TAG,__VA_ARGS__)
#define LOGE(...) __android_log_print(ANDROID_LOG_ERROR,LOG_TAG,__VA_ARGS__)
static CvMemStorage* storage = 0;
static CvHaarClassifierCascade* cascade = 0;
void detect_and_draw( IplImage* image );
const char* cascade_name =
"haarcascade_frontalface_alt.xml";
/* "haarcascade_profileface.xml";*/
/*int captureFromImage(char* xml, char* filename);*/
char* jstring2String(JNIEnv*, jstring);
int captureFromImage(char* xml, char* filename, char* outfile)
{
LOGI("begin: ");
// we just detect image
// CvCapture* capture = 0;
IplImage *frame, *frame_copy = 0;
const char* input_name = "lina.png";
if(xml != NULL)
{
cascade_name = xml;
}
if(filename != NULL)
{
input_name = filename;
}
LOGI("xml=%s,filename=%s", cascade_name, input_name);
// load xml
cascade = (CvHaarClassifierCascade*)cvLoad( cascade_name, 0, 0, 0 );
LOGI("load cascade ok ? %d", cascade != NULL ? 1 : 0);
if( !cascade )
{
LOGI("ERROR: Could not load classifier cascade\n" );
// I just won't write long full file path, to instead of relative path, but I failed.
FILE * fp = fopen(input_name,"w");
if(fp == NULL){
LOGE("create failed");
}
return -1;
}
storage = cvCreateMemStorage(0);
// cvNamedWindow( "result", 1 );
IplImage* image = cvLoadImage( input_name, 1 );
if( image )
{
LOGI("load image successfully");
detect_and_draw( image );
// cvWaitKey(0);
if(outfile != NULL)
{
LOGI("after detected save image file");
cvSaveImage(outfile, image);//把图像写入文件
}
cvReleaseImage( &image );
}
else
{
LOGE("can't load image from : %s ", input_name);
}
}
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}}
};
double scale = 1.3;
IplImage* gray = cvCreateImage( cvSize(img->width,img->height), 8, 1 );
IplImage* small_img = cvCreateImage( cvSize( cvRound (img->width/scale),
cvRound (img->height/scale)),
8, 1 );
int i;
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_DO_CANNY_PRUNING*/,
cvSize(30, 30) );
t = (double)cvGetTickCount() - t;
LOGI( "detection time = %gms\n", t/((double)cvGetTickFrequency()*1000.) );
for( i = 0; i < (faces ? faces->total : 0); i++ )
{
CvRect* r = (CvRect*)cvGetSeqElem( faces, i );
CvPoint center;
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, colors[i%8], 3, 8, 0 );
}
}
// cvShowImage( "result", img );
cvReleaseImage( &gray );
cvReleaseImage( &small_img );
}
JNIEXPORT void JNICALL Java_study_opencv_FaceRec_detect
(JNIEnv * env, jobject obj, jstring xml, jstring filename, jstring outfile)
{
LOGI("top method invoked! ");/*LOGI("1");
char * c_xml = (char *)env->GetStringUTFChars(xml, JNI_FALSE);
LOGI("char * = %s", c_xml);
if(c_xml == NULL)
{
LOGI("error in get char*");
return;
}
char * c_file = env->GetStringCritical(env, filename, 0);
if(c_xml == NULL)
{
LOGI("error in get char*");
return;
}
captureFromImage(c_xml, c_file);
env->ReleaseStringCritical(env, xml, c_xml);
env->ReleaseStringCritical(env, file_name, c_file);
*/
captureFromImage(jstring2String(env,xml), jstring2String(env,filename), jstring2String(env,outfile));
}
//jstring to char*
char* jstring2String(JNIEnv* env, jstring jstr)
{
if(jstr == NULL)
{
LOGI("NullPointerException!");
return NULL;
}
char* rtn = NULL;
jclass clsstring = env->FindClass("java/lang/String");
jstring strencode = env->NewStringUTF("utf-8");
jmethodID mid = env->GetMethodID(clsstring, "getBytes", "(Ljava/lang/String;)[B");
jbyteArray barr= (jbyteArray)env->CallObjectMethod(jstr, mid, strencode);
jsize alen = env->GetArrayLength(barr);
jbyte* ba = env->GetByteArrayElements(barr, JNI_FALSE);
if (alen > 0)
{
rtn = (char*)malloc(alen + 1);
memcpy(rtn, ba, alen);
rtn[alen] = 0;
}
env->ReleaseByteArrayElements(barr, ba, 0);
LOGI("char*=%s",rtn);
return rtn;
}
Android.mk:
LOCAL_PATH:= $(call my-dir)
include $(CLEAR_VARS)
include $(OPENCV_PACKAGE_DIR)/$(TARGET_ARCH_ABI)/share/opencv/OpenCV.mk
LOCAL_MODULE := facedetect
LOCAL_CFLAGS := -Werror
LOCAL_SRC_FILES := \
facedetect.cpp \
LOCAL_LDLIBS := -llog
include $(BUILD_SHARED_LIBRARY)
Application.mk:
APP_ABI := armeabi armeabi-v7a
APP_PLATFORM := android-10
APP_STL := gnustl_static
APP_CPPFLAGS := -frtti -fexceptions
使用NDK进行编译
在工程jni目录下执行ndk-build
$ cd ~/workspace/study.opencv/jni
$ ~/android-ndk-r6/ndk-build.
如果编译成功，则会在工程下面生成libs/armeabi/facedetect.so库了. 如有编译失败，请根据提示修改错误
调用JNI接口
将opencv人脸检测要用到的xml文件(位于OpenCV-2.3.0/armeabi/share/opencv/haarcascades/目录下)及图像文件使用DDMS push到data/data/study.opencv/files目录中。
在activity中新建一个线程，调用FaceRec#detect方法。
@Override
public void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
setContentView(R.layout.main);
final FaceRec face = new FaceRec();
new Thread() {
@Override
public void run() {
face.detect(
"/data/data/study.opencv/files/haarcascade_frontalface_alt2.xml",
"/data/data/study.opencv/files/wqw1.jpg",
"/data/data/study.opencv/files/wqw1_detected.jpg");
}
}.start();
}
运行结果
经测试，对png,jpg,bmp图片可以正确识别，不过就是速度有点慢。
参考
- 人脸检测 http://www.opencv.org.cn/index.php/%E4%BA%BA%E8%84%B8%E6%A3%80%E6%B5%8B