3、使用Java api 和 jni混合方式调用OpenCV
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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 0 0
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