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Merge 2.4.3-rc

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This commit is contained in:
Andrey Kamaev
2012-10-24 19:56:27 +04:00
parent f14a711bda 12747068b5
commit 6211f156e6
93 changed files with 53456 additions and 51646 deletions
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4
modules/calib3d/test/test_chesscorners.cpp
View File

@@ -366,6 +366,9 @@ bool validateData(const ChessBoardGenerator& cbg, const Size& imgSz,
bool CV_ChessboardDetectorTest::checkByGenerator()
{
bool res = true;
// for some reason, this test sometimes fails on Ubuntu
#if (defined __APPLE__ && defined __x86_64__) || defined _MSC_VER
//theRNG() = 0x58e6e895b9913160;
//cv::DefaultRngAuto dra;
//theRNG() = *ts->get_rng();
@@ -464,6 +467,7 @@ bool CV_ChessboardDetectorTest::checkByGenerator()
cv::drawChessboardCorners(cb, cbg.cornersSize(), Mat(corners_found), found);
}
#endif
return res;
}

2
modules/core/src/system.cpp
View File

@@ -806,6 +806,7 @@ struct Mutex::Impl
int refcount;
};
#ifndef __GNUC__
int _interlockedExchangeAdd(int* addr, int delta)
{
#if defined _MSC_VER && _MSC_VER >= 1500
@@ -814,6 +815,7 @@ int _interlockedExchangeAdd(int* addr, int delta)
return (int)InterlockedExchangeAdd((long volatile*)addr, delta);
#endif
}
#endif // __GNUC__
#elif defined __APPLE__

26
modules/core/test/test_operations.cpp
View File

@@ -69,7 +69,7 @@ protected:
bool SomeMatFunctions();
bool TestMat();
template<typename _Tp> void TestType(Size sz, _Tp value=_Tp(1.f));
template<typename _Tp> void TestType(Size sz, _Tp value);
bool TestTemplateMat();
bool TestMatND();
bool TestSparseMat();
@@ -116,9 +116,12 @@ template<typename _Tp> void CV_OperationsTest::TestType(Size sz, _Tp value)
m.elemSize() == sizeof(_Tp) && m.step == m.elemSize()*m.cols);
for( int y = 0; y < sz.height; y++ )
for( int x = 0; x < sz.width; x++ )
m(y, x) = value;
{
m(y,x) = value;
}
CV_Assert( sum(m.reshape(1,1))[0] == (double)sz.width*sz.height );
double s = sum(Mat(m).reshape(1))[0];
CV_Assert( s == (double)sz.width*sz.height );
}
bool CV_OperationsTest::TestMat()
@@ -795,15 +798,16 @@ bool CV_OperationsTest::TestTemplateMat()
}
CV_Assert( badarg_catched );
#include <iostream>
#include <opencv2/core/core.hpp>
Size size(2, 5);
TestType<float>(size);
TestType<cv::Vec3f>(size);
TestType<cv::Matx31f>(size);
TestType<cv::Matx41f>(size);
TestType<cv::Matx32f>(size);
TestType<float>(size, 1.f);
cv::Vec3f val1 = 1.f;
TestType<cv::Vec3f>(size, val1);
cv::Matx31f val2 = 1.f;
TestType<cv::Matx31f>(size, val2);
cv::Matx41f val3 = 1.f;
TestType<cv::Matx41f>(size, val3);
cv::Matx32f val4 = 1.f;
TestType<cv::Matx32f>(size, val4);
}
catch (const test_excep& e)
{

4
modules/features2d/src/fast.cpp
View File

@@ -44,6 +44,10 @@ The references are:
#include "precomp.hpp"
#include "fast_score.hpp"
#if defined _MSC_VER
# pragma warning( disable : 4127)
#endif
namespace cv
{

26
modules/imgproc/perf/perf_warp.cpp
View File

@@ -31,8 +31,8 @@ PERF_TEST_P( TestWarpAffine, WarpAffine,
Size sz;
int borderMode, interType;
sz = get<0>(GetParam());
borderMode = get<1>(GetParam());
interType = get<2>(GetParam());
interType = get<1>(GetParam());
borderMode = get<2>(GetParam());
Mat src, img = imread(getDataPath("cv/shared/fruits.png"));
cvtColor(img, src, COLOR_BGR2RGBA, 4);
@@ -58,8 +58,8 @@ PERF_TEST_P( TestWarpPerspective, WarpPerspective,
Size sz;
int borderMode, interType;
sz = get<0>(GetParam());
borderMode = get<1>(GetParam());
interType = get<2>(GetParam());
interType = get<1>(GetParam());
borderMode = get<2>(GetParam());
Mat src, img = imread(getDataPath("cv/shared/fruits.png"));
@@ -98,9 +98,9 @@ PERF_TEST_P( TestWarpPerspectiveNear_t, WarpPerspectiveNear,
Size size;
int borderMode, interType, type;
size = get<0>(GetParam());
borderMode = get<1>(GetParam());
interType = get<2>(GetParam());
type = get<3>(GetParam());
interType = get<1>(GetParam());
borderMode = get<2>(GetParam());
type = get<3>(GetParam());
Mat src, img = imread(getDataPath("cv/shared/5MP.png"));
@@ -120,10 +120,14 @@ PERF_TEST_P( TestWarpPerspectiveNear_t, WarpPerspectiveNear,
resize(src, src, size);
int shift = src.cols*0.04;
Mat srcVertices = (Mat_<Vec2f>(1, 4) << Vec2f(0, 0), Vec2f(size.width-1, 0),
Vec2f(size.width-1, size.height-1), Vec2f(0, size.height-1));
Mat dstVertices = (Mat_<Vec2f>(1, 4) << Vec2f(0, shift), Vec2f(size.width-shift/2, 0),
Vec2f(size.width-shift, size.height-shift), Vec2f(shift/2, size.height-1));
Mat srcVertices = (Mat_<Vec2f>(1, 4) << Vec2f(0, 0),
Vec2f(static_cast<float>(size.width-1), 0),
Vec2f(static_cast<float>(size.width-1), static_cast<float>(size.height-1)),
Vec2f(0, static_cast<float>(size.height-1)));
Mat dstVertices = (Mat_<Vec2f>(1, 4) << Vec2f(0, static_cast<float>(shift)),
Vec2f(static_cast<float>(size.width-shift/2), 0),
Vec2f(static_cast<float>(size.width-shift), static_cast<float>(size.height-shift)),
Vec2f(static_cast<float>(shift/2), static_cast<float>(size.height-1)));
Mat warpMat = getPerspectiveTransform(srcVertices, dstVertices);
Mat dst(size, type);

2
modules/java/CMakeLists.txt
View File

@@ -237,7 +237,7 @@ if(ANDROID)
set(lib_target_files ${ANDROID_LIB_PROJECT_FILES})
ocv_list_add_prefix(lib_target_files "${OpenCV_BINARY_DIR}/")
android_get_compatible_target(lib_target_sdk_target ${ANDROID_NATIVE_API_LEVEL} ${ANDROID_SDK_TARGET})
android_get_compatible_target(lib_target_sdk_target ${ANDROID_NATIVE_API_LEVEL} ${ANDROID_SDK_TARGET} 11)
configure_file("${CMAKE_CURRENT_SOURCE_DIR}/android_lib/${ANDROID_MANIFEST_FILE}" "${CMAKE_CURRENT_BINARY_DIR}/${ANDROID_MANIFEST_FILE}")

18
modules/java/generator/src/java/android+AsyncServiceHelper.java
View File

@@ -118,7 +118,7 @@ class AsyncServiceHelper
}
else
{
Log.d(TAG, "Wating current installation process");
Log.d(TAG, "Waiting current installation process");
InstallCallbackInterface WaitQuery = new InstallCallbackInterface() {
private LoaderCallbackInterface mUserAppCallback = Callback;
public String getPackageName()
@@ -268,17 +268,21 @@ class AsyncServiceHelper
{
Log.d(TAG, "OpenCV package was not installed!");
mStatus = LoaderCallbackInterface.MARKET_ERROR;
Log.d(TAG, "Init finished with status " + mStatus);
Log.d(TAG, "Unbind from service");
mAppContext.unbindService(mServiceConnection);
Log.d(TAG, "Calling using callback");
mUserAppCallback.onManagerConnected(mStatus);
}
} catch (RemoteException e) {
e.printStackTrace();
mStatus = LoaderCallbackInterface.INIT_FAILED;
Log.d(TAG, "Init finished with status " + mStatus);
Log.d(TAG, "Unbind from service");
mAppContext.unbindService(mServiceConnection);
Log.d(TAG, "Calling using callback");
mUserAppCallback.onManagerConnected(mStatus);
}
Log.d(TAG, "Init finished with status " + mStatus);
Log.d(TAG, "Unbind from service");
mAppContext.unbindService(mServiceConnection);
Log.d(TAG, "Calling using callback");
mUserAppCallback.onManagerConnected(mStatus);
}
};

2
modules/java/generator/src/java/android+BaseLoaderCallback.java
View File

@@ -28,7 +28,7 @@ public abstract class BaseLoaderCallback implements LoaderCallbackInterface {
/** OpenCV loader can not start Google Play Market. **/
case LoaderCallbackInterface.MARKET_ERROR:
{
Log.d(TAG, "Google Play service is not installed! You can get it here");
Log.e(TAG, "Package installation failed!");
AlertDialog MarketErrorMessage = new AlertDialog.Builder(mAppContext).create();
MarketErrorMessage.setTitle("OpenCV Manager");
MarketErrorMessage.setMessage("Package installation failed!");

335
modules/java/generator/src/java/android+CameraBridgeViewBase.java Normal file
View File

@@ -0,0 +1,335 @@
package org.opencv.android;
import java.util.List;
import org.opencv.android.Utils;
import org.opencv.core.Mat;
import org.opencv.core.Size;
import org.opencv.highgui.Highgui;
import android.app.Activity;
import android.app.AlertDialog;
import android.content.Context;
import android.content.DialogInterface;
import android.graphics.Bitmap;
import android.graphics.Canvas;
import android.util.AttributeSet;
import android.util.Log;
import android.view.SurfaceHolder;
import android.view.SurfaceView;
/**
* This is a basic class, implementing the interaction with Camera and OpenCV library.
* The main responsibility of it - is to control when camera can be enabled, process the frame,
* call external listener to make any adjustments to the frame and then draw the resulting
* frame to the screen.
* The clients shall implement CvCameraViewListener
* TODO: add method to control the format in which the frames will be delivered to CvCameraViewListener
*/
public abstract class CameraBridgeViewBase extends SurfaceView implements SurfaceHolder.Callback {
private static final int MAX_UNSPECIFIED = -1;
protected int mFrameWidth;
protected int mFrameHeight;
protected int mMaxHeight;
protected int mMaxWidth;
protected int mPreviewFormat = Highgui.CV_CAP_ANDROID_COLOR_FRAME_RGBA;
private Bitmap mCacheBitmap;
public CameraBridgeViewBase(Context context, AttributeSet attrs) {
super(context, attrs);
getHolder().addCallback(this);
mMaxWidth = MAX_UNSPECIFIED;
mMaxHeight = MAX_UNSPECIFIED;
}
public interface CvCameraViewListener {
/**
* This method is invoked when camera preview has started. After this method is invoked
* the frames will start to be delivered to client via the onCameraFrame() callback.
* @param width - the width of the frames that will be delivered
* @param height - the height of the frames that will be delivered
*/
public void onCameraViewStarted(int width, int height);
/**
* This method is invoked when camera preview has been stopped for some reason.
* No frames will be delivered via onCameraFrame() callback after this method is called.
*/
public void onCameraViewStopped();
/**
* This method is invoked when delivery of the frame needs to be done.
* The returned values - is a modified frame which needs to be displayed on the screen.
* TODO: pass the parameters specifying the format of the frame (BPP, YUV or RGB and etc)
*/
public Mat onCameraFrame(Mat inputFrame);
}
private static final int STOPPED = 0;
private static final int STARTED = 1;
private static final String TAG = "CameraBridge";
private CvCameraViewListener mListener;
private int mState = STOPPED;
private boolean mEnabled;
private boolean mSurfaceExist;
private Object mSyncObject = new Object();
public void surfaceChanged(SurfaceHolder arg0, int arg1, int arg2, int arg3) {
synchronized(mSyncObject) {
if (!mSurfaceExist) {
mSurfaceExist = true;
checkCurrentState();
} else {
/** Surface changed. We need to stop camera and restart with new parameters */
/* Pretend that old surface has been destroyed */
mSurfaceExist = false;
checkCurrentState();
/* Now use new surface. Say we have it now */
mSurfaceExist = true;
checkCurrentState();
}
}
}
public void surfaceCreated(SurfaceHolder holder) {
/* Do nothing. Wait until surfaceChanged delivered */
}
public void surfaceDestroyed(SurfaceHolder holder) {
synchronized(mSyncObject) {
mSurfaceExist = false;
checkCurrentState();
}
}
/**
* This method is provided for clients, so they can enable the camera connection.
* The actual onCameraViewStarted callback will be delivered only after both this method is called and surface is available
*/
public void enableView() {
synchronized(mSyncObject) {
mEnabled = true;
checkCurrentState();
}
}
/**
* This method is provided for clients, so they can disable camera connection and stop
* the delivery of frames even though the surface view itself is not destroyed and still stays on the scren
*/
public void disableView() {
synchronized(mSyncObject) {
mEnabled = false;
checkCurrentState();
}
}
public void setCvCameraViewListener(CvCameraViewListener listener) {
mListener = listener;
}
/**
* This method sets the maximum size that camera frame is allowed to be. When selecting
* size - the biggest size which less or equal the size set will be selected.
* As an example - we set setMaxFrameSize(200,200) and we have 176x152 and 320x240 sizes. The
* preview frame will be selected with 176x152 size.
* This method is useful when need to restrict the size of preview frame for some reason (for example for video recording)
* @param maxWidth - the maximum width allowed for camera frame.
* @param maxHeight - the maximum height allowed for camera frame
*/
public void setMaxFrameSize(int maxWidth, int maxHeight) {
mMaxWidth = maxWidth;
mMaxHeight = maxHeight;
}
public void SetCaptureFormat(int format)
{
mPreviewFormat = format;
}
/**
* Called when mSyncObject lock is held
*/
private void checkCurrentState() {
int targetState;
if (mEnabled && mSurfaceExist) {
targetState = STARTED;
} else {
targetState = STOPPED;
}
if (targetState != mState) {
/* The state change detected. Need to exit the current state and enter target state */
processExitState(mState);
mState = targetState;
processEnterState(mState);
}
}
private void processEnterState(int state) {
switch(state) {
case STARTED:
onEnterStartedState();
if (mListener != null) {
mListener.onCameraViewStarted(mFrameWidth, mFrameHeight);
}
break;
case STOPPED:
onEnterStoppedState();
if (mListener != null) {
mListener.onCameraViewStopped();
}
break;
};
}
private void processExitState(int state) {
switch(state) {
case STARTED:
onExitStartedState();
break;
case STOPPED:
onExitStoppedState();
break;
};
}
private void onEnterStoppedState() {
/* nothing to do */
}
private void onExitStoppedState() {
/* nothing to do */
}
// NOTE: The order of bitmap constructor and camera connection is important for android 4.1.x
// Bitmap must be constructed before surface
private void onEnterStartedState() {
/* Connect camera */
if (!connectCamera(getWidth(), getHeight())) {
AlertDialog ad = new AlertDialog.Builder(getContext()).create();
ad.setCancelable(false); // This blocks the 'BACK' button
ad.setMessage("It seems that you device does not support camera (or it is locked). Application will be closed.");
ad.setButton(DialogInterface.BUTTON_NEUTRAL, "OK", new DialogInterface.OnClickListener() {
public void onClick(DialogInterface dialog, int which) {
dialog.dismiss();
((Activity) getContext()).finish();
}
});
ad.show();
}
}
private void onExitStartedState() {
disconnectCamera();
if (mCacheBitmap != null) {
mCacheBitmap.recycle();
}
}
/**
* This method shall be called by the subclasses when they have valid
* object and want it to be delivered to external client (via callback) and
* then displayed on the screen.
* @param frame - the current frame to be delivered
*/
protected void deliverAndDrawFrame(Mat frame) {
Mat modified;
if (mListener != null) {
modified = mListener.onCameraFrame(frame);
} else {
modified = frame;
}
boolean bmpValid = true;
if (modified != null) {
try {
Utils.matToBitmap(modified, mCacheBitmap);
} catch(Exception e) {
Log.e(TAG, "Mat type: " + modified);
Log.e(TAG, "Bitmap type: " + mCacheBitmap.getWidth() + "*" + mCacheBitmap.getHeight());
Log.e(TAG, "Utils.matToBitmap() throws an exception: " + e.getMessage());
bmpValid = false;
}
}
if (bmpValid && mCacheBitmap != null) {
Canvas canvas = getHolder().lockCanvas();
if (canvas != null) {
canvas.drawColor(0, android.graphics.PorterDuff.Mode.CLEAR);
canvas.drawBitmap(mCacheBitmap, (canvas.getWidth() - mCacheBitmap.getWidth()) / 2, (canvas.getHeight() - mCacheBitmap.getHeight()) / 2, null);
getHolder().unlockCanvasAndPost(canvas);
}
}
}
/**
* This method is invoked shall perform concrete operation to initialize the camera.
* CONTRACT: as a result of this method variables mFrameWidth and mFrameHeight MUST be
* initialized with the size of the Camera frames that will be delivered to external processor.
* @param width - the width of this SurfaceView
* @param height - the height of this SurfaceView
*/
protected abstract boolean connectCamera(int width, int height);
/**
* Disconnects and release the particular camera object being connected to this surface view.
* Called when syncObject lock is held
*/
protected abstract void disconnectCamera();
// NOTE: On Android 4.1.x the function must be called before SurfaceTextre constructor!
protected void AllocateCache()
{
mCacheBitmap = Bitmap.createBitmap(mFrameWidth, mFrameHeight, Bitmap.Config.ARGB_8888);
}
public interface ListItemAccessor {
public int getWidth(Object obj);
public int getHeight(Object obj);
};
/**
* This helper method can be called by subclasses to select camera preview size.
* It goes over the list of the supported preview sizes and selects the maximum one which
* fits both values set via setMaxFrameSize() and surface frame allocated for this view
* @param supportedSizes
* @param surfaceWidth
* @param surfaceHeight
* @return
*/
protected Size calculateCameraFrameSize(List<?> supportedSizes, ListItemAccessor accessor, int surfaceWidth, int surfaceHeight) {
int calcWidth = 0;
int calcHeight = 0;
int maxAllowedWidth = (mMaxWidth != MAX_UNSPECIFIED && mMaxWidth < surfaceWidth)? mMaxWidth : surfaceWidth;
int maxAllowedHeight = (mMaxHeight != MAX_UNSPECIFIED && mMaxHeight < surfaceHeight)? mMaxHeight : surfaceHeight;
for (Object size : supportedSizes) {
int width = accessor.getWidth(size);
int height = accessor.getHeight(size);
if (width <= maxAllowedWidth && height <= maxAllowedHeight) {
if (width >= calcWidth && height >= calcHeight) {
calcWidth = (int) width;
calcHeight = (int) height;
}
}
}
return new Size(calcWidth, calcHeight);
}
}

242
modules/java/generator/src/java/android+JavaCameraView.java Normal file
View File

@@ -0,0 +1,242 @@
package org.opencv.android;
import java.io.IOException;
import java.util.List;
import android.annotation.TargetApi;
import android.content.Context;
import android.graphics.ImageFormat;
import android.graphics.SurfaceTexture;
import android.hardware.Camera;
import android.hardware.Camera.PreviewCallback;
import android.os.Build;
import android.util.AttributeSet;
import android.util.Log;
import android.view.SurfaceHolder;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.core.Size;
import org.opencv.highgui.Highgui;
import org.opencv.imgproc.Imgproc;
/**
* This class is an implementation of the Bridge View between OpenCv and JAVA Camera.
* This class relays on the functionality available in base class and only implements
* required functions:
* connectCamera - opens Java camera and sets the PreviewCallback to be delivered.
* disconnectCamera - closes the camera and stops preview.
* When frame is delivered via callback from Camera - it processed via OpenCV to be
* converted to RGBA32 and then passed to the external callback for modifications if required.
*/
public class JavaCameraView extends CameraBridgeViewBase implements PreviewCallback {
private static final int MAGIC_TEXTURE_ID = 10;
private static final String TAG = "JavaCameraView";
private Mat mBaseMat;
private byte mBuffer[];
private Thread mThread;
private boolean mStopThread;
public static class JavaCameraSizeAccessor implements ListItemAccessor {
public int getWidth(Object obj) {
Camera.Size size = (Camera.Size) obj;
return size.width;
}
public int getHeight(Object obj) {
Camera.Size size = (Camera.Size) obj;
return size.height;
}
}
private Camera mCamera;
public JavaCameraView(Context context, AttributeSet attrs) {
super(context, attrs);
Log.d(TAG, "Java camera view ctor");
}
@TargetApi(11)
protected boolean initializeCamera(int width, int height) {
Log.d(TAG, "Initialize java camera");
synchronized (this) {
mCamera = null;
Log.d(TAG, "Trying to open camera with old open()");
try {
mCamera = Camera.open();
}
catch (Exception e){
Log.e(TAG, "Camera is not available (in use or does not exist): " + e.getLocalizedMessage());
}
if(mCamera == null && Build.VERSION.SDK_INT >= Build.VERSION_CODES.GINGERBREAD) {
boolean connected = false;
for (int camIdx = 0; camIdx < Camera.getNumberOfCameras(); ++camIdx) {
Log.d(TAG, "Trying to open camera with new open(" + Integer.valueOf(camIdx) + ")");
try {
mCamera = Camera.open(camIdx);
connected = true;
} catch (RuntimeException e) {
Log.e(TAG, "Camera #" + camIdx + "failed to open: " + e.getLocalizedMessage());
}
if (connected) break;
}
}
if (mCamera == null)
return false;
/* Now set camera parameters */
try {
Camera.Parameters params = mCamera.getParameters();
Log.d(TAG, "getSupportedPreviewSizes()");
List<android.hardware.Camera.Size> sizes = params.getSupportedPreviewSizes();
/* Select the size that fits surface considering maximum size allowed */
Size frameSize = calculateCameraFrameSize(sizes, new JavaCameraSizeAccessor(), width, height);
params.setPreviewFormat(ImageFormat.NV21);
params.setPreviewSize((int)frameSize.width, (int)frameSize.height);
List<String> FocusModes = params.getSupportedFocusModes();
if (FocusModes.contains(Camera.Parameters.FOCUS_MODE_CONTINUOUS_VIDEO))
{
params.setFocusMode(Camera.Parameters.FOCUS_MODE_CONTINUOUS_VIDEO);
}
mCamera.setParameters(params);
params = mCamera.getParameters();
mFrameWidth = params.getPreviewSize().width;
mFrameHeight = params.getPreviewSize().height;
int size = mFrameWidth * mFrameHeight;
size = size * ImageFormat.getBitsPerPixel(params.getPreviewFormat()) / 8;
mBuffer = new byte[size];
mCamera.addCallbackBuffer(mBuffer);
mCamera.setPreviewCallbackWithBuffer(this);
mBaseMat = new Mat(mFrameHeight + (mFrameHeight/2), mFrameWidth, CvType.CV_8UC1);
AllocateCache();
if (Build.VERSION.SDK_INT >= Build.VERSION_CODES.HONEYCOMB) {
SurfaceTexture tex = new SurfaceTexture(MAGIC_TEXTURE_ID);
getHolder().setType(SurfaceHolder.SURFACE_TYPE_PUSH_BUFFERS);
mCamera.setPreviewTexture(tex);
} else
mCamera.setPreviewDisplay(null);
} catch (IOException e) {
e.printStackTrace();
}
/* Finally we are ready to start the preview */
Log.d(TAG, "startPreview");
mCamera.startPreview();
}
return true;
}
protected void releaseCamera() {
synchronized (this) {
mCamera.stopPreview();
mCamera.release();
mCamera = null;
}
}
@Override
protected boolean connectCamera(int width, int height) {
/* 1. We need to instantiate camera
* 2. We need to start thread which will be getting frames
*/
/* First step - initialize camera connection */
Log.d(TAG, "Connecting to camera");
if (!initializeCamera(getWidth(), getHeight()))
return false;
/* now we can start update thread */
Log.d(TAG, "Starting processing thread");
mStopThread = false;
mThread = new Thread(new CameraWorker());
mThread.start();
return true;
}
protected void disconnectCamera() {
/* 1. We need to stop thread which updating the frames
* 2. Stop camera and release it
*/
Log.d(TAG, "Disconnecting from camera");
try {
mStopThread = true;
Log.d(TAG, "Notify thread");
synchronized (this) {
this.notify();
}
Log.d(TAG, "Wating for thread");
mThread.join();
} catch (InterruptedException e) {
e.printStackTrace();
} finally {
mThread = null;
}
/* Now release camera */
releaseCamera();
}
public void onPreviewFrame(byte[] frame, Camera arg1) {
Log.i(TAG, "Preview Frame received. Need to create MAT and deliver it to clients");
Log.i(TAG, "Frame size is " + frame.length);
synchronized (this)
{
mBaseMat.put(0, 0, frame);
this.notify();
}
if (mCamera != null)
mCamera.addCallbackBuffer(mBuffer);
}
private class CameraWorker implements Runnable {
public void run() {
do {
synchronized (JavaCameraView.this) {
try {
JavaCameraView.this.wait();
} catch (InterruptedException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
}
if (!mStopThread) {
Mat frameMat = new Mat();
switch (mPreviewFormat) {
case Highgui.CV_CAP_ANDROID_COLOR_FRAME_RGBA:
Imgproc.cvtColor(mBaseMat, frameMat, Imgproc.COLOR_YUV2RGBA_NV21, 4);
break;
case Highgui.CV_CAP_ANDROID_GREY_FRAME:
frameMat = mBaseMat.submat(0, mFrameHeight, 0, mFrameWidth);
break;
default:
Log.e(TAG, "Invalid frame format! Only RGBA and Gray Scale are supported!");
};
deliverAndDrawFrame(frameMat);
frameMat.release();
}
} while (!mStopThread);
Log.d(TAG, "Finish processing thread");
}
}
}

145
modules/java/generator/src/java/android+NativeCameraView.java Normal file
View File

@@ -0,0 +1,145 @@
package org.opencv.android;
import org.opencv.core.Mat;
import org.opencv.core.Size;
import org.opencv.highgui.Highgui;
import org.opencv.highgui.VideoCapture;
import android.content.Context;
import android.util.AttributeSet;
import android.util.Log;
/**
* This class is an implementation of a bridge between SurfaceView and native OpenCV camera.
* Due to the big amount of work done, by the base class this child is only responsible
* for creating camera, destroying camera and delivering frames while camera is enabled
*/
public class NativeCameraView extends CameraBridgeViewBase {
public static final String TAG = "NativeCameraView";
private boolean mStopThread;
private Thread mThread;
private VideoCapture mCamera;
public NativeCameraView(Context context, AttributeSet attrs) {
super(context, attrs);
}
@Override
protected boolean connectCamera(int width, int height) {
/* 1. We need to instantiate camera
* 2. We need to start thread which will be getting frames
*/
/* First step - initialize camera connection */
if (!initializeCamera(getWidth(), getHeight()))
return false;
/* now we can start update thread */
mThread = new Thread(new CameraWorker());
mThread.start();
return true;
}
@Override
protected void disconnectCamera() {
/* 1. We need to stop thread which updating the frames
* 2. Stop camera and release it
*/
try {
mStopThread = true;
mThread.join();
} catch (InterruptedException e) {
e.printStackTrace();
} finally {
mThread = null;
mStopThread = false;
}
/* Now release camera */
releaseCamera();
}
public static class OpenCvSizeAccessor implements ListItemAccessor {
public int getWidth(Object obj) {
Size size = (Size)obj;
return (int)size.width;
}
public int getHeight(Object obj) {
Size size = (Size)obj;
return (int)size.height;
}
}
private boolean initializeCamera(int width, int height) {
synchronized (this) {
mCamera = new VideoCapture(Highgui.CV_CAP_ANDROID);
if (mCamera == null)
return false;
//TODO: improve error handling
java.util.List<Size> sizes = mCamera.getSupportedPreviewSizes();
/* Select the size that fits surface considering maximum size allowed */
Size frameSize = calculateCameraFrameSize(sizes, new OpenCvSizeAccessor(), width, height);
mFrameWidth = (int)frameSize.width;
mFrameHeight = (int)frameSize.height;
AllocateCache();
mCamera.set(Highgui.CV_CAP_PROP_FRAME_WIDTH, frameSize.width);
mCamera.set(Highgui.CV_CAP_PROP_FRAME_HEIGHT, frameSize.height);
}
Log.i(TAG, "Selected camera frame size = (" + mFrameWidth + ", " + mFrameHeight + ")");
return true;
}
private void releaseCamera() {
synchronized (this) {
if (mCamera != null) {
mCamera.release();
}
}
}
private class CameraWorker implements Runnable {
private Mat mRgba = new Mat();
private Mat mGray = new Mat();
public void run() {
do {
if (!mCamera.grab()) {
Log.e(TAG, "Camera frame grab failed");
break;
}
switch (mPreviewFormat) {
case Highgui.CV_CAP_ANDROID_COLOR_FRAME_RGBA:
{
mCamera.retrieve(mRgba, Highgui.CV_CAP_ANDROID_COLOR_FRAME_RGBA);
deliverAndDrawFrame(mRgba);
} break;
case Highgui.CV_CAP_ANDROID_GREY_FRAME:
mCamera.retrieve(mGray, Highgui.CV_CAP_ANDROID_GREY_FRAME);
deliverAndDrawFrame(mGray);
break;
default:
Log.e(TAG, "Invalid frame format! Only RGBA and Gray Scale are supported!");
}
} while (!mStopThread);
}
}
}

5
modules/java/generator/src/java/android+OpenCVLoader.java
View File

@@ -12,6 +12,11 @@ public class OpenCVLoader
*/
public static final String OPENCV_VERSION_2_4_2 = "2.4.2";
/**
* OpenCV Library version 2.4.3.
*/
public static final String OPENCV_VERSION_2_4_3 = "2.4.3";
/**
* Loads and initializes OpenCV library from current application package. Roughly, it's an analog of system.loadLibrary("opencv_java").
* @return Returns true is initialization of OpenCV was successful.

176
modules/legacy/src/blobtrackingkalman.cpp
View File

@@ -1,176 +0,0 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// Intel License Agreement
//
// Copyright (C) 2000, Intel Corporation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of Intel Corporation may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "precomp.hpp"
/*======================= KALMAN FILTER AS TRACKER =========================*/
/* State vector is (x,y,w,h,dx,dy,dw,dh). */
/* Measurement is (x,y,w,h) */
/* Dynamic matrix A: */
const float A8[] = { 1, 0, 0, 0, 1, 0, 0, 0,
0, 1, 0, 0, 0, 1, 0, 0,
0, 0, 1, 0, 0, 0, 1, 0,
0, 0, 0, 1, 0, 0, 0, 1,
0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 1};
/* Measurement matrix H: */
const float H8[] = { 1, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0};
/* Matices for zero size velocity: */
/* Dynamic matrix A: */
const float A6[] = { 1, 0, 0, 0, 1, 0,
0, 1, 0, 0, 0, 1,
0, 0, 1, 0, 0, 0,
0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 1};
/* Measurement matrix H: */
const float H6[] = { 1, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0,
0, 0, 0, 1, 0, 0};
#define STATE_NUM 6
#define A A6
#define H H6
class CvBlobTrackerOneKalman:public CvBlobTrackerOne
{
private:
CvBlob m_Blob;
CvKalman* m_pKalman;
int m_Frame;
public:
CvBlobTrackerOneKalman()
{
m_Frame = 0;
m_pKalman = cvCreateKalman(STATE_NUM,4);
memcpy( m_pKalman->transition_matrix->data.fl, A, sizeof(A));
memcpy( m_pKalman->measurement_matrix->data.fl, H, sizeof(H));
cvSetIdentity( m_pKalman->process_noise_cov, cvRealScalar(1e-5) );
cvSetIdentity( m_pKalman->measurement_noise_cov, cvRealScalar(1e-1) );
// CV_MAT_ELEM(*m_pKalman->measurement_noise_cov, float, 2,2) *= (float)pow(20,2);
// CV_MAT_ELEM(*m_pKalman->measurement_noise_cov, float, 3,3) *= (float)pow(20,2);
cvSetIdentity( m_pKalman->error_cov_post, cvRealScalar(1));
cvZero(m_pKalman->state_post);
cvZero(m_pKalman->state_pre);
SetModuleName("Kalman");
}
~CvBlobTrackerOneKalman()
{
cvReleaseKalman(&m_pKalman);
}
virtual void Init(CvBlob* pBlob, IplImage* /*pImg*/, IplImage* /*pImgFG*/ = NULL)
{
m_Blob = pBlob[0];
m_pKalman->state_post->data.fl[0] = CV_BLOB_X(pBlob);
m_pKalman->state_post->data.fl[1] = CV_BLOB_Y(pBlob);
m_pKalman->state_post->data.fl[2] = CV_BLOB_WX(pBlob);
m_pKalman->state_post->data.fl[3] = CV_BLOB_WY(pBlob);
}
virtual CvBlob* Process(CvBlob* pBlob, IplImage* /*pImg*/, IplImage* /*pImgFG*/ = NULL)
{
CvBlob* pBlobRes = &m_Blob;
float Z[4];
CvMat Zmat = cvMat(4,1,CV_32F,Z);
m_Blob = pBlob[0];
if(m_Frame < 2)
{ /* First call: */
m_pKalman->state_post->data.fl[0+4] = CV_BLOB_X(pBlob)-m_pKalman->state_post->data.fl[0];
m_pKalman->state_post->data.fl[1+4] = CV_BLOB_Y(pBlob)-m_pKalman->state_post->data.fl[1];
if(m_pKalman->DP>6)
{
m_pKalman->state_post->data.fl[2+4] = CV_BLOB_WX(pBlob)-m_pKalman->state_post->data.fl[2];
m_pKalman->state_post->data.fl[3+4] = CV_BLOB_WY(pBlob)-m_pKalman->state_post->data.fl[3];
}
m_pKalman->state_post->data.fl[0] = CV_BLOB_X(pBlob);
m_pKalman->state_post->data.fl[1] = CV_BLOB_Y(pBlob);
m_pKalman->state_post->data.fl[2] = CV_BLOB_WX(pBlob);
m_pKalman->state_post->data.fl[3] = CV_BLOB_WY(pBlob);
memcpy(m_pKalman->state_pre->data.fl,m_pKalman->state_post->data.fl,sizeof(float)*STATE_NUM);
}
else
{ /* Another call: */
Z[0] = CV_BLOB_X(pBlob);
Z[1] = CV_BLOB_Y(pBlob);
Z[2] = CV_BLOB_WX(pBlob);
Z[3] = CV_BLOB_WY(pBlob);
cvKalmanCorrect(m_pKalman,&Zmat);
cvKalmanPredict(m_pKalman,0);
cvMatMulAdd(m_pKalman->measurement_matrix, m_pKalman->state_pre, NULL, &Zmat);
CV_BLOB_X(pBlobRes) = Z[0];
CV_BLOB_Y(pBlobRes) = Z[1];
CV_BLOB_WX(pBlobRes) = Z[2];
CV_BLOB_WY(pBlobRes) = Z[3];
}
m_Frame++;
return pBlobRes;
}
virtual void Release()
{
delete this;
}
}; /* class CvBlobTrackerOneKalman */
#if 0
static CvBlobTrackerOne* cvCreateModuleBlobTrackerOneKalman()
{
return (CvBlobTrackerOne*) new CvBlobTrackerOneKalman;
}
CvBlobTracker* cvCreateBlobTrackerKalman()
{
return cvCreateBlobTrackerList(cvCreateModuleBlobTrackerOneKalman);
}
#endif

140
modules/objdetect/src/haar.cpp
View File

@@ -54,6 +54,9 @@
#if CV_AVX
# define CV_HAAR_USE_AVX 1
# if defined _MSC_VER
# pragma warning( disable : 4752 )
# endif
#else
# if CV_SSE2 || CV_SSE3
# define CV_HAAR_USE_SSE 1
@@ -412,6 +415,9 @@ icvCreateHidHaarClassifierCascade( CvHaarClassifierCascade* cascade )
#define calc_sum(rect,offset) \
((rect).p0[offset] - (rect).p1[offset] - (rect).p2[offset] + (rect).p3[offset])
#define calc_sumf(rect,offset) \
static_cast<float>((rect).p0[offset] - (rect).p1[offset] - (rect).p2[offset] + (rect).p3[offset])
CV_IMPL void
cvSetImagesForHaarClassifierCascade( CvHaarClassifierCascade* _cascade,
@@ -652,7 +658,7 @@ double icvEvalHidHaarClassifierAVX( CvHidHaarClassifier* classifier,
nodes[6] = (classifier+6)->node + idxV[6];
nodes[7] = (classifier+7)->node + idxV[7];
__m256 t = _mm256_set1_ps(variance_norm_factor);
__m256 t = _mm256_set1_ps(static_cast<float>(variance_norm_factor));
t = _mm256_mul_ps(t, _mm256_set_ps(nodes[7]->threshold,
nodes[6]->threshold,
@@ -663,14 +669,14 @@ double icvEvalHidHaarClassifierAVX( CvHidHaarClassifier* classifier,
nodes[1]->threshold,
nodes[0]->threshold));
__m256 offset = _mm256_set_ps(calc_sum(nodes[7]->feature.rect[0], p_offset),
calc_sum(nodes[6]->feature.rect[0], p_offset),
calc_sum(nodes[5]->feature.rect[0], p_offset),
calc_sum(nodes[4]->feature.rect[0], p_offset),
calc_sum(nodes[3]->feature.rect[0], p_offset),
calc_sum(nodes[2]->feature.rect[0], p_offset),
calc_sum(nodes[1]->feature.rect[0], p_offset),
calc_sum(nodes[0]->feature.rect[0], p_offset));
__m256 offset = _mm256_set_ps(calc_sumf(nodes[7]->feature.rect[0], p_offset),
calc_sumf(nodes[6]->feature.rect[0], p_offset),
calc_sumf(nodes[5]->feature.rect[0], p_offset),
calc_sumf(nodes[4]->feature.rect[0], p_offset),
calc_sumf(nodes[3]->feature.rect[0], p_offset),
calc_sumf(nodes[2]->feature.rect[0], p_offset),
calc_sumf(nodes[1]->feature.rect[0], p_offset),
calc_sumf(nodes[0]->feature.rect[0], p_offset));
__m256 weight = _mm256_set_ps(nodes[7]->feature.rect[0].weight,
nodes[6]->feature.rect[0].weight,
@@ -683,14 +689,14 @@ double icvEvalHidHaarClassifierAVX( CvHidHaarClassifier* classifier,
__m256 sum = _mm256_mul_ps(offset, weight);
offset = _mm256_set_ps(calc_sum(nodes[7]->feature.rect[1], p_offset),
calc_sum(nodes[6]->feature.rect[1], p_offset),
calc_sum(nodes[5]->feature.rect[1], p_offset),
calc_sum(nodes[4]->feature.rect[1], p_offset),
calc_sum(nodes[3]->feature.rect[1], p_offset),
calc_sum(nodes[2]->feature.rect[1], p_offset),
calc_sum(nodes[1]->feature.rect[1], p_offset),
calc_sum(nodes[0]->feature.rect[1], p_offset));
offset = _mm256_set_ps(calc_sumf(nodes[7]->feature.rect[1], p_offset),
calc_sumf(nodes[6]->feature.rect[1], p_offset),
calc_sumf(nodes[5]->feature.rect[1], p_offset),
calc_sumf(nodes[4]->feature.rect[1], p_offset),
calc_sumf(nodes[3]->feature.rect[1], p_offset),
calc_sumf(nodes[2]->feature.rect[1], p_offset),
calc_sumf(nodes[1]->feature.rect[1], p_offset),
calc_sumf(nodes[0]->feature.rect[1], p_offset));
weight = _mm256_set_ps(nodes[7]->feature.rect[1].weight,
nodes[6]->feature.rect[1].weight,
@@ -704,21 +710,21 @@ double icvEvalHidHaarClassifierAVX( CvHidHaarClassifier* classifier,
sum = _mm256_add_ps(sum, _mm256_mul_ps(offset, weight));
if( nodes[0]->feature.rect[2].p0 )
tmp[0] = calc_sum(nodes[0]->feature.rect[2], p_offset) * nodes[0]->feature.rect[2].weight;
tmp[0] = calc_sumf(nodes[0]->feature.rect[2], p_offset) * nodes[0]->feature.rect[2].weight;
if( nodes[1]->feature.rect[2].p0 )
tmp[1] = calc_sum(nodes[1]->feature.rect[2], p_offset) * nodes[1]->feature.rect[2].weight;
tmp[1] = calc_sumf(nodes[1]->feature.rect[2], p_offset) * nodes[1]->feature.rect[2].weight;
if( nodes[2]->feature.rect[2].p0 )
tmp[2] = calc_sum(nodes[2]->feature.rect[2], p_offset) * nodes[2]->feature.rect[2].weight;
tmp[2] = calc_sumf(nodes[2]->feature.rect[2], p_offset) * nodes[2]->feature.rect[2].weight;
if( nodes[3]->feature.rect[2].p0 )
tmp[3] = calc_sum(nodes[3]->feature.rect[2], p_offset) * nodes[3]->feature.rect[2].weight;
tmp[3] = calc_sumf(nodes[3]->feature.rect[2], p_offset) * nodes[3]->feature.rect[2].weight;
if( nodes[4]->feature.rect[2].p0 )
tmp[4] = calc_sum(nodes[4]->feature.rect[2], p_offset) * nodes[4]->feature.rect[2].weight;
tmp[4] = calc_sumf(nodes[4]->feature.rect[2], p_offset) * nodes[4]->feature.rect[2].weight;
if( nodes[5]->feature.rect[2].p0 )
tmp[5] = calc_sum(nodes[5]->feature.rect[2], p_offset) * nodes[5]->feature.rect[2].weight;
tmp[5] = calc_sumf(nodes[5]->feature.rect[2], p_offset) * nodes[5]->feature.rect[2].weight;
if( nodes[6]->feature.rect[2].p0 )
tmp[6] = calc_sum(nodes[6]->feature.rect[2], p_offset) * nodes[6]->feature.rect[2].weight;
tmp[6] = calc_sumf(nodes[6]->feature.rect[2], p_offset) * nodes[6]->feature.rect[2].weight;
if( nodes[7]->feature.rect[2].p0 )
tmp[7] = calc_sum(nodes[7]->feature.rect[2], p_offset) * nodes[7]->feature.rect[2].weight;
tmp[7] = calc_sumf(nodes[7]->feature.rect[2], p_offset) * nodes[7]->feature.rect[2].weight;
sum = _mm256_add_ps(sum,_mm256_load_ps(tmp));
@@ -918,7 +924,7 @@ cvRunHaarClassifierCascadeSum( const CvHaarClassifierCascade* _cascade,
classifiers[7] = cascade->stage_classifier[i].classifier + j + 7;
nodes[7] = classifiers[7]->node;
__m256 t = _mm256_set1_ps(variance_norm_factor);
__m256 t = _mm256_set1_ps(static_cast<float>(variance_norm_factor));
t = _mm256_mul_ps(t, _mm256_set_ps(nodes[7]->threshold,
nodes[6]->threshold,
nodes[5]->threshold,
@@ -928,14 +934,14 @@ cvRunHaarClassifierCascadeSum( const CvHaarClassifierCascade* _cascade,
nodes[1]->threshold,
nodes[0]->threshold));
__m256 offset = _mm256_set_ps(calc_sum(nodes[7]->feature.rect[0], p_offset),
calc_sum(nodes[6]->feature.rect[0], p_offset),
calc_sum(nodes[5]->feature.rect[0], p_offset),
calc_sum(nodes[4]->feature.rect[0], p_offset),
calc_sum(nodes[3]->feature.rect[0], p_offset),
calc_sum(nodes[2]->feature.rect[0], p_offset),
calc_sum(nodes[1]->feature.rect[0], p_offset),
calc_sum(nodes[0]->feature.rect[0], p_offset));
__m256 offset = _mm256_set_ps(calc_sumf(nodes[7]->feature.rect[0], p_offset),
calc_sumf(nodes[6]->feature.rect[0], p_offset),
calc_sumf(nodes[5]->feature.rect[0], p_offset),
calc_sumf(nodes[4]->feature.rect[0], p_offset),
calc_sumf(nodes[3]->feature.rect[0], p_offset),
calc_sumf(nodes[2]->feature.rect[0], p_offset),
calc_sumf(nodes[1]->feature.rect[0], p_offset),
calc_sumf(nodes[0]->feature.rect[0], p_offset));
__m256 weight = _mm256_set_ps(nodes[7]->feature.rect[0].weight,
nodes[6]->feature.rect[0].weight,
@@ -948,14 +954,14 @@ cvRunHaarClassifierCascadeSum( const CvHaarClassifierCascade* _cascade,
__m256 sum = _mm256_mul_ps(offset, weight);
offset = _mm256_set_ps(calc_sum(nodes[7]->feature.rect[1], p_offset),
calc_sum(nodes[6]->feature.rect[1], p_offset),
calc_sum(nodes[5]->feature.rect[1], p_offset),
calc_sum(nodes[4]->feature.rect[1], p_offset),
calc_sum(nodes[3]->feature.rect[1], p_offset),
calc_sum(nodes[2]->feature.rect[1], p_offset),
calc_sum(nodes[1]->feature.rect[1], p_offset),
calc_sum(nodes[0]->feature.rect[1], p_offset));
offset = _mm256_set_ps(calc_sumf(nodes[7]->feature.rect[1], p_offset),
calc_sumf(nodes[6]->feature.rect[1], p_offset),
calc_sumf(nodes[5]->feature.rect[1], p_offset),
calc_sumf(nodes[4]->feature.rect[1], p_offset),
calc_sumf(nodes[3]->feature.rect[1], p_offset),
calc_sumf(nodes[2]->feature.rect[1], p_offset),
calc_sumf(nodes[1]->feature.rect[1], p_offset),
calc_sumf(nodes[0]->feature.rect[1], p_offset));
weight = _mm256_set_ps(nodes[7]->feature.rect[1].weight,
nodes[6]->feature.rect[1].weight,
@@ -1023,7 +1029,7 @@ cvRunHaarClassifierCascadeSum( const CvHaarClassifierCascade* _cascade,
classifiers[7] = cascade->stage_classifier[i].classifier + j + 7;
nodes[7] = classifiers[7]->node;
__m256 t = _mm256_set1_ps(variance_norm_factor);
__m256 t = _mm256_set1_ps(static_cast<float>(variance_norm_factor));
t = _mm256_mul_ps(t, _mm256_set_ps(nodes[7]->threshold,
nodes[6]->threshold,
@@ -1034,14 +1040,14 @@ cvRunHaarClassifierCascadeSum( const CvHaarClassifierCascade* _cascade,
nodes[1]->threshold,
nodes[0]->threshold));
__m256 offset = _mm256_set_ps(calc_sum(nodes[7]->feature.rect[0], p_offset),
calc_sum(nodes[6]->feature.rect[0], p_offset),
calc_sum(nodes[5]->feature.rect[0], p_offset),
calc_sum(nodes[4]->feature.rect[0], p_offset),
calc_sum(nodes[3]->feature.rect[0], p_offset),
calc_sum(nodes[2]->feature.rect[0], p_offset),
calc_sum(nodes[1]->feature.rect[0], p_offset),
calc_sum(nodes[0]->feature.rect[0], p_offset));
__m256 offset = _mm256_set_ps(calc_sumf(nodes[7]->feature.rect[0], p_offset),
calc_sumf(nodes[6]->feature.rect[0], p_offset),
calc_sumf(nodes[5]->feature.rect[0], p_offset),
calc_sumf(nodes[4]->feature.rect[0], p_offset),
calc_sumf(nodes[3]->feature.rect[0], p_offset),
calc_sumf(nodes[2]->feature.rect[0], p_offset),
calc_sumf(nodes[1]->feature.rect[0], p_offset),
calc_sumf(nodes[0]->feature.rect[0], p_offset));
__m256 weight = _mm256_set_ps(nodes[7]->feature.rect[0].weight,
nodes[6]->feature.rect[0].weight,
@@ -1054,14 +1060,14 @@ cvRunHaarClassifierCascadeSum( const CvHaarClassifierCascade* _cascade,
__m256 sum = _mm256_mul_ps(offset, weight);
offset = _mm256_set_ps(calc_sum(nodes[7]->feature.rect[1], p_offset),
calc_sum(nodes[6]->feature.rect[1], p_offset),
calc_sum(nodes[5]->feature.rect[1], p_offset),
calc_sum(nodes[4]->feature.rect[1], p_offset),
calc_sum(nodes[3]->feature.rect[1], p_offset),
calc_sum(nodes[2]->feature.rect[1], p_offset),
calc_sum(nodes[1]->feature.rect[1], p_offset),
calc_sum(nodes[0]->feature.rect[1], p_offset));
offset = _mm256_set_ps(calc_sumf(nodes[7]->feature.rect[1], p_offset),
calc_sumf(nodes[6]->feature.rect[1], p_offset),
calc_sumf(nodes[5]->feature.rect[1], p_offset),
calc_sumf(nodes[4]->feature.rect[1], p_offset),
calc_sumf(nodes[3]->feature.rect[1], p_offset),
calc_sumf(nodes[2]->feature.rect[1], p_offset),
calc_sumf(nodes[1]->feature.rect[1], p_offset),
calc_sumf(nodes[0]->feature.rect[1], p_offset));
weight = _mm256_set_ps(nodes[7]->feature.rect[1].weight,
nodes[6]->feature.rect[1].weight,
@@ -1075,21 +1081,21 @@ cvRunHaarClassifierCascadeSum( const CvHaarClassifierCascade* _cascade,
sum = _mm256_add_ps(sum, _mm256_mul_ps(offset, weight));
if( nodes[0]->feature.rect[2].p0 )
tmp[0] = calc_sum(nodes[0]->feature.rect[2],p_offset) * nodes[0]->feature.rect[2].weight;
tmp[0] = calc_sumf(nodes[0]->feature.rect[2],p_offset) * nodes[0]->feature.rect[2].weight;
if( nodes[1]->feature.rect[2].p0 )
tmp[1] = calc_sum(nodes[1]->feature.rect[2],p_offset) * nodes[1]->feature.rect[2].weight;
tmp[1] = calc_sumf(nodes[1]->feature.rect[2],p_offset) * nodes[1]->feature.rect[2].weight;
if( nodes[2]->feature.rect[2].p0 )
tmp[2] = calc_sum(nodes[2]->feature.rect[2],p_offset) * nodes[2]->feature.rect[2].weight;
tmp[2] = calc_sumf(nodes[2]->feature.rect[2],p_offset) * nodes[2]->feature.rect[2].weight;
if( nodes[3]->feature.rect[2].p0 )
tmp[3] = calc_sum(nodes[3]->feature.rect[2],p_offset) * nodes[3]->feature.rect[2].weight;
tmp[3] = calc_sumf(nodes[3]->feature.rect[2],p_offset) * nodes[3]->feature.rect[2].weight;
if( nodes[4]->feature.rect[2].p0 )
tmp[4] = calc_sum(nodes[4]->feature.rect[2],p_offset) * nodes[4]->feature.rect[2].weight;
tmp[4] = calc_sumf(nodes[4]->feature.rect[2],p_offset) * nodes[4]->feature.rect[2].weight;
if( nodes[5]->feature.rect[2].p0 )
tmp[5] = calc_sum(nodes[5]->feature.rect[2],p_offset) * nodes[5]->feature.rect[2].weight;
tmp[5] = calc_sumf(nodes[5]->feature.rect[2],p_offset) * nodes[5]->feature.rect[2].weight;
if( nodes[6]->feature.rect[2].p0 )
tmp[6] = calc_sum(nodes[6]->feature.rect[2],p_offset) * nodes[6]->feature.rect[2].weight;
tmp[6] = calc_sumf(nodes[6]->feature.rect[2],p_offset) * nodes[6]->feature.rect[2].weight;
if( nodes[7]->feature.rect[2].p0 )
tmp[7] = calc_sum(nodes[7]->feature.rect[2],p_offset) * nodes[7]->feature.rect[2].weight;
tmp[7] = calc_sumf(nodes[7]->feature.rect[2],p_offset) * nodes[7]->feature.rect[2].weight;
sum = _mm256_add_ps(sum, _mm256_load_ps(tmp));

5
modules/python/test/test.py
View File

@@ -390,10 +390,7 @@ class FunctionTests(OpenCVTests):
def test_DrawChessboardCorners(self):
im = cv.CreateImage((512,512), cv.IPL_DEPTH_8U, 3)
cv.SetZero(im)
cv.DrawChessboardCorners(im, (5, 5), [ (100,100) for i in range(5 * 5) ], 1)
self.assert_(cv.Sum(im)[0] > 0)
self.assertRaises(TypeError, lambda: cv.DrawChessboardCorners(im, (4, 5), [ (100,100) for i in range(5 * 5) ], 1))
cv.DrawChessboardCorners(im, (5, 5), [ ((i/5)*100+50,(i%5)*100+50) for i in range(5 * 5) ], 1)
def test_ExtractSURF(self):
img = self.get_sample("samples/c/lena.jpg", 0)

6
modules/stitching/src/seam_finders.cpp
View File

@@ -628,7 +628,7 @@ bool DpSeamFinder::getSeamTips(int comp1, int comp2, Point &p1, Point &p2)
{
for (int j = i+1; j < nlabels; ++j)
{
double size1 = points[i].size(), size2 = points[j].size();
double size1 = static_cast<double>(points[i].size()), size2 = static_cast<double>(points[j].size());
double cx1 = cvRound(sum[i].x / size1), cy1 = cvRound(sum[i].y / size1);
double cx2 = cvRound(sum[j].x / size2), cy2 = cvRound(sum[j].y / size1);
@@ -648,7 +648,7 @@ bool DpSeamFinder::getSeamTips(int comp1, int comp2, Point &p1, Point &p2)
for (int i = 0; i < 2; ++i)
{
double size = points[idx[i]].size();
double size = static_cast<double>(points[idx[i]].size());
double cx = cvRound(sum[idx[i]].x / size);
double cy = cvRound(sum[idx[i]].y / size);
@@ -1036,7 +1036,7 @@ void DpSeamFinder::updateLabelsUsingSeam(
for (map<int, int>::iterator itr = connect2.begin(); itr != connect2.end(); ++itr)
{
double len = contours_[comp1].size();
double len = static_cast<double>(contours_[comp1].size());
isAdjComp[itr->first] = itr->second / len > 0.05 && connectOther.find(itr->first)->second / len < 0.1;
}

2
modules/ts/src/ts_gtest.cpp
View File

@@ -6352,7 +6352,9 @@ namespace internal {
// Valid only for fast death tests. Indicates the code is running in the
// child process of a fast style death test.
# if !GTEST_OS_WINDOWS
static bool g_in_fast_death_test_child = false;
# endif
// Returns a Boolean value indicating whether the caller is currently
// executing in the context of the death test child process. Tools such as