1.下载
首先先去官网 /opencv-3-2.html 下载 Android SDK: sourceforge ，下载下来以后我们的开发方式目前有两种：一种是基于 OpenCV_3.2.0_Manager.apk 的纯 Java 代码；还有一种方式是配置好 opencv 后利用 Android NDK，使用C++开发。
解压下载好的文件夹后
image.png
apk：OpenCV_3.2.0_Manager 可以说是一个服务 apk , 网上的所有代码都是基于 OpenCV_3.2.0_Manager，也就是说你必须运行这个 apk
samples：所有的与android相关的一些事例代码，基本全部都是 java 代码，封装了很多功能(图片转成灰度，高斯模糊，边缘检测)，而且都是 Eclipse 版本，网上的例子(Java例子)
sdk：所有的资源，so库，头文件，源码(GitHub /opencv/opencv)
2. 人脸识别实现的思路 (人脸登录)
2.1 人脸信息录入
2.1.1 获取相机的 Bitmap , 检测人脸(保证人脸特征信息比较精准)人脸要足够大，当前范围内人脸只能有一张人脸，比如：正常、眨眼睛、张嘴巴 (3张人脸信息)
2.1.2 获取到人脸必须要保存人脸特征信息，然后上传给后台(后台会再次做算法优化)，保存到数据库
2.2 人脸的特征值的匹配
2.2.1 获取相机的 Bitmap , 检测人脸(保证人脸特征信息比较精准)人脸要足够大，当前范围内人脸只能有一张人脸，比如：正常、眨眼睛、张嘴巴 (3张人脸信息)
2.2.2 从后台去查询用户进行登录
3. 提取特征值和匹配人脸信息
思路：
整合 opencv
获取相机的 SurfaceView 传到 native 层去检测，或者不断的获取 SurfaceView 的 Bitmap，传到 Native 层
检测人脸，保存人脸特征信息在本地
上传到后台
4.灰度图算法：java 里面把一张图片转成灰度图？
RGB： 0-255,0-255,0-255 (彩色图)
灰度：R+G+B = 255 = 0.33R+0.33G+0.33B(一般) = 0.3R + 0.59G + 0.11B(适合人的眼睛)
灰度图所含有的信息量(取值范围 0-255)不高，而彩色图的取值范围比较高 (255 * 255 * 255)
5.实现人脸识别
下载完opencv后选择并添加到项目
image.png
首先修改CmakeLists.txt
# For more information about using CMake with Android Studio, read the
# documentation: /studio/projects/add-native-code.html
# Sets the minimum version of CMake required to build the native library.
cmake_minimum_required(VERSION 3.4.1)
#set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=gnu++11")
#判断编译器类型,如果是gcc编译器,则在编译选项中加入c++11支持
if(CMAKE_COMPILER_IS_GNUCXX)
set(CMAKE_CXX_FLAGS "-std=c++11 ${CMAKE_CXX_FLAGS}")
message(STATUS "optional:-std=c++11")
endif(CMAKE_COMPILER_IS_GNUCXX)
#需要引入我们头文件,以这个配置的目录为基准
include_directories(src/main/jniLibs/include)
# 添加依赖 opencv.so 库
set(distribution_DIR ${CMAKE_SOURCE_DIR}/../../../../src/main/jniLibs)
add_library(
opencv_java3
SHARED
IMPORTED)
set_target_properties(
opencv_java3
PROPERTIES IMPORTED_LOCATION
../../../../src/main/jniLibs/armeabi/libopencv_java3.so)
# Creates and names a library, sets it as either STATIC
# or SHARED, and provides the relative paths to its source code.
# You can define multiple libraries, and CMake builds them for you.
# Gradle automatically packages shared libraries with your APK.
add_library( # Sets the name of the library.
native-lib
# Sets the library as a shared library.
SHARED
# Provides a relative path to your source file(s).
src/main/cpp/native-lib.cpp )
# Searches for a specified prebuilt library and stores the path as a
# variable. Because CMake includes system libraries in the search path by
# default, you only need to specify the name of the public NDK library
# you want to add. CMake verifies that the library exists before
# completing its build.
find_library( # Sets the name of the path variable.
log-lib
# Specifies the name of the NDK library that
# you want CMake to locate.
log )
# Specifies libraries CMake should link to your target library. You
# can link multiple libraries, such as libraries you define in this
# build script, prebuilt third-party libraries, or system libraries.
target_link_libraries( # Specifies the target library.
native-lib opencv_java3
#加入该依赖库
jnigraphics
# Links the target library to the log library
# included in the NDK.
${log-lib} )
新建FaceDetection人脸识别类
public class FaceDetection {
static {
System.loadLibrary("native-lib");
}
/**
* 检测人脸并保存人脸信息
* @param faceBitmap
*/
public native void faceDetectionSaveInfo(Bitmap faceBitmap);
/**
* 加载人脸识别器
* @param filePath
*/
public native void loadCascade(String filePath);
}
MainActivity的使用
public class MainActivity extends AppCompatActivity {
private ImageView mFaceImageView;
private Bitmap mFaceBitmap;
private FaceDetection mFaceDetection;
private File mCascadeFile;
@Override
protected void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
setContentView(R.layout.activity_main);
mFaceImageView = findViewById(R.id.face_image);
mFaceBitmap= BitmapFactory.decodeResource(getResources(),R.drawable.face);
mFaceImageView.setImageBitmap(mFaceBitmap);
copyCascadeFile();
mFaceDetection=new FaceDetection();
//人脸识别
mFaceDetection.loadCascade(mCascadeFile.getAbsolutePath());
}
private void copyCascadeFile() {
try {
// load cascade file from application resources
InputStream is = getResources().openRawResource(R.raw.lbpcascade_frontalface);
File cascadeDir = getDir("cascade", Context.MODE_PRIVATE);
mCascadeFile = new File(cascadeDir, "lbpcascade_frontalface.xml");
if(mCascadeFile.exists()) return;
FileOutputStream os = new FileOutputStream(mCascadeFile);
byte[] buffer = new byte[4096];
int bytesRead;
while ((bytesRead = is.read(buffer)) != -1) {
os.write(buffer, 0, bytesRead);
}
is.close();
os.close();
} catch (IOException e) {
e.printStackTrace();
}
}
public void faceDetection(View view) {
//识别人脸，保存人脸
mFaceDetection.faceDetectionSaveInfo(mFaceBitmap);
}
}
native-lib实现功能
#include
#include
#include
#include
#include
#include
using namespace cv;
#define TAG "JNI_TAG"
#define LOGE(...) __android_log_print(ANDROID_LOG_ERROR,TAG,__VA_ARGS__)
extern "C" {
JNIEXPORT void JNICALL
Java_com_peakmain_ndk_FaceDetection_faceDetectionSaveInfo(JNIEnv *env, jobject instance,
jobject faceBitmap);
void bitmap2Mat(JNIEnv *pEnv, Mat &mat, jobject bitmap);
void mat2Bitmap(JNIEnv *env, Mat mat, jobject bitmap);
JNIEXPORT void JNICALL
Java_com_peakmain_ndk_FaceDetection_loadCascade(JNIEnv *env, jobject instance, jstring filePath);
}
//bitmap转成mat
void bitmap2Mat(JNIEnv *env, Mat &mat, jobject bitmap) {
//mat里面有个type CV_8UC4刚好是我们的bitmap中RGB_8888,CV_8UC2对应的是我们的bitmap中的RGB_565
//获取bitmap的信息
AndroidBitmapInfo info;
void* pixels;
AndroidBitmap_getInfo(env,bitmap,&info);
//锁定Bitmap
AndroidBitmap_lockPixels(env,bitmap,&pixels);
//指定mat的宽高和type，bgra
mat.create(info.height,info.width,CV_8UC4);
if(info.format== ANDROID_BITMAP_FORMAT_RGBA_8888){
//对应的mat应该是CV_8UC4
Mat temp(info.height,info.width,CV_8UC4,pixels);
temp.copyTo(mat);
}else if(info.format==ANDROID_BITMAP_FORMAT_RGB_565){
//对应的mat应该是CV_8UC2
Mat temp(info.height,info.width,CV_8UC2,pixels);
//mat是CV_8UC4,
cvtColor(temp,mat, COLOR_BGR5652BGRA);
}
//其他的要自己去转
//解锁Bitmap画布
AndroidBitmap_unlockPixels(env,bitmap);
}
CascadeClassifier cascadeClassifier;
extern "C"
JNIEXPORT void JNICALL
Java_com_peakmain_ndk_FaceDetection_loadCascade(JNIEnv *env, jobject instance, jstring filePath_) {
const char *filePath = env->GetStringUTFChars(filePath_, 0);
cascadeClassifier.load(filePath);
LOGE("加载分类器文件成功");
env->ReleaseStringUTFChars(filePath_, filePath);
}
extern "C"
JNIEXPORT void JNICALL
Java_com_peakmain_ndk_FaceDetection_faceDetectionSaveInfo(JNIEnv *env, jobject instance,
jobject bitmap) {
//检测人脸,opencv有一个非常关键的类,opencv是c和c++写的，只处理Mat,android界面是bitmap
//1.bitmap转换成opencv能操作的c++对象Mat,mat是个矩阵
Mat mat;
bitmap2Mat(env,mat,bitmap);
//处理灰度,提高效率,一般操作都会执行
Mat gray_mat;
//转换成灰度
cvtColor(mat,gray_mat,COLOR_BGRA2GRAY);
//再次处理,直方均衡处理
Mat equalize_mat;
equalizeHist(gray_mat,equalize_mat);
//识别人脸,当然我们可以直接用彩色去做,识别人脸要加载人脸分类器文件
CV_OUT std::vector faces;
//5次识别
cascadeClassifier.detectMultiScale(equalize_mat,faces,1.1,5);
LOGE("人脸个数:%d",faces.size());
if(faces.size()==1){
Rect faceRect=faces[0];
//保存人脸信息,保存的其实就是mat,图片
// 在人脸部分画个图
rectangle(mat,faceRect,Scalar(255,155,155),8) ;
//把mat放到bitmap里面
mat2Bitmap(env,mat,bitmap);
//保存人脸的一部分
Mat face_info_mat(equalize_mat,faceRect);
//保存face_info_mat即可
}
//保存人脸信息
}
void mat2Bitmap(JNIEnv *env, Mat mat, jobject bitmap) {
// 1. 获取 bitmap 信息
AndroidBitmapInfo info;
void* pixels;
AndroidBitmap_getInfo(env,bitmap,&info);
// 锁定 Bitmap 画布
AndroidBitmap_lockPixels(env,bitmap,&pixels);
if(info.format == ANDROID_BITMAP_FORMAT_RGBA_8888){// C4
Mat temp(info.height,info.width,CV_8UC4,pixels);
if(mat.type() == CV_8UC4){
mat.copyTo(temp);
}
else if(mat.type() == CV_8UC2){
cvtColor(mat,temp,COLOR_BGR5652BGRA);
}
else if(mat.type() == CV_8UC1){// 灰度 mat
cvtColor(mat,temp,COLOR_GRAY2BGRA);
}
} else if(info.format == ANDROID_BITMAP_FORMAT_RGB_565){// C2
Mat temp(info.height,info.width,CV_8UC2,pixels);
if(mat.type() == CV_8UC4){
cvtColor(mat,temp,COLOR_BGRA2BGR565);
}
else if(mat.type() == CV_8UC2){
mat.copyTo(temp);
}
else if(mat.type() == CV_8UC1){// 灰度 mat
cvtColor(mat,temp,COLOR_GRAY2BGR565);
}
}
// 其他要自己去转
// 解锁 Bitmap 画布
AndroidBitmap_unlockPixels(env,bitmap);
}
build.gradle中defautConfig需要添加如下代码
externalNativeBuild {
cmake {
cppFlags ""
//只生成aremabi
abiFilters "armeabi"
}
}
效果图
效果图.png
