Android RakNet 系列之五 視頻通訊 OpenCV4Android
來源：程序員人生 發布時間：2014-12-16 08:37:39 閱讀次數：7938次
簡介
引入OpenCV4Android的目標是在Raknet框架下解決視頻通訊的問題，目前在ubuntu下已成功實現，現在把它援用到Android平臺下。
OpenCV是1個基于開源發行的跨平臺計算機視覺庫，可以在 Windows, Android, Maemo,FreeBSD, OpenBSD, iOS,Linux 和Mac OS等平臺上運行。它輕量級而且高效――由1系列 C 函數和少許 C++ 類構成，同時提供了Python、Ruby、MATLAB等語言的接口，實現了圖象處理和計算機視覺方面的很多通用算法。OpenCV致力于真實世界的實時利用，通過優化的C代碼的編寫對其履行速度帶來了可觀的提升，并且可以通過購買Intel的IPP高性能多媒體函數庫(Integrated Performance Primitives)得到更快的處理速度。
相干網站
http://sourceforge.net/projects/opencvlibrary/files/opencv-android/ 最新版項目源碼下載
http://www.opencv.org.cn/ OpenCV中文論壇
http://opencv.org/?s=+android&x=0&y=0 OpenCV 官網
http://www.code.opencv.org/projects/opencv/issues OpenCV 官網下解決方案
http://docs.opencv.org/platforms/android/service/doc/index.html 或 http://docs.opencv.org/trunk/ OpenCV 官網下介紹文檔
http://www.jayrambhia.com/android/ 相干博客
詳情
項目介紹
官方提供了1個庫項目（OpenCV Library - 2.4.10）和9個Demo項目（OpenCV Manager - 2.4.10、OpenCV Tutorial 1 - Camera Preview、OpenCV Tutorial 2 - Mixed Processing、OpenCV Tutorial 3 - Camera Control、OpenCV Sample - 4 puzzle、OpenCV Sample - camera-calibration、OpenCV Sample - color-blob-detection、OpenCV Sample - face-detection、OpenCV Sample - image-manipulations、OpenCV Sample - native-activity、OpenCV Library - 2.4.10），再加上OpenCV Manager項目總計11個項目，項目如圖：
OpenCV Manager - 2.4.10
官方提供的Demo運行需要OpenCV Manager項目的支持，該項目負責匹配手機加載庫文件，通過服務綁定進行通訊。
如果未安裝它，并運行Demo會出現提示框：OpenCV Manager package was not found! Try to install it? 固然如果直接使用它的庫運行是不會出現此情況的。緣由就是該項目只是做加載庫的工作。
項目如圖：
官方給出解釋：
加載庫的代碼以下：
public class BinderConnector {
private static boolean mIsReady = false;
private MarketConnector mMarket;
static {
try {
System.loadLibrary("OpenCVEngine");
System.loadLibrary("OpenCVEngine_jni");
mIsReady = true;
} catch (UnsatisfiedLinkError localUnsatisfiedLinkError) {
mIsReady = false;
localUnsatisfiedLinkError.printStackTrace();
}
}
public BinderConnector(MarketConnector paramMarketConnector) {
this.mMarket = paramMarketConnector;
}
private native void Final();
private native boolean Init(MarketConnector paramMarketConnector);
public native IBinder Connect();
public boolean Disconnect() {
if (mIsReady)
Final();
return mIsReady;
}
public boolean Init() {
boolean bool = false;
if (mIsReady)
bool = Init(this.mMarket);
return bool;
}
}
public class HardwareDetector { //硬件匹配
public static final int ARCH_ARMv5 = 0x4000000;
public static final int ARCH_ARMv6 = 0x8000000;
public static final int ARCH_ARMv7 = 0x10000000;
public static final int ARCH_ARMv8 = 0x20000000;
public static final int ARCH_MIPS = 0x40000000;
public static final int ARCH_UNKNOWN = ⑴;
public static final int ARCH_X64 = 0x2000000;
public static final int ARCH_X86 = 0x1000000;
public static final int FEATURES_HAS_GPU = 65536;
public static final int FEATURES_HAS_NEON = 8;
public static final int FEATURES_HAS_NEON2 = 22;
public static final int FEATURES_HAS_SSE = 1;
public static final int FEATURES_HAS_SSE2 = 2;
public static final int FEATURES_HAS_SSE3 = 4;
public static final int FEATURES_HAS_VFPv3 = 2;
public static final int FEATURES_HAS_VFPv3d16 = 1;
public static final int FEATURES_HAS_VFPv4 = 4;
public static final int PLATFORM_TEGRA = 1;
public static final int PLATFORM_TEGRA2 = 2;
public static final int PLATFORM_TEGRA3 = 3;
public static final int PLATFORM_TEGRA4 = 5;
public static final int PLATFORM_TEGRA4i = 4;
public static final int PLATFORM_TEGRA5 = 6;
public static final int PLATFORM_UNKNOWN = ⑴;
public static boolean mIsReady = false;
static {
try {
System.loadLibrary("OpenCVEngine");
System.loadLibrary("OpenCVEngine_jni");
mIsReady = true;
} catch (UnsatisfiedLinkError localUnsatisfiedLinkError) {
mIsReady = false;
localUnsatisfiedLinkError.printStackTrace();
}
}
public static native int DetectKnownPlatforms();
public static native int GetCpuID();
public static native String GetPlatformName();
public static native int GetProcessorCount();
}
public class OpenCVLibraryInfo {
private String mLibraryList;
private long mNativeObj;
private String mPackageName;
private String mVersionName;
public OpenCVLibraryInfo(String paramString) {
mNativeObj = open(paramString + "/libopencv_info.so");
if (this.mNativeObj == 0L)
return;
this.mPackageName = getPackageName(this.mNativeObj);
this.mLibraryList = getLibraryList(this.mNativeObj);
this.mVersionName = getVersionName(this.mNativeObj);
close(this.mNativeObj);
}
private native void close(long paramLong);
private native String getLibraryList(long paramLong);
private native String getPackageName(long paramLong);
private native String getVersionName(long paramLong);
private native long open(String paramString);
public String libraryList() {
return this.mLibraryList;
}
public String packageName() {
return this.mPackageName;
}
public boolean status() {
if (mNativeObj == 0L || mLibraryList.length() == 0)
return false;
return true;
}
public String versionName() {
return this.mVersionName;
}
}
//關鍵服務 demo中綁定的服務就該服務 該服務就是匹配手機加載庫
public class OpenCVEngineService extends Service {
private static final String TAG = "OpenCVEngine/Service";
private IBinder mEngineInterface = null;
private MarketConnector mMarket;
private BinderConnector mNativeBinder;
public void OnDestroy() {
Log.i("OpenCVEngine/Service", "OpenCV Engine service destruction");
this.mNativeBinder.Disconnect();
}
public IBinder onBind(Intent paramIntent) {
Log.i("OpenCVEngine/Service", "Service onBind called for intent "
+ paramIntent.toString());
return this.mEngineInterface;
}
public void onCreate() {
Log.i("OpenCVEngine/Service", "Service starting");
super.onCreate();
Log.i("OpenCVEngine/Service", "Engine binder component creating");
this.mMarket = new MarketConnector(getBaseContext());
this.mNativeBinder = new BinderConnector(this.mMarket);
if (this.mNativeBinder.Init()) {
this.mEngineInterface = this.mNativeBinder.Connect();
Log.i("OpenCVEngine/Service", "Service started successfully");
}
else {
Log.e("OpenCVEngine/Service",
"Cannot initialize native part of OpenCV Manager!");
Log.e("OpenCVEngine/Service", "Using stub instead");
return;
}
this.mEngineInterface = new OpenCVEngineInterface(this);
}
public boolean onUnbind(Intent paramIntent) {
Log.i("OpenCVEngine/Service", "Service onUnbind called for intent "
+ paramIntent.toString());
return true;
}
}
它的AndroidManifest.xml 以下：
<?xml version="1.0" encoding="utf⑻"?>
<manifest android:versionCode="2191" android:versionName="2.19" package="org.opencv.engine"
xmlns:android="http://schemas.android.com/apk/res/android">
<uses-feature android:name="android.hardware.touchscreen" android:required="false" />
<application android:label="@string/app_name" android:icon="@drawable/icon">
<service android:name="OpenCVEngineService" android:exported="true" android:process=":OpenCVEngineProcess">
<intent-filter>
<action android:name="org.opencv.engine.BIND" />
</intent-filter>
</service>
<activity android:label="@string/app_name" android:name="org.opencv.engine.manager.ManagerActivity" android:screenOrientation="portrait">
<intent-filter>
<action android:name="android.intent.action.MAIN" />
<category android:name="android.intent.category.LAUNCHER" />
</intent-filter>
</activity>
</application>
</manifest>
OpenCV Tutorial 1 - Camera Preview
Demo就1個文件，使用攝像機預覽，Demo中提供了兩種方法，1種是Java層調用，1種是Native層調用。
如圖：
關鍵控件以下：
<org.opencv.android.JavaCameraView
android:layout_width="fill_parent"
android:layout_height="fill_parent"
android:visibility="gone"
android:id="@+id/tutorial1_activity_java_surface_view"
opencv:show_fps="true"
opencv:camera_id="any" />
<org.opencv.android.NativeCameraView
android:layout_width="fill_parent"
android:layout_height="fill_parent"
android:visibility="gone"
android:id="@+id/tutorial1_activity_native_surface_view"
opencv:show_fps="true"
opencv:camera_id="any" />
OpenCV Tutorial 2 - Mixed Processing
該Demo就1個Java文件和1個C++文件，實現4中混合處理。
如圖：
本地代碼以下：
JNIEXPORT void JNICALL Java_org_opencv_samples_tutorial2_Tutorial2Activity_FindFeatures(JNIEnv*, jobject, jlong addrGray, jlong addrRgba)
{
Mat& mGr = *(Mat*)addrGray;
Mat& mRgb = *(Mat*)addrRgba;
vector<KeyPoint> v;
FastFeatureDetector detector(50);
detector.detect(mGr, v);
for( unsigned int i = 0; i < v.size(); i++ )
{
const KeyPoint& kp = v[i];
circle(mRgb, Point(kp.pt.x, kp.pt.y), 10, Scalar(255,0,0,255));
}
}
使用的控件以下：
<org.opencv.android.JavaCameraView
android:layout_width="fill_parent"
android:layout_height="fill_parent"
android:id="@+id/tutorial2_activity_surface_view" />
OpenCV Tutorial 3 - Camera Control
該Demo就2個Java文件，攝像頭控制，控制色彩顯示、攝像分辨率。
效果如圖：
關鍵代碼：
使用的控件
<org.opencv.samples.tutorial3.Tutorial3View
android:layout_width="match_parent"
android:layout_height="match_parent"
android:visibility="gone"
android:id="@+id/tutorial3_activity_java_surface_view" />
public class Tutorial3View extends JavaCameraView implements PictureCallback {
private static final String TAG = "Sample::Tutorial3View";
private String mPictureFileName;
public Tutorial3View(Context context, AttributeSet attrs) {
super(context, attrs);
}
public List<String> getEffectList() {
return mCamera.getParameters().getSupportedColorEffects();
}
public boolean isEffectSupported() {
return (mCamera.getParameters().getColorEffect() != null);
}
public String getEffect() {
return mCamera.getParameters().getColorEffect();
}
public void setEffect(String effect) {
Camera.Parameters params = mCamera.getParameters();
params.setColorEffect(effect);
mCamera.setParameters(params);
}
public List<Size> getResolutionList() {
return mCamera.getParameters().getSupportedPreviewSizes();
}
public void setResolution(Size resolution) {
disconnectCamera();
mMaxHeight = resolution.height;
mMaxWidth = resolution.width;
connectCamera(getWidth(), getHeight());
}
public Size getResolution() {
return mCamera.getParameters().getPreviewSize();
}
public void takePicture(final String fileName) {
Log.i(TAG, "Taking picture");
this.mPictureFileName = fileName;
// Postview and jpeg are sent in the same buffers if the queue is not empty when performing a capture.
// Clear up buffers to avoid mCamera.takePicture to be stuck because of a memory issue
mCamera.setPreviewCallback(null);
// PictureCallback is implemented by the current class
mCamera.takePicture(null, null, this);
}
@Override
public void onPictureTaken(byte[] data, Camera camera) {
Log.i(TAG, "Saving a bitmap to file");
// The camera preview was automatically stopped. Start it again.
mCamera.startPreview();
mCamera.setPreviewCallback(this);
// Write the image in a file (in jpeg format)
try {
FileOutputStream fos = new FileOutputStream(mPictureFileName);
fos.write(data);
fos.close();
} catch (java.io.IOException e) {
Log.e("PictureDemo", "Exception in photoCallback", e);
}
}
}
OpenCV Sample - 4 puzzle
該Demo就兩個Java文件，實現攝像格式錯亂輸出。
效果如圖：
主要代碼以下：
public class Puzzle15Processor { //攝像圖片轉換
private static final int GRID_SIZE = 4;
private static final int GRID_AREA = GRID_SIZE * GRID_SIZE;
private static final int GRID_EMPTY_INDEX = GRID_AREA - 1;
private static final String TAG = "Puzzle15Processor";
private static final Scalar GRID_EMPTY_COLOR = new Scalar(0x33, 0x33, 0x33, 0xFF);
private int[] mIndexes;
private int[] mTextWidths;
private int[] mTextHeights;
private Mat mRgba15;
private Mat[] mCells15;
private boolean mShowTileNumbers = true;
public Puzzle15Processor() {
mTextWidths = new int[GRID_AREA];
mTextHeights = new int[GRID_AREA];
mIndexes = new int [GRID_AREA];
for (int i = 0; i < GRID_AREA; i++)
mIndexes[i] = i;
}
/* this method is intended to make processor prepared for a new game */
public synchronized void prepareNewGame() {
do {
shuffle(mIndexes);
} while (!isPuzzleSolvable());
}
/* This method is to make the processor know the size of the frames that
* will be delivered via puzzleFrame.
* If the frames will be different size - then the result is unpredictable
*/
public synchronized void prepareGameSize(int width, int height) {
mRgba15 = new Mat(height, width, CvType.CV_8UC4);
mCells15 = new Mat[GRID_AREA];
for (int i = 0; i < GRID_SIZE; i++) {
for (int j = 0; j < GRID_SIZE; j++) {
int k = i * GRID_SIZE + j;
mCells15[k] = mRgba15.submat(i * height / GRID_SIZE, (i + 1) * height / GRID_SIZE, j * width / GRID_SIZE, (j + 1) * width / GRID_SIZE);
}
}
for (int i = 0; i < GRID_AREA; i++) {
Size s = Core.getTextSize(Integer.toString(i + 1), 3/* CV_FONT_HERSHEY_COMPLEX */, 1, 2, null);
mTextHeights[i] = (int) s.height;
mTextWidths[i] = (int) s.width;
}
}
/* this method to be called from the outside. it processes the frame and shuffles
* the tiles as specified by mIndexes array
*/
public synchronized Mat puzzleFrame(Mat inputPicture) {
Mat[] cells = new Mat[GRID_AREA];
int rows = inputPicture.rows();
int cols = inputPicture.cols();
rows = rows - rows%4;
cols = cols - cols%4;
for (int i = 0; i < GRID_SIZE; i++) {
for (int j = 0; j < GRID_SIZE; j++) {
int k = i * GRID_SIZE + j;
cells[k] = inputPicture.submat(i * inputPicture.rows() / GRID_SIZE, (i + 1) * inputPicture.rows() / GRID_SIZE, j * inputPicture.cols()/ GRID_SIZE, (j + 1) * inputPicture.cols() / GRID_SIZE);
}
}
rows = rows - rows%4;
cols = cols - cols%4;
// copy shuffled tiles
for (int i = 0; i < GRID_AREA; i++) {
int idx = mIndexes[i];
if (idx == GRID_EMPTY_INDEX)
mCells15[i].setTo(GRID_EMPTY_COLOR);
else {
cells[idx].copyTo(mCells15[i]);
if (mShowTileNumbers) {
Core.putText(mCells15[i], Integer.toString(1 + idx), new Point((cols / GRID_SIZE - mTextWidths[idx]) / 2,
(rows / GRID_SIZE + mTextHeights[idx]) / 2), 3/* CV_FONT_HERSHEY_COMPLEX */, 1, new Scalar(255, 0, 0, 255), 2);
}
}
}
for (int i = 0; i < GRID_AREA; i++)
cells[i].release();
drawGrid(cols, rows, mRgba15);
return mRgba15;
}
public void toggleTileNumbers() {
mShowTileNumbers = !mShowTileNumbers;
}
public void deliverTouchEvent(int x, int y) {
int rows = mRgba15.rows();
int cols = mRgba15.cols();
int row = (int) Math.floor(y * GRID_SIZE / rows);
int col = (int) Math.floor(x * GRID_SIZE / cols);
if (row < 0 || row >= GRID_SIZE || col < 0 || col >= GRID_SIZE) {
Log.e(TAG, "It is not expected to get touch event outside of picture");
return ;
}
int idx = row * GRID_SIZE + col;
int idxtoswap = ⑴;
// left
if (idxtoswap < 0 && col > 0)
if (mIndexes[idx - 1] == GRID_EMPTY_INDEX)
idxtoswap = idx - 1;
// right
if (idxtoswap < 0 && col < GRID_SIZE - 1)
if (mIndexes[idx + 1] == GRID_EMPTY_INDEX)
idxtoswap = idx + 1;
// top
if (idxtoswap < 0 && row > 0)
if (mIndexes[idx - GRID_SIZE] == GRID_EMPTY_INDEX)
idxtoswap = idx - GRID_SIZE;
// bottom
if (idxtoswap < 0 && row < GRID_SIZE - 1)
if (mIndexes[idx + GRID_SIZE] == GRID_EMPTY_INDEX)
idxtoswap = idx + GRID_SIZE;
// swap
if (idxtoswap >= 0) {
synchronized (this) {
int touched = mIndexes[idx];
mIndexes[idx] = mIndexes[idxtoswap];
mIndexes[idxtoswap] = touched;
}
}
}
private void drawGrid(int cols, int rows, Mat drawMat) {
for (int i = 1; i < GRID_SIZE; i++) {
Core.line(drawMat, new Point(0, i * rows / GRID_SIZE), new Point(cols, i * rows / GRID_SIZE), new Scalar(0, 255, 0, 255), 3);
Core.line(drawMat, new Point(i * cols / GRID_SIZE, 0), new Point(i * cols / GRID_SIZE, rows), new Scalar(0, 255, 0, 255), 3);
}
}
private static void shuffle(int[] array) {
for (int i = array.length; i > 1; i--) {
int temp = array[i - 1];
int randIx = (int) (Math.random() * i);
array[i - 1] = array[randIx];
array[randIx] = temp;
}
}
private boolean isPuzzleSolvable() {
int sum = 0;
for (int i = 0; i < GRID_AREA; i++) {
if (mIndexes[i] == GRID_EMPTY_INDEX)
sum += (i / GRID_SIZE) + 1;
else {
int smaller = 0;
for (int j = i + 1; j < GRID_AREA; j++) {
if (mIndexes[j] < mIndexes[i])
smaller++;
}
sum += smaller;
}
}
return sum % 2 == 0;
}
}
OpenCV Sample - camera-calibration
該Demo就4個Java文件，實現攝像校準。
效果如圖：
使用的控件：
<org.opencv.android.JavaCameraView
android:layout_width="fill_parent"
android:layout_height="fill_parent"
android:id="@+id/camera_calibration_java_surface_view" />
OpenCV Sample - color-blob-detection
該Demo就兩個Java文件，實現色斑檢測。
效果如圖：
使用的控件：
<org.opencv.android.JavaCameraView
android:layout_width="fill_parent"
android:layout_height="fill_parent"
android:id="@+id/color_blob_detection_activity_surface_view" />
public class ColorBlobDetector { //匹配
// Lower and Upper bounds for range checking in HSV color space
private Scalar mLowerBound = new Scalar(0);
private Scalar mUpperBound = new Scalar(0);
// Minimum contour area in percent for contours filtering
private static double mMinContourArea = 0.1;
// Color radius for range checking in HSV color space
private Scalar mColorRadius = new Scalar(25,50,50,0);
private Mat mSpectrum = new Mat();
private List<MatOfPoint> mContours = new ArrayList<MatOfPoint>();
// Cache
Mat mPyrDownMat = new Mat();
Mat mHsvMat = new Mat();
Mat mMask = new Mat();
Mat mDilatedMask = new Mat();
Mat mHierarchy = new Mat();
public void setColorRadius(Scalar radius) {
mColorRadius = radius;
}
public void setHsvColor(Scalar hsvColor) {
double minH = (hsvColor.val[0] >= mColorRadius.val[0]) ? hsvColor.val[0]-mColorRadius.val[0] : 0;
double maxH = (hsvColor.val[0]+mColorRadius.val[0] <= 255) ? hsvColor.val[0]+mColorRadius.val[0] : 255;
mLowerBound.val[0] = minH;
mUpperBound.val[0] = maxH;
mLowerBound.val[1] = hsvColor.val[1] - mColorRadius.val[1];
mUpperBound.val[1] = hsvColor.val[1] + mColorRadius.val[1];
mLowerBound.val[2] = hsvColor.val[2] - mColorRadius.val[2];
mUpperBound.val[2] = hsvColor.val[2] + mColorRadius.val[2];
mLowerBound.val[3] = 0;
mUpperBound.val[3] = 255;
Mat spectrumHsv = new Mat(1, (int)(maxH-minH), CvType.CV_8UC3);
for (int j = 0; j < maxH-minH; j++) {
byte[] tmp = {(byte)(minH+j), (byte)255, (byte)255};
spectrumHsv.put(0, j, tmp);
}
Imgproc.cvtColor(spectrumHsv, mSpectrum, Imgproc.COLOR_HSV2RGB_FULL, 4);
}
public Mat getSpectrum() {
return mSpectrum;
}
public void setMinContourArea(double area) {
mMinContourArea = area;
}
public void process(Mat rgbaImage) {
Imgproc.pyrDown(rgbaImage, mPyrDownMat);
Imgproc.pyrDown(mPyrDownMat, mPyrDownMat);
Imgproc.cvtColor(mPyrDownMat, mHsvMat, Imgproc.COLOR_RGB2HSV_FULL);
Core.inRange(mHsvMat, mLowerBound, mUpperBound, mMask);
Imgproc.dilate(mMask, mDilatedMask, new Mat());
List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Imgproc.findContours(mDilatedMask, contours, mHierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
// Find max contour area
double maxArea = 0;
Iterator<MatOfPoint> each = contours.iterator();
while (each.hasNext()) {
MatOfPoint wrapper = each.next();
double area = Imgproc.contourArea(wrapper);
if (area > maxArea)
maxArea = area;
}
// Filter contours by area and resize to fit the original image size
mContours.clear();
each = contours.iterator();
while (each.hasNext()) {
MatOfPoint contour = each.next();
if (Imgproc.contourArea(contour) > mMinContourArea*maxArea) {
Core.multiply(contour, new Scalar(4,4), contour);
mContours.add(contour);
}
}
}
public List<MatOfPoint> getContours() {
return mContours;
}
}
OpenCV Sample - face-detection
該Demo就兩個Java文件和兩個C++文件，實現匹配臉。
效果如圖：
使用的控件：
<org.opencv.android.JavaCameraView
android:layout_width="fill_parent"
android:layout_height="fill_parent"
android:id="@+id/fd_activity_surface_view" />
public class DetectionBasedTracker
{
public DetectionBasedTracker(String cascadeName, int minFaceSize) {
mNativeObj = nativeCreateObject(cascadeName, minFaceSize);
}
public void start() {
nativeStart(mNativeObj);
}
public void stop() {
nativeStop(mNativeObj);
}
public void setMinFaceSize(int size) {
nativeSetFaceSize(mNativeObj, size);
}
public void detect(Mat imageGray, MatOfRect faces) {
nativeDetect(mNativeObj, imageGray.getNativeObjAddr(), faces.getNativeObjAddr());
}
public void release() {
nativeDestroyObject(mNativeObj);
mNativeObj = 0;
}
private long mNativeObj = 0;
private static native long nativeCreateObject(String cascadeName, int minFaceSize);
private static native void nativeDestroyObject(long thiz);
private static native void nativeStart(long thiz);
private static native void nativeStop(long thiz);
private static native void nativeSetFaceSize(long thiz, int size);
private static native void nativeDetect(long thiz, long inputImage, long faces);
}
OpenCV Sample - image-manipulations
該Demo就1個Java文件，實現圖片操作。
效果如圖：
使用的控件：
<org.opencv.android.JavaCameraView
android:layout_width="fill_parent"
android:layout_height="fill_parent"
android:id="@+id/image_manipulations_activity_surface_view" />
實現CvCameraViewListener2接口，從而操作圖片。
OpenCV Sample - native-activity
該Demo就1個Java文件和1個C++文件，實現本地界面顯示圖片。
效果如圖：
本地代碼以下：
