• 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);

});

}

});

});

}

}

• Dnn模式的人脸识别 Activity

package com.hxg.ndkface;

import android.Manifest;

import android.annot

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ation.SuppressLint;

import android.content.Context;

import android.graphics.Bitmap;