android opencv NDK人脸识别和对比，移动app定制开发
Sets the library as a shared library.
SHARED
Provides a relative path to your source file(s).
hxgopencv-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.
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
/**
- 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
#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);
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的RGB_555
//获取 bitmap 信息
AndroidBitmapInfo info;
void *pixels;
try {
// AndroidBitmap_getInfo(env, bitmap, &info);
Android高级架构师
由于篇幅问题，我呢也将自己当前所在技术领域的各项知识点、工具、框架等汇总成一份技术路线图，还有一些架构进阶视频、全套学习PDF文件、面试文档、源码笔记做整理一份资料。
需要的朋友可以**私信【学习】**我分享给你，希望里面的资料可以给你们一个更好的学习参考。
或者直接点击下面链接免费获取
Android学习PDF+架构视频+面试文档+源码笔记
- 330页PDF Android学习核心笔记（内含上面8大板块）
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-
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-
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- Android BAT部分大厂面试题（有解析）
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好了，以上便是今天的分享，希望为各位朋友后续的学习提供方便。觉得内容不错，也欢迎多多分享给身边的朋友哈。