<div style="font-family:'Helvetica Neue';font-size:14px;"></div><div><pre name="code" class="java"><pre name="code" class="java"><pre name="code" class="java">int a =b;
如果想在项目中直接使用opencv的java api 并且也需要自己编写c++，那么就需要Java Api与Jni混用，下面就以人脸检测为例，实验一些混合方式
一、创建项目
创建项目FaceDetection
二、添加opencv的java api
1、再项目中创建文件夹libopencv用来存放opencv的库module
2、将
Android/OpenCV-android-sdk/sdk/java 复制到libopencv目录中，并将其改名opencv
3、打开settings.gradle添加
include
':libopencv:opencv’并点击Sync Now
4、在opencv中创建build.gradle文件，并将以下内容复制进去，注意按要求
替换内容，
然后点击Sync Now
apply plugin:'android-library'
buildscript{
repositories{
mavenCentral()
}
dependencies{
classpath 'com.android.tools.build:gradle:1.3.0' // 和项目/build.gradle中的一致
}
}
android{
compileSdkVersion 22 //与 app/build.gradle中的一致
buildToolsVersion "22.0.1" //与 app/build.gradle中的一致
defaultConfig {
minSdkVersion 15 //与 app/build.gradle中的一致
targetSdkVersion 22 //与 app/build.gradle中的一致
versionCode 2411 //改成自己下的opencv的版本
versionName "2.4.11" //改成自己下的opencv的版本
}
sourceSets{
main{
manifest.srcFile 'AndroidManifest.xml'
java.srcDirs = ['src']
resources.srcDirs = ['src']
res.srcDirs = ['res']
aidl.srcDirs = ['src']
}
}
}
5、为app添加opencv依赖，在app上右键 open module settings,将opencv加进去
三、添加Opencv Face Detection Jni
1、打开opencv提供的人脸识别示例，将samples/face-detectioin/src/org/opencv/samples/facedetect/DetectionBasedTracker.java文件拷贝到app中包下，注意java文件package修改成当前的包
错误是因为并没有native文件与之关联
2、在app中创建autojavah.sh文件，用来创建jni文件夹及.h文件，内容如下：
#!/bin/sh
export ProjectPath=$(cd "../$(dirname "$1")"; pwd)
export ProjectPath=$(cd "../$(dirname "$1")"; pwd)
export TargetClassName="com.lingyun.facedetection.DetectionBasedTracker" #换成你的包名.含有native方法的类名
export SourceFile="${ProjectPath}/app/src/main/java" #java源文件目录
export TargetPath="${ProjectPath}/app/src/main/jni" #输出jni文件目录
cd "${SourceFile}"
javah -d ${TargetPath} -classpath "${SourceFile}" "${TargetClassName}"
echo -d ${TargetPath} -classpath "${SourceFile}" "${TargetClassName}"
javah -d ${TargetPath} -classpath "${SourceFile}" "${TargetClassName}"
echo -d ${TargetPath} -classpath "${SourceFile}" "${TargetClassName}"
3、右键运行autojavah.sh文件，如果没有插件，android Studio会提示是否下载安装插件
此时可以看到多了jni目录以及一个.h文件
4、将
OpenCV-android-sdk/samples/face-detection/jni中的.cpp 和.mk文件复制到jni目录中
修改.cpp中的include头文件
#include <com_lingyun_facedetection_DetectionBasedTracker.h>
修改函数名为.h中的函数名，这里有6个函数
修改Android.mk文件：
LOCAL_PATH := $(call my-dir)
include $(CLEAR_VARS)
OPENCV_CAMERA_MODULES:=on
OPENCV_INSTALL_MODULES:=off
OPENCV_LIB_TYPE:=STATIC
下面一行换成自己的opencvsdk
include /Users/lichuanpeng/Documents/Program_File/Android/OpenCV-android-sdk/sdk/native/jni/OpenCV.mk
LOCAL_SRC_FILES := DetectionBasedTracker_jni.cpp
LOCAL_C_INCLUDES += $(LOCAL_PATH)
LOCAL_LDLIBS += -lm -llog
LOCAL_MODULE := detection_based_tracker
include $(BUILD_SHARED_LIBRARY)
修改Application.mk文件
APP_STL:=gnustl_static
APP_CPPFLAGS:=-frtti -fexceptions
APP_ABI := armeabi armeabi-v7a x86 mips
APP_PLATFORM := android-8
5、配置app的build.gradle
我的配置是
apply plugin: 'com.android.application'
android {
compileSdkVersion 22
buildToolsVersion "22.0.1"
defaultConfig {
applicationId "com.lingyun.facedetecttest"
minSdkVersion 15
targetSdkVersion 22
versionCode 1
versionName "1.0"
这是添加的
ndk{
moduleName "app"
}
}
这是添加的
sourceSets.main {
jniLibs.srcDir 'src/main/jnilibs'
jni.srcDirs = [] //disable automatic ndk-build call
}
buildTypes {
release {
minifyEnabled false
proguardFiles getDefaultProguardFile('proguard-android.txt'), 'proguard-rules.pro'
}
}
}
dependencies {
compile fileTree(dir: 'libs', include: ['*.jar'])
compile 'com.android.support:appcompat-v7:22+'
compile project(':opencvlibs:opencv')
}
6、新增NDK_BUILD 工具
点击Android Studio->Preferences->External Tools 点击+新增
新增 NDK Build
Name: NDK Build
Group: NDK
Description: NDK Build
Options: 全打勾
Show in: 全打勾
Tools Settings:
Program: NDK目錄/ndk-build
Parameters: NDK_PROJECT_PATH=$ModuleFileDir$/build/intermediates/ndk NDK_LIBS_OUT=$ModuleFileDir$/src/main/jniLibs NDK_APPLICATION_MK=$ModuleFileDir$/src/main/jni/Application.mk APP_BUILD_SCRIPT=$ModuleFileDir$/src/main/jni/Android.mk V=1
Working directory: $SourcepathEntry$
7、在app上右键点击NDK NDK Build
可以看到多出来jniLibs目录
8、将
OpenCV-android-sdk/sdk/native/libs 目录里面四个文件夹中的libopencv_java.so分别对应放在刚才生成的目录中，因为java api需要这些。
四、添加布局文件及activity和权限
1、将
OpenCV-android-sdk/samples/face-detection/res/layout/face_detect_surface_view.xml 文件复制到app中的layout目录中
2、在res中创建raw目录,并将
OpenCV-android-sdk/samples/face-detection/res/raw/lbpcascade_frontalface.xml 文件复制到raw中
3、修改MainActivity
import java.io.File;
import java.io.FileOutputStream;
import java.io.IOException;
import java.io.InputStream;
import org.opencv.android.CameraBridgeViewBase.CvCameraViewFrame;
import org.opencv.android.OpenCVLoader;
import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.MatOfRect;
import org.opencv.core.Rect;
import org.opencv.core.Scalar;
import org.opencv.core.Size;
import org.opencv.android.CameraBridgeViewBase;
import org.opencv.android.CameraBridgeViewBase.CvCameraViewListener2;
import org.opencv.objdetect.CascadeClassifier;
import android.content.Context;
import android.os.Bundle;
import android.support.v7.app.AppCompatActivity;
import android.util.Log;
import android.view.Menu;
import android.view.MenuItem;
import android.view.WindowManager;
import com.lingyun.facedetection.R;
public class MainActivity extends AppCompatActivity implements CvCameraViewListener2{
private static final String TAG = "OCVSample::Activity";
private static final Scalar FACE_RECT_COLOR = new Scalar(0, 255, 0, 255);
public static final int JAVA_DETECTOR = 0;
public static final int NATIVE_DETECTOR = 1;
private MenuItem mItemFace50;
private MenuItem mItemFace40;
private MenuItem mItemFace30;
private MenuItem mItemFace20;
private MenuItem mItemType;
private Mat mRgba;
private Mat mGray;
private File mCascadeFile;
private CascadeClassifier mJavaDetector;
private DetectionBasedTracker mNativeDetector;
private int mDetectorType = JAVA_DETECTOR;
private String[] mDetectorName;
private float mRelativeFaceSize = 0.2f;
private int mAbsoluteFaceSize = 0;
private CameraBridgeViewBase mOpenCvCameraView;
static {
if(!OpenCVLoader.initDebug()){
Log.d("MyDebug","Falied");
}else{
Log.d("MyDebug","success");
System.loadLibrary("opencv_java");
}
}
public void doDetect(){
// Load native library after(!) OpenCV initialization
System.loadLibrary("detection_based_tracker");//
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");
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();
mJavaDetector = new CascadeClassifier(mCascadeFile.getAbsolutePath());
if (mJavaDetector.empty()) {
Log.e(TAG, "Failed to load cascade classifier");
mJavaDetector = null;
} else
Log.i(TAG, "Loaded cascade classifier from " + mCascadeFile.getAbsolutePath());
mNativeDetector = new DetectionBasedTracker(mCascadeFile.getAbsolutePath(), 0);
cascadeDir.delete();
} catch (IOException e) {
e.printStackTrace();
Log.e(TAG, "Failed to load cascade. Exception thrown: " + e);
}
mOpenCvCameraView.enableView();
}
public MainActivity() {
mDetectorName = new String[2];
mDetectorName[JAVA_DETECTOR] = "Java";
mDetectorName[NATIVE_DETECTOR] = "Native (tracking)";
Log.i(TAG, "Instantiated new " + this.getClass());
}
/** Called when the activity is first created. */
@Override
public void onCreate(Bundle savedInstanceState) {
Log.i(TAG, "called onCreate");
super.onCreate(savedInstanceState);
getWindow().addFlags(WindowManager.LayoutParams.FLAG_KEEP_SCREEN_ON);
setContentView(R.layout.face_detect_surface_view);
mOpenCvCameraView = (CameraBridgeViewBase) findViewById(R.id.fd_activity_surface_view);
mOpenCvCameraView.setCvCameraViewListener(this);
doDetect();
}
@Override
public void onPause()
{
super.onPause();
if (mOpenCvCameraView != null)
mOpenCvCameraView.disableView();
}
@Override
public void onResume()
{
super.onResume();
// OpenCVLoader.initAsync(OpenCVLoader.OPENCV_VERSION_2_4_3, this, mLoaderCallback);
}
public void onDestroy() {
super.onDestroy();
mOpenCvCameraView.disableView();
}
public void onCameraViewStarted(int width, int height) {
mGray = new Mat();
mRgba = new Mat();
}
public void onCameraViewStopped() {
mGray.release();
mRgba.release();
}
public Mat onCameraFrame(CvCameraViewFrame inputFrame) {
mRgba = inputFrame.rgba();
mGray = inputFrame.gray();
if (mAbsoluteFaceSize == 0) {
int height = mGray.rows();
if (Math.round(height * mRelativeFaceSize) > 0) {
mAbsoluteFaceSize = Math.round(height * mRelativeFaceSize);
}
mNativeDetector.setMinFaceSize(mAbsoluteFaceSize);
}
MatOfRect faces = new MatOfRect();
if (mDetectorType == JAVA_DETECTOR) {
if (mJavaDetector != null)
mJavaDetector.detectMultiScale(mGray, faces, 1.1, 2, 2, // TODO: objdetect.CV_HAAR_SCALE_IMAGE
new Size(mAbsoluteFaceSize, mAbsoluteFaceSize), new Size());
}
else if (mDetectorType == NATIVE_DETECTOR) {
if (mNativeDetector != null)
mNativeDetector.detect(mGray, faces);
}
else {
Log.e(TAG, "Detection method is not selected!");
}
Rect[] facesArray = faces.toArray();
for (int i = 0; i < facesArray.length; i++)
Core.rectangle(mRgba, facesArray[i].tl(), facesArray[i].br(), FACE_RECT_COLOR, 3);
return mRgba;
}
@Override
public boolean onCreateOptionsMenu(Menu menu) {
Log.i(TAG, "called onCreateOptionsMenu");
mItemFace50 = menu.add("Face size 50%");
mItemFace40 = menu.add("Face size 40%");
mItemFace30 = menu.add("Face size 30%");
mItemFace20 = menu.add("Face size 20%");
mItemType = menu.add(mDetectorName[mDetectorType]);
return true;
}
@Override
public boolean onOptionsItemSelected(MenuItem item) {
Log.i(TAG, "called onOptionsItemSelected; selected item: " + item);
if (item == mItemFace50)
setMinFaceSize(0.5f);
else if (item == mItemFace40)
setMinFaceSize(0.4f);
else if (item == mItemFace30)
setMinFaceSize(0.3f);
else if (item == mItemFace20)
setMinFaceSize(0.2f);
else if (item == mItemType) {
int tmpDetectorType = (mDetectorType + 1) % mDetectorName.length;
item.setTitle(mDetectorName[tmpDetectorType]);
setDetectorType(tmpDetectorType);
}
return true;
}
private void setMinFaceSize(float faceSize) {
mRelativeFaceSize = faceSize;
mAbsoluteFaceSize = 0;
}
private void setDetectorType(int type) {
if (mDetectorType != type) {
mDetectorType = type;
if (type == NATIVE_DETECTOR) {
Log.i(TAG, "Detection Based Tracker enabled");
mNativeDetector.start();
} else {
Log.i(TAG, "Cascade detector enabled");
mNativeDetector.stop();
}
}
}
}
4、添加摄像机权限
<?xml version="1.0" encoding="utf-8"?>
<manifest xmlns:android="http://schemas.android.com/apk/res/android"
package="com.lingyun.facedetection" >
<application
android:allowBackup="true"
android:icon="@mipmap/ic_launcher"
android:label="@string/app_name"
android:theme="@style/AppTheme" >
<activity
android:name=".MainActivity"
android:label="@string/app_name" >
<intent-filter>
<action android:name="android.intent.action.MAIN" />
<category android:name="android.intent.category.LAUNCHER" />
</intent-filter>
</activity>
</application>
<supports-screens android:resizeable="true"
android:smallScreens="true"
android:normalScreens="true"
android:largeScreens="true"
android:anyDensity="true" />
<uses-sdk android:minSdkVersion="8" />
<uses-permission android:name="android.permission.CAMERA"/>
<uses-feature android:name="android.hardware.camera" android:required="false"/>
<uses-feature android:name="android.hardware.camera.autofocus" android:required="false"/>
<uses-feature android:name="android.hardware.camera.front" android:required="false"/>
<uses-feature android:name="android.hardware.camera.front.autofocus" android:required="false"/>
</manifest>
五、调试
运行项目
