OpenCV4Android 2，脱离JNI的C++接口
OpenCV4Android 2，脱离JNI的C++接口
——让你的OpenCV程序远离Android
关于环境的搭建，参考我前一篇博客：
第一个OpenCV4Android
程序目标：实现相机对周围环境的实时检测，要求OpenCV处理代码脱离Android代码已经JNI代码
1、Camera线程
在写C++代码时，我们会开启一个新的线程，在线程中cvqueryframe实时的得到每一帧的数据再进行处理，那么按照这个思路我们在Android使用相机也要开启一个新的线程。
思考了很久怎样在Android新线程中（非UI线程）中嵌入OpenCV打开相机的例子，其实，这一点org.opencv.android.CameraBridgeViewBase类中已经帮我们（通过继承）解决了。我们可以键入如下测试代码：
protected void onCreate(Bundle savedInstanceState) {
Log.i(TAG,"called onCreate");
super.onCreate(savedInstanceState);
setContentView(R.layout.activity_main);
mOpenCvCameraView=(CameraBridgeViewBase)findViewById(R.id.HelloOpenCvView);
mOpenCvCameraView.setVisibility(SurfaceView.VISIBLE);
mOpenCvCameraView.setCvCameraViewListener(this);
btn=(Button)findViewById(R.id.button1);
btn.setOnClickListener(new OnClickListener(){
public void onClick(View view){
doCany=!doCany;
System.out.println("OnClickListener -----"+Thread.currentThread().getId());
}
});
}
public Mat onCameraFrame(CvCameraViewFrame inputFrame){
System.out.println("onCameraFrame -----"+Thread.currentThread().getId());
return inputFrame.rgba();
}
第一个println位于我们响应UI界面的OnCreatea函数，二个println位于我们响应CameraViewListener的事件响应函数中。
在LogCat中我们新建 Tag=System.out的过滤器，我们会得到下列输出：
可以看到输出的线程ID并不同，那么显然CameraBridgeViewBase中已经帮我们解决了多线程的问题，我们没有必要再开一个新的线程去处理相机的每一帧数据。直接在onCameraFrame(CvCameraViewFrameinputFrame)中加入处理每一帧图像的相关代码即可。
2、程序框架
3、程序源码
Activity_main.xml
注意android:layout_width、android:layout_height不能为任意值
<LinearLayout xmlns:android="http://schemas.android.com/apk/res/android"
xmlns:tools="http://schemas.android.com/tools"
xmlns:opencv="http://schemas.android.com/apk/res-auto"
android:id="@+id/container"
android:layout_width="match_parent"
android:layout_height="match_parent"
android:orientation="vertical" >
<org.opencv.android.JavaCameraView
android:layout_width="320px"
android:layout_height="280px"
android:visibility="gone"
android:id="@+id/HelloOpenCvView"
opencv:show_fps="true"
opencv:camera_id="any"/>
<Button
android:id="@+id/button1"
android:layout_width="wrap_content"
android:layout_height="wrap_content"
android:layout_below="@+id/HelloOpenCvView"
android:text="Button" />
</LinearLayout>
MainActivity.java
public class MainActivity extends Activity implements CvCameraViewListener2 {
private CameraBridgeViewBase mOpenCvCameraView;
private boolean mIsJavaCamera = true;
private boolean doCany=false;
private Button btn;
private static final String TAG = "OCVSample::Activity";
private ProcessImg nativeProcess;
String xmlFile="heh";
//当加载OpenCV库成功后的回调函数
private BaseLoaderCallback mLoaderCallback = new BaseLoaderCallback(this) {
@Override
public void onManagerConnected(int status) {
switch (status) {
case LoaderCallbackInterface.SUCCESS:
{
Log.i(TAG, "OpenCV loaded successfully");
//加载本地库
System.loadLibrary("ProcessImg");
//
mOpenCvCameraView.enableView();
nativeProcess=new ProcessImg(xmlFile);
} break;
default:
{
super.onManagerConnected(status);
} break;
}
}
};
@SuppressWarnings("deprecation")
@Override
protected void onCreate(Bundle savedInstanceState) {
Log.i(TAG,"called onCreate");
super.onCreate(savedInstanceState);
setContentView(R.layout.activity_main);
if (mIsJavaCamera)
mOpenCvCameraView = (CameraBridgeViewBase) findViewById(R.id.HelloOpenCvView);
else
mOpenCvCameraView = (CameraBridgeViewBase) findViewById(R.id.HelloOpenCvView);
mOpenCvCameraView=(CameraBridgeViewBase)findViewById(R.id.HelloOpenCvView);
mOpenCvCameraView.setVisibility(SurfaceView.VISIBLE);
//设置CameraView的事件监听
mOpenCvCameraView.setCvCameraViewListener(this);
btn=(Button)findViewById(R.id.button1);
btn.setOnClickListener(new OnClickListener(){
public void onClick(View view){
doCany=!doCany;
System.out.println("OnClickListener -----"+Thread.currentThread().getId());
}
});
}
public void onPause()
{
super.onPause();
if(mOpenCvCameraView!=null){
mOpenCvCameraView.disableView();
}
}
public void onResume()
{
super.onResume();
System.out.println("onResume -----"+Thread.currentThread().getId());
OpenCVLoader.initAsync(OpenCVLoader.OPENCV_VERSION_2_4_3, this, mLoaderCallback);
}
public void onDestroy(){
super.onDestroy();
if(mOpenCvCameraView!=null){
mOpenCvCameraView.disableView();
}
}
@Override
//当相机开始工作后触发该函数，之后会调用onCameraFrame()函数
public void onCameraViewStarted(int width, int height) {
// TODO Auto-generated method stub
}
public void onCameraViewStopped(){
}
//接收每一帧图像，并进行需要的处理
public Mat onCameraFrame(CvCameraViewFrame inputFrame){
System.out.println("onCameraFrame -----"+Thread.currentThread().getId());
if(doCany==true){
Mat CannyMat=inputFrame.gray();
inputFrame.gray().copyTo(CannyMat);
nativeProcess.SignDetect(CannyMat);
return CannyMat;
}
else {
return inputFrame.rgba();
}
}
}
Process.java
public class ProcessImg {
public ProcessImg(String xmlFile){
mNativeObj = nativeCreateObject(xmlFile);
}
public void SignDetect(Mat input){
nativeSignDetect(mNativeObj,input.getNativeObjAddr());
}
private long mNativeObj = 0;
private static native long nativeCreateObject(String cascadeName);
private static native void nativeSignDetect(long thiz,long inputImage);
}
ProcessImg.h自动生成，不在论述。
ProcessImg.cpp
#include "ProcessImg.h"
#include <opencv2/core/core.hpp>
#include <opencv/cv.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <string>
#include <vector>
#include <android/log.h>
#include "TrafficSign.h"
using namespace std;
using namespace cv;
extern "C" {
JNIEXPORT jlong JNICALL Java_com_pan_helloopencv_ProcessImg_nativeCreateObject
(JNIEnv *jenv, jclass, jstring jFileName)
{
jlong result = 0;
//将jstring 转换为 char*
const char* xmlFileName = jenv->GetStringUTFChars(jFileName,NULL);
//string xmlFile(xmlFileName);
try
{
//创建图像处理对象（由TrafficSign.h定义）
result = (jlong)new TrafficSignDetection(xmlFileName);
return result;
}
catch(cv::Exception& e)
{
// LOGD("nativeCreateObject caught cv::Exception: %s", e.what());
jclass je = jenv->FindClass("org/opencv/core/CvException");
if(!je)
je = jenv->FindClass("java/lang/Exception");
jenv->ThrowNew(je, e.what());
}
catch (...)
{
// LOGD("nativeCreateObject caught unknown exception");
jclass je = jenv->FindClass("java/lang/Exception");
jenv->ThrowNew(je, "Unknown exception in JNI code {highgui::VideoCapture_n_1VideoCapture__()}");
return 0;
}
}
/*
* Class: com_pan_helloopencv_ProcessImg
* Method: nativeSignDetect
* Signature: (JJ)V
*/
JNIEXPORT void JNICALL Java_com_pan_helloopencv_ProcessImg_nativeSignDetect
(JNIEnv *jenv, jclass, jlong thiz, jlong inputImage)
{
try
{
//处理每一帧图像
((TrafficSignDetection*)thiz)->process(*((Mat*)inputImage));
}
catch(cv::Exception& e)
{
//LOGD("nativeCreateObject caught cv::Exception: %s", e.what());
jclass je = jenv->FindClass("org/opencv/core/CvException");
if(!je)
je = jenv->FindClass("java/lang/Exception");
jenv->ThrowNew(je, e.what());
}
catch (...)
{
// LOGD("nativeDetect caught unknown exception");
jclass je = jenv->FindClass("java/lang/Exception");
jenv->ThrowNew(je, "Unknown exception in JNI code {highgui::VideoCapture_n_1VideoCapture__()}");
}
}
}
TrafficSign.h
用C++代码实现图像处理的主逻辑
#pragma once
#if defined(__linux__) || defined(LINUX) || defined(__APPLE__) || defined(ANDROID)
#include <opencv2/core/core.hpp>
#include <vector>
#include <string>
class TrafficSignDetection
{
public:
//需要的参数
struct Parameters
{
int minObjectSize;
int maxObjectSize;
double scaleFactor;
int maxTrackLifetime;
int minNeighbors;
int minDetectionPeriod; //the minimal time between run of the big object detector (on the whole frame) in ms (1000 mean 1 sec), default=0
Parameters();
};
//含参构造函数
//TrafficSignDetection(const char* xmlFile,const Parameters& params);
TrafficSignDetection(const char* xmlFile);
virtual ~TrafficSignDetection();
//进行交通标志检测
virtual void process(const cv::Mat& imageGray);
//停止检测
virtual void stop();
//
virtual void setXmlFile(const char *fileName);
private:
char * FileName;
};
namespace cv
{
::TrafficSignDetection;
}
#endif
Android.mk
LOCAL_PATH := $(call my-dir) include $(CLEAR_VARS) include E:/OpenCV-2.4.4-android-sdk/sdk/native/jni/OpenCV.mk LOCAL_SRC_FILES := ProcessImg.cpp TrafficSign.cpp LOCAL_LDLIBS += -llog -ldl LOCAL_CFLAGS += -DLIBUTILS_NATIVE=1 $(TOOL_CFLAGS) -fpermissive LOCAL_MODULE := ProcessImg include $(BUILD_SHARED_LIBRARY)
4、运行结果
点击按钮楷书处理每一帧图像：
至此，我们就实现了脱离一切JNI函数的接口文件TrafficSign.h，之后我们就可以定义TrafficSign.cpp文件，用纯C++的代码实现我们的图像算法了！
再使用Cygwin编译的时候遇到很多问题，会在后面的博文中进行讨论，因此未完待续……
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