Android studio opencv图像处理如何运行得更快?
我正在使用OpenCV库开发android studio。我正在处理ColorBlobDetectionActivity类,所以我想重新加强它的处理。OpenCV处理所有屏幕,但我只想处理特定区域,以便在android摄像头上更快。有人能帮我吗 这里是ColorBlobDetectionActivity类代码:Android studio opencv图像处理如何运行得更快?,android-studio,opencv3.0,Android Studio,Opencv3.0,我正在使用OpenCV库开发android studio。我正在处理ColorBlobDetectionActivity类,所以我想重新加强它的处理。OpenCV处理所有屏幕,但我只想处理特定区域,以便在android摄像头上更快。有人能帮我吗 这里是ColorBlobDetectionActivity类代码: private boolean mIsColorSelected = false; private Mat mRgba; pr
private boolean mIsColorSelected = false;
private Mat mRgba;
private Scalar mBlobColorRgba;
private Scalar mBlobColorHsv;
private ColorBlobDetector mDetector;
private Mat mSpectrum;
private Size SPECTRUM_SIZE;
private Scalar CONTOUR_COLOR;
private CameraBridgeViewBase mOpenCvCameraView;
private BaseLoaderCallback mLoaderCallback = new BaseLoaderCallback(this) {
@Override
public void onManagerConnected(int status) {
switch (status) {
case LoaderCallbackInterface.SUCCESS:
{
Log.i(TAG, "OpenCV loaded successfully");
mOpenCvCameraView.enableView();
mOpenCvCameraView.setOnTouchListener(ColorBlobDetectionActivity.this);
} break;
default:
{
super.onManagerConnected(status);
} break;
}
}
};
public ColorBlobDetectionActivity() {
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);
requestWindowFeature(Window.FEATURE_NO_TITLE);
getWindow().addFlags(WindowManager.LayoutParams.FLAG_KEEP_SCREEN_ON);
setContentView(R.layout.color_blob_detection_surface_view);
mOpenCvCameraView = (CameraBridgeViewBase) findViewById(R.id.color_blob_detection_activity_surface_view);
mOpenCvCameraView.setVisibility(SurfaceView.VISIBLE);
mOpenCvCameraView.setCvCameraViewListener(this);
}
@Override
public void onPause()
{
super.onPause();
if (mOpenCvCameraView != null)
mOpenCvCameraView.disableView();
}
@Override
public void onResume()
{
super.onResume();
if (!OpenCVLoader.initDebug()) {
Log.d(TAG, "Internal OpenCV library not found. Using OpenCV Manager for initialization");
OpenCVLoader.initAsync(OpenCVLoader.OPENCV_VERSION_3_0_0, this, mLoaderCallback);
} else {
Log.d(TAG, "OpenCV library found inside package. Using it!");
mLoaderCallback.onManagerConnected(LoaderCallbackInterface.SUCCESS);
}
}
public void onDestroy() {
super.onDestroy();
if (mOpenCvCameraView != null)
mOpenCvCameraView.disableView();
}
public void onCameraViewStarted(int width, int height) {
mRgba = new Mat(height, width, CvType.CV_8UC4);
mDetector = new ColorBlobDetector();
mSpectrum = new Mat();
mBlobColorRgba = new Scalar(255);
mBlobColorHsv = new Scalar(255);
SPECTRUM_SIZE = new Size(200, 64);
CONTOUR_COLOR = new Scalar(255,0,0,255);
}
public void onCameraViewStopped() {
mRgba.release();
}
public boolean onTouch(View v, MotionEvent event) {
int cols = mRgba.cols();
int rows = mRgba.rows();
int xOffset = (mOpenCvCameraView.getWidth() - cols) / 2;
int yOffset = (mOpenCvCameraView.getHeight() - rows) / 2;
int x = (int)event.getX() - xOffset;
int y = (int)event.getY() - yOffset;
Log.i(TAG, "Touch image coordinates: (" + x + ", " + y + ")");
if ((x < 0) || (y < 0) || (x > cols) || (y > rows)) return false;
Rect touchedRect = new Rect();
touchedRect.x = (x>4) ? x-4 : 0;
touchedRect.y = (y>4) ? y-4 : 0;
touchedRect.width = (x+4 < cols) ? x + 4 - touchedRect.x : cols - touchedRect.x;
touchedRect.height = (y+4 < rows) ? y + 4 - touchedRect.y : rows - touchedRect.y;
Mat touchedRegionRgba = mRgba.submat(touchedRect);
Mat touchedRegionHsv = new Mat();
Imgproc.cvtColor(touchedRegionRgba, touchedRegionHsv, Imgproc.COLOR_RGB2HSV_FULL);
// Calculate average color of touched region
mBlobColorHsv = Core.sumElems(touchedRegionHsv);
int pointCount = touchedRect.width*touchedRect.height;
for (int i = 0; i < mBlobColorHsv.val.length; i++)
mBlobColorHsv.val[i] /= pointCount;
mBlobColorRgba = converScalarHsv2Rgba(mBlobColorHsv);
Log.i(TAG, "Touched rgba color: (" + mBlobColorRgba.val[0] + ", " + mBlobColorRgba.val[1] +
", " + mBlobColorRgba.val[2] + ", " + mBlobColorRgba.val[3] + ")");
mDetector.setHsvColor(mBlobColorHsv);
Imgproc.resize(mDetector.getSpectrum(), mSpectrum, SPECTRUM_SIZE);
mIsColorSelected = true;
touchedRegionRgba.release();
touchedRegionHsv.release();
return false; // don't need subsequent touch events
}
public Mat onCameraFrame(CvCameraViewFrame inputFrame) {
mRgba = inputFrame.rgba();
if (mIsColorSelected) {
mDetector.process(mRgba);
List<MatOfPoint> contours = mDetector.getContours();
Log.e(TAG, "Contours count: " + contours.size());
Imgproc.drawContours(mRgba, contours, -1, CONTOUR_COLOR);
Mat colorLabel = mRgba.submat(4, 68, 4, 68);
colorLabel.setTo(mBlobColorRgba);
Mat spectrumLabel = mRgba.submat(4, 4 + mSpectrum.rows(), 70, 70 + mSpectrum.cols());
mSpectrum.copyTo(spectrumLabel);
}
return mRgba;
}
private Scalar converScalarHsv2Rgba(Scalar hsvColor) {
Mat pointMatRgba = new Mat();
Mat pointMatHsv = new Mat(1, 1, CvType.CV_8UC3, hsvColor);
Imgproc.cvtColor(pointMatHsv, pointMatRgba, Imgproc.COLOR_HSV2RGB_FULL, 4);
return new Scalar(pointMatRgba.get(0, 0));
}
private boolean mIsColorSelected=false;
私人Mat mRgba;
私有标量mBlobColorRgba;
专用标量MBV-HSV;
专用ColorBlobDetector mDetector;
私有矩阵谱;
私有大小和频谱大小;
私有标量轮廓颜色;
私人摄像机BridgeViewBase mOpenCvCameraView;
专用BaseLoaderCallback mlLoaderCallback=新BaseLoaderCallback(此){
@凌驾
已连接管理器上的公共无效(int状态){
开关(状态){
案例加载程序CallbackInterface.SUCCESS:
{
Log.i(标记“OpenCV已成功加载”);
mOpenCvCameraView.enableView();
mOpenCvCameraView.setOnTouchListener(ColorBlobDetectionActivity.this);
}中断;
违约:
{
超级管理器已连接(状态);
}中断;
}
}
};
公共ColorBlobDetectionActivity(){
Log.i(标记“实例化新”+this.getClass());
}
/**在首次创建活动时调用*/
@凌驾
创建时的公共void(Bundle savedInstanceState){
Log.i(标记“calledoncreate”);
super.onCreate(savedInstanceState);
requestWindowFeature(窗口。功能\u无\u标题);
getWindow().addFlags(WindowManager.LayoutParams.FLAG\u保持屏幕打开);
setContentView(R.layout.color\u blob\u detection\u surface\u view);
mOpenCvCameraView=(CameraBridgeViewBase)findViewById(R.id.color\u blob\u detection\u activity\u surface\u view);
mOpenCvCameraView.setVisibility(SurfaceView.VISIBLE);
mOpenCvCameraView.setCvCameraViewListener(本);
}
@凌驾
公共无效暂停()
{
super.onPause();
if(mOpenCvCameraView!=null)
mOpenCvCameraView.disableView();
}
@凌驾
恢复时公开作废()
{
super.onResume();
如果(!OpenCVLoader.initDebug()){
d(标记“找不到内部OpenCV库。使用OpenCV管理器进行初始化”);
initAsync(OpenCVLoader.OPENCV_VERSION_3_0_0,this,mLoaderCallback);
}否则{
d(标记“在包中找到OpenCV库。正在使用它!”);
mLoaderCallback.onManagerConnected(LoaderCallbackInterface.SUCCESS);
}
}
公共空间{
super.ondestory();
if(mOpenCvCameraView!=null)
mOpenCvCameraView.disableView();
}
开始时的公共空隙(整数宽度、整数高度){
mRgba=新垫(高度、宽度、CvType.CV_8UC4);
mDetector=新的ColorBlobDetector();
msspectrum=新的Mat();
mBlobColorRgba=新标量(255);
mBlobColorHsv=新标量(255);
光谱尺寸=新尺寸(200,64);
轮廓颜色=新标量(255,0,0255);
}
CAMERAVIEWSTOPPED()上的公共空白{
mRgba.release();
}
公共布尔onTouch(视图v,运动事件){
int cols=mRgba.cols();
int rows=mRgba.rows();
int xOffset=(mOpenCvCameraView.getWidth()-cols)/2;
int yOffset=(mOpenCvCameraView.getHeight()-rows)/2;
int x=(int)event.getX()-xOffset;
int y=(int)event.getY()-yOffset;
Log.i(标签,“触摸图像坐标:(“+x+”,“+y+”));
if((x<0)| |(y<0)| |(x>cols)| |(y>rows))返回false;
Rect touchedRect=new Rect();
touchedRect.x=(x>4)?x-4:0;
touchedRect.y=(y>4)?y-4:0;
touchedRect.width=(x+4
}怎么做?告诉我如何优化?如何优化?告诉我如何优化?