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.

人脸识别

hxgopencv-lib

opencv_java3

#加入该依赖库 undefined reference to `AndroidBitmap_getInfo’

jnigraphics

Links the target library to the log library

included in the NDK.

${log-lib})

• 加载级联选择器

![在这里插入图片描述](https://img-blog.csdnimg.cn/20201208102948469.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLm

《Android学习笔记总结+最新移动架构视频+大厂安卓面试真题+项目实战源码讲义》

【docs.qq.com/doc/DSkNLaERkbnFoS0ZF】 完整内容开源分享

NzZG4ubmV0L2h1YW5neGlhb2d1bzE=,size_16,color_FFFFFF,t_70)

/**

• 加载人脸识别的分类器文件

*/

private void copyCaseCadeFile() {

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();

}

}

/**

• 加载人脸识别的分类器文件

• @param filePath

*/

public native void loadCascade(String filePath);

#include <jni.h>

#include

#include “opencv2/opencv.hpp”

#include “android/bitmap.h”

#include “android/log.h”

//使用命名空间

using namespace cv;

using namespace dnn;

/**

• 加载人脸识别的分类器文件

*/

CascadeClassifier cascadeClassifier;

extern “C”

JNIEXPORT void JNICALL

Java_com_hxg_ndkface_FaceDetection_loadCascade(JNIEnv *env, jobject instance, jstring file_path) {

const char *filePath = env->GetStringUTFChars(file_path, 0);

cascadeClassifier.load(filePath);

__android_log_print(ANDROID_LOG_INFO, “TTTTT”, “%s”, “分类器文件加载成功”);

env->ReleaseStringUTFChars(file_path, filePath);

}

• 只检测是否有人脸

/**

• 只检测是否有人脸

*/

extern “C”

JNIEXPORT jboolean JNICALL

Java_com_hxg_ndkface_FaceDetection_faceDetection(JNIEnv *env, jobject thiz, jobject bitmap) {

//检测人脸，opencv 有个关键类 是Mat open只会处理Mat android里面是Bitmap

//1.Bitmap转成opencv能操作的C++对象Mat

Mat mat;

bitmap2Mat(env, mat, bitmap);

//处理灰度图,提高效率

Mat gray_mat;

__android_log_print(ANDROID_LOG_INFO, “TTTTT”, “%s”, “处理灰度图”);

cvtColor(mat, gray_mat, COLOR_BGRA2GRAY);

__android_log_print(ANDROID_LOG_INFO, “TTTTT”, “%s”, “再次处理 直方均衡补偿”);

//再次处理 直方均衡补偿

Mat equalize_mat;

equalizeHist(gray_mat, equalize_mat);

//识别人脸，要加载人脸分类器文件

std::vector faces;

cascadeClassifier.detectMultiScale(equalize_mat, faces, 1.1, 3, CV_HAAR_SCALE_IMAGE,

Size(30, 30));

__android_log_print(ANDROID_LOG_INFO, “TTTTT”, “人脸个数：%d”, faces.size());

if (faces.size() == 1) {

return true;

}

return false;

}

• 检测有无人脸，并保存到文件夹

/**

• 检测有无人脸，并保存到文件夹

*/

extern “C”

JNIEXPORT jint JNICALL

Java_com_hxg_ndkface_FaceDetection_faceDetectionSaveInfo(JNIEnv *env, jobject instance,

jstring name,

jobject bitmap) {

const char *filePath = env->GetStringUTFChars(name, 0);

//检测人脸，opencv 有个关键类 是Mat open只会处理Mat android里面是Bitmap

//1.Bitmap转成opencv能操作的C++对象Mat

Mat mat;

bitmap2Mat(env, mat, bitmap);

//处理灰度图,提高效率

Mat gray_mat;

cvtColor(mat, gray_mat, COLOR_BGRA2GRAY);

//再次处理 直方均衡补偿

Mat equalize_mat;

equalizeHist(gray_mat, equalize_mat);

//识别人脸，要加载人脸分类器文件

std::vector faces;

cascadeClassifier.detectMultiScale(equalize_mat, faces, 1.1, 5, 0 | CV_HAAR_SCALE_IMAGE,

Size(160, 160));

__android_log_print(ANDROID_LOG_INFO, “TTTTT”, “人脸个数：%d”, faces.size());

if (faces.size() == 1) {

Rect faceRect = faces[0];

//在人脸部分画个图

rectangle(mat, faceRect, Scalar(255, 0, 0), 3);

__android_log_print(ANDROID_LOG_ERROR, “TTTTT”, “人脸个数：%s”, “在人脸部分画个图”);

//把mat我们又放到bitmap中

mat2Bitmap(env, mat, bitmap);

//保存人脸信息Mat，图片jpg

Mat saveMat = Mat(equalize_mat, faceRect);

//保存face_info_mat

imwrite(filePath, equalize_mat);

return 1;

}

env->ReleaseStringUTFChars(name, filePath);

return 0;

}

• 人脸对比

/**

*人脸对比

*/

extern “C”

JNIEXPORT jdouble JNICALL

Java_com_hxg_ndkface_FaceDetection_histogramMatch(JNIEnv *env, jobject instance, jobject bitmap1,

jobject bitmap2) {

//1.Bitmap转成opencv能操作的C++对象Mat

Mat mat, mat1;

bitmap2Mat(env, mat, bitmap1);

bitmap2Mat(env, mat1, bitmap2);

// 转灰度矩阵

cvtColor(mat, mat, COLOR_BGR2HSV);

cvtColor(mat1, mat1, COLOR_BGR2HSV);

int channels[] = {0, 1};

int histsize[] = {180, 255};

float r1[] = {0, 180};

float r2[] = {0, 255};

const float *ranges[] = {r1, r2};

Mat hist1, hist2;

calcHist(&mat, 3, channels, Mat(), hist1, 2, histsize, ranges, true);

//https://www.cnblogs.com/bjxqmy/p/12292421.html

normalize(hist1, hist1, 1, 0, NORM_L1);

calcHist(&mat1, 3, channels, Mat(), hist2, 2, histsize, ranges, true);

normalize(hist2, hist2, 1, 0, NORM_L1);

double similarity = compareHist(hist1, hist2, HISTCMP_CORREL);

__android_log_print(ANDROID_LOG_ERROR, “TTTTT”, “相识度：%f”, similarity);

return similarity;

}

• Dnn模式的人脸识别，并抠图

private void copyCaseCadeFilePbtxt() {

InputStream is = null;

FileOutputStream os = null;

try {

// load cascade file from application resources

is = getResources().openRawResource(R.raw.opencv_face_detector);

File cascadeDir = getDir(“cascade”, Context.MODE_PRIVATE);

mCascadeFile = new File(cascadeDir, “opencv_face_detector.pbtxt”);

if (mCascadeFile.exists()) return;

os = new FileOutputStream(mCascadeFile);

byte[] buffer = new byte[1024 * 1024];

int bytesRead;

while ((bytesRead = is.read(buffer)) != -1) {

os.write(buffer, 0, bytesRead);

}

is.close();

os.close();

} catch (IOException e) {

e.printStackTrace();

} finally {

try {

if (is != null) {

is.close();

}

if (os != null) {

os.close();

}

} catch (IOException e) {

e.printStackTrace();

}

}

}

private void copyCaseCadeFileUint8() {

InputStream is = null;

FileOutputStream os = null;

try {

// load cascade file from application resources

is = getResources().openRawResource(R.raw.opencv_face_detector_uint8);

File cascadeDir = getDir(“cascade”, Context.MODE_PRIVATE);

mCascadeFile = new File(cascadeDir, “opencv_face_detector_uint8.pb”);

if (mCascadeFile.exists()) return;

os = new FileOutputStream(mCascadeFile);

byte[] buffer = new byte[1024 * 1024];

int bytesRead;

while ((bytesRead = is.read(buffer)) != -1) {

os.write(buffer, 0, bytesRead);

}

is.close();

os.close();

} catch (IOException e) {

e.printStackTrace();

} finally {

try {

if (is != null) {

is.close();

}

if (os != null) {

os.close();

}

} catch (IOException e) {

e.printStackTrace();

}

}

}

/**

*Dnn模式的人脸识别，并抠图

*/

extern “C”

JNIEXPORT jboolean JNICALL

Java_com_hxg_ndkface_FaceDetection_faceDnnDetection(JNIEnv *env, jobject instance,

jstring model_binary,

jstring model_desc,

jstring checkPath,

jstring resultPath) {

const char *model_binary_path = env->GetStringUTFChars(model_binary, 0);

const char *model_desc_path = env->GetStringUTFChars(model_desc, 0);

const char *check_path = env->GetStringUTFChars(checkPath, 0);

const char *result_path = env->GetStringUTFChars(resultPath, 0);

Net net = readNetFromTensorflow(model_binary_path, model_desc_path);

net.setPreferableBackend(DNN_BACKEND_OPENCV);

net.setPreferableTarget(DNN_TARGET_CPU);

if (net.empty()) {

__android_log_print(ANDROID_LOG_ERROR, “TTTTT”, “%s”, “could not load net…”);

return false;

}

Mat frame = imread(check_path); //读入检测文件

__android_log_print(ANDROID_LOG_ERROR, “TTTTT”, “%s”, “输入数据调整”);

// 输入数据调整

Mat inputBlob = blobFromImage(frame, 1.0,

Size(300, 300), Scalar(104.0, 177.0, 123.0), false, false);

net.setInput(inputBlob, “data”);

// 人脸检测

Mat detection = net.forward(“detection_out”);

Mat detectionMat(detection.size[2], detection.size[3], CV_32F, detection.ptr());

Mat face_area;

for (int i = 0; i < detectionMat.rows; i++) {

// 置信度 0～1之间

float confidence = detectionMat.at(i, 2);

if (confidence > 0.7) {

//count++;

int xLeftBottom = static_cast(detectionMat.at(i, 3) * frame.cols);

int yLeftBottom = static_cast(detectionMat.at(i, 4) * frame.rows);

int xRightTop = static_cast(detectionMat.at(i, 5) * frame.cols);

int yRightTop = static_cast(detectionMat.at(i, 6) * frame.rows);

Rect object((int) xLeftBottom, (int) yLeftBottom,

(int) (xRightTop - xLeftBottom),

(int) (yRightTop - yLeftBottom));

face_area = frame(object); //扣出图片

rectangle(frame, object, Scalar(0, 255, 0)); //画框

}

}

imwrite(result_path, face_area); //写出文件

env->ReleaseStringUTFChars(model_binary, model_binary_path);

env->ReleaseStringUTFChars(model_desc, model_desc_path);

env->ReleaseStringUTFChars(checkPath, check_path);

env->ReleaseStringUTFChars(resultPath, result_path);

return true;

}

• Bitmap和Mat互转

/**

• Bitmap转成opencv能操作的C++对象Mat

• @param env

• @param mat

• @param bitmap

*/

void bitmap2Mat(JNIEnv *env, Mat &mat, jobject bitmap) {

//Mat 里面有个type ：CV_8UC4刚好对上我们的Bitmap中的ARGB_8888 , CV_8UC2对应Bitmap中的RGB_555

//获取 bitmap 信息

AndroidBitmapInfo info;

void *pixels;

try {

// AndroidBitmap_getInfo(env, bitmap, &info);

//锁定Bitmap画布

// AndroidBitmap_lockPixels(env, bitmap, &pixels);

CV_Assert(AndroidBitmap_getInfo(env, bitmap, &info) >= 0);

CV_Assert(info.format == ANDROID_BITMAP_FORMAT_RGBA_8888 ||

info.format == ANDROID_BITMAP_FORMAT_RGB_565);

CV_Assert(AndroidBitmap_lockPixels(env, bitmap, &pixels) >= 0);

CV_Assert(pixels);

//指定mat的宽高type BGRA

mat.create(info.height, info.width, CV_8UC4);

if (info.format == ANDROID_BITMAP_FORMAT_RGBA_8888) {

//对应mat应该是CV_8UC4

Mat temp(info.height, info.width, CV_8UC4, pixels);

//把数据temp复制到mat里面

temp.copyTo(mat);

} else if (info.format == ANDROID_BITMAP_FORMAT_RGB_565) {

//对应mat应该是CV_8UC2

Mat temp(info.height, info.width, CV_8UC2, pixels);

//mat 是CV_8UC4 ，CV_8UC2 > CV_8UC4

cvtColor(temp, mat, COLOR_BGR5652BGRA);

}

//解锁Bitmap画布

AndroidBitmap_unlockPixels(env, bitmap);

return;

} catch (Exception &e) {

AndroidBitmap_unlockPixels(env, bitmap);

jclass je = env->FindClass(“java/lang/Exception”);

env->ThrowNew(je, e.what());

return;

} catch (…) {

AndroidBitmap_unlockPixels(env, bitmap);

jclass je = env->FindClass(“java/lang/Exception”);

env->ThrowNew(je, “Unknown exception in JNI code {nBitmapToMat}”);

return;

}

}

/**

• 把mat转成bitmap

• @param env

• @param mat

• @param bitmap

*/

void mat2Bitmap(JNIEnv *env, Mat mat, jobject bitmap) {

//Mat 里面有个type ：CV_8UC4刚好对上我们的Bitmap中的ARGB_8888 , CV_8UC2对应Bitmap中的RGB_555

//获取 bitmap 信息

AndroidBitmapInfo info;

void *pixels;

try {

// AndroidBitmap_getInfo(env, bitmap, &info);

//锁定Bitmap画布

// AndroidBitmap_lockPixels(env, bitmap, &pixels);

CV_Assert(AndroidBitmap_getInfo(env, bitmap, &info) >= 0);

CV_Assert(info.format == ANDROID_BITMAP_FORMAT_RGBA_8888 ||

info.format == ANDROID_BITMAP_FORMAT_RGB_565);

CV_Assert(mat.dims == 2 && info.height == (uint32_t) mat.rows &&

info.width == (uint32_t) mat.cols);

CV_Assert(mat.type() == CV_8UC1 || mat.type() == CV_8UC3 || mat.type() == CV_8UC4);

CV_Assert(AndroidBitmap_lockPixels(env, bitmap, &pixels) >= 0);

CV_Assert(pixels);

if (info.format == ANDROID_BITMAP_FORMAT_RGBA_8888) {

//对应mat应该是CV_8UC4

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 (mat.type() == CV_8UC3) {

cvtColor(mat, temp, COLOR_RGB2BGRA);

}

} else if (info.format == ANDROID_BITMAP_FORMAT_RGB_565) {

//对应mat应该是CV_8UC2

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);

} else if (mat.type() == CV_8UC3) {

cvtColor(mat, temp, COLOR_RGB2BGR565);

}

}

//解锁Bitmap画布

AndroidBitmap_unlockPixels(env, bitmap);

return;

} catch (const Exception &e) {

AndroidBitmap_unlockPixels(env, bitmap);

jclass je = env->FindClass(“java/lang/Exception”);

env->ThrowNew(je, e.what());

return;

} catch (…) {

AndroidBitmap_unlockPixels(env, bitmap);

jclass je = env->FindClass(“java/lang/Exception”);

env->ThrowNew(je, “Unknown exception in JNI code {nMatToBitmap}”);

return;

}

}

• 人脸检测Activity

package com.hxg.ndkface;

import android.Manifest;

import android.annotation.SuppressLint;

import android.content.Context;

import android.graphics.Bitmap;

import android.graphics.BitmapFactory;

import android.hardware.Camera;

import android.os.Bundle;

import androidx.appcompat.app.AppCompatActivity;

import androidx.appcompat.widget.AppCompatImageView;

import androidx.appcompat.widget.AppCompatTextView;

import androidx.arch.core.executor.ArchTaskExecutor;

import com.hxg.ndkface.camera.AutoTexturePreviewView;

import com.hxg.ndkface.manager.CameraPreviewManager;

import com.hxg.ndkface.model.SingleBaseConfig;

import com.hxg.ndkface.utils.CornerUtil;

import com.hxg.ndkface.utils.FileUtils;

import com.tbruyelle.rxpermissions3.RxPermissions;

import java.io.File;

import java.io.FileOutputStream;

import java.io.IOException;

import java.io.InputStream;

public class MainNorFaceActivity extends AppCompatActivity {

private Bitmap mFaceBitmap;

private FaceDetection mFaceDetection;

private File mCascadeFile;

private AppCompatTextView mTextView;

private RxPermissions rxPermissions;

private AutoTexturePreviewView mAutoCameraPreviewView;

// 图片越大，性能消耗越大，也可以选择640480， 1280720

private static final int PREFER_WIDTH = SingleBaseConfig.getBaseConfig().getRgbAndNirWidth();

private static final int PERFER_HEIGH = SingleBaseConfig.getBaseConfig().getRgbAndNirHeight();

@Override

public void onDetachedFromWindow() {

super.onDetachedFromWindow();

CameraPreviewManager.getInstance().stopPreview();

}

@Override

protected void onCreate(Bundle savedInstanceState) {

super.onCreate(savedInstanceState);

setContentView(R.layout.activity_main);

rxPermissions = new RxPermissions(this);

mTextView = findViewById(R.id.note);

mAutoCameraPreviewView = findViewById(R.id.auto_camera_preview_view);

mFaceBitmap = BitmapFactory.decodeResource(getResources(), R.drawable.face);

copyCaseCadeFile();

mFaceDetection = new FaceDetection();

mFaceDetection.loadCascade(mCascadeFile.getAbsolutePath());

}

/**

• 加载人脸识别的分类器文件

*/

private void copyCaseCadeFile() {

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();

}

}

@Override

public void onAttachedToWindow() {

super.onAttachedToWindow();

CornerUtil.clipViewCircle(mAutoCameraPreviewView);

rxPermissions.request(

Manifest.permission.WRITE_EXTERNAL_STORAGE,

Manifest.permission.READ_EXTERNAL_STORAGE,

Manifest.permission.CAMERA)

.subscribe(aBoolean -> {

startTestOpenDebugRegisterFunction();

});

}

@SuppressLint(“RestrictedApi”)

private void startTestOpenDebugRegisterFunction() {

CameraPreviewManager.getInstance().setCameraFacing(CameraPreviewManager.CAMERA_FACING_FRONT);

CameraPreviewManager.getInstance().startPreview(this, mAutoCameraPreviewView,

PREFER_WIDTH, PERFER_HEIGH, (byte[] data, Camera camera, int width, int height) -> {

//识别人脸，保存人脸特征信息

// String name = FileUtils.createFile(this) + “/test.png”;

// int type = mFaceDetection.faceDetectionSaveInfo(name, mFaceBitmap);

ArchTaskExecutor.getIOThreadExecutor().execute(() -> {

Bitmap bitmap = FileUtils.decodeToBitMap(data, camera);

boolean haveFace = mFaceDetection.faceDetection(bitmap);

runOnUiThread(() -> {

((AppCompatImageView) findViewById(R.id.tv_img)).setImageBitmap(bitmap);

});

if (haveFace) {

double similarity = mFaceDetection.histogramMatch(mFaceBitmap, bitmap);

String str = “对比度：”;

runOnUiThread(() -> {

mTextView.setText(str + similarity);

});

}

});

});

}

}