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lessthanoptimal/BoofCV
main/boofcv-feature/src/main/java/boofcv/alg/shapes/ellipse/SnapToEllipseEdge.java
SnapToEllipseEdge.change
protected static double change( EllipseRotated_F64 a , EllipseRotated_F64 b ) { double total = 0; total += Math.abs(a.center.x - b.center.x); total += Math.abs(a.center.y - b.center.y); total += Math.abs(a.a - b.a); total += Math.abs(a.b - b.b); // only care about the change of angle when it is not a circ...
java
protected static double change( EllipseRotated_F64 a , EllipseRotated_F64 b ) { double total = 0; total += Math.abs(a.center.x - b.center.x); total += Math.abs(a.center.y - b.center.y); total += Math.abs(a.a - b.a); total += Math.abs(a.b - b.b); // only care about the change of angle when it is not a circ...
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Computes a numerical value for the difference in parameters between the two ellipses
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-feature/src/main/java/boofcv/alg/shapes/ellipse/SnapToEllipseEdge.java#L116-L129
train
lessthanoptimal/BoofCV
main/boofcv-sfm/src/main/java/boofcv/factory/sfm/FactoryVisualOdometry.java
FactoryVisualOdometry.monoPlaneInfinity
public static <T extends ImageGray<T>> MonocularPlaneVisualOdometry<T> monoPlaneInfinity(int thresholdAdd, int thresholdRetire, double inlierPixelTol, int ransacIterations, PointTracker<T> tracker, ImageType<T> imageType) { //squared pixel...
java
public static <T extends ImageGray<T>> MonocularPlaneVisualOdometry<T> monoPlaneInfinity(int thresholdAdd, int thresholdRetire, double inlierPixelTol, int ransacIterations, PointTracker<T> tracker, ImageType<T> imageType) { //squared pixel...
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Monocular plane based visual odometry algorithm which uses both points on the plane and off plane for motion estimation. @see VisOdomMonoPlaneInfinity @param thresholdAdd New points are spawned when the number of on plane inliers drops below this value. @param thresholdRetire Tracks are dropped when they are not con...
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-sfm/src/main/java/boofcv/factory/sfm/FactoryVisualOdometry.java#L94-L118
train
lessthanoptimal/BoofCV
main/boofcv-sfm/src/main/java/boofcv/factory/sfm/FactoryVisualOdometry.java
FactoryVisualOdometry.monoPlaneOverhead
public static <T extends ImageGray<T>> MonocularPlaneVisualOdometry<T> monoPlaneOverhead(double cellSize, double maxCellsPerPixel, double mapHeightFraction , double inlierGroundTol, int ransacIterations , int thresholdRetire , ...
java
public static <T extends ImageGray<T>> MonocularPlaneVisualOdometry<T> monoPlaneOverhead(double cellSize, double maxCellsPerPixel, double mapHeightFraction , double inlierGroundTol, int ransacIterations , int thresholdRetire , ...
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Monocular plane based visual odometry algorithm which creates a synthetic overhead view and tracks image features inside this synthetic view. @see VisOdomMonoOverheadMotion2D @param cellSize (Overhead) size of ground cells in overhead image in world units @param maxCellsPerPixel (Overhead) Specifies the minimum resol...
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-sfm/src/main/java/boofcv/factory/sfm/FactoryVisualOdometry.java#L145-L170
train
lessthanoptimal/BoofCV
main/boofcv-sfm/src/main/java/boofcv/factory/sfm/FactoryVisualOdometry.java
FactoryVisualOdometry.stereoDepth
public static <T extends ImageGray<T>> StereoVisualOdometry<T> stereoDepth(double inlierPixelTol, int thresholdAdd, int thresholdRetire , int ransacIterations , int refineIterations , boolean doublePass , StereoDisparitySparse<T> sparseDisparity, Po...
java
public static <T extends ImageGray<T>> StereoVisualOdometry<T> stereoDepth(double inlierPixelTol, int thresholdAdd, int thresholdRetire , int ransacIterations , int refineIterations , boolean doublePass , StereoDisparitySparse<T> sparseDisparity, Po...
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Stereo vision based visual odometry algorithm which runs a sparse feature tracker in the left camera and estimates the range of tracks once when first detected using disparity between left and right cameras. @see VisOdomPixelDepthPnP @param thresholdAdd Add new tracks when less than this number are in the inlier set....
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-sfm/src/main/java/boofcv/factory/sfm/FactoryVisualOdometry.java#L185-L222
train
lessthanoptimal/BoofCV
main/boofcv-sfm/src/main/java/boofcv/factory/sfm/FactoryVisualOdometry.java
FactoryVisualOdometry.depthDepthPnP
public static <Vis extends ImageGray<Vis>, Depth extends ImageGray<Depth>> DepthVisualOdometry<Vis,Depth> depthDepthPnP(double inlierPixelTol, int thresholdAdd, int thresholdRetire , int ransacIterations , int refineIterations , boolean doublePass , ...
java
public static <Vis extends ImageGray<Vis>, Depth extends ImageGray<Depth>> DepthVisualOdometry<Vis,Depth> depthDepthPnP(double inlierPixelTol, int thresholdAdd, int thresholdRetire , int ransacIterations , int refineIterations , boolean doublePass , ...
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Depth sensor based visual odometry algorithm which runs a sparse feature tracker in the visual camera and estimates the range of tracks once when first detected using the depth sensor. @see VisOdomPixelDepthPnP @param thresholdAdd Add new tracks when less than this number are in the inlier set. Tracker dependent. Se...
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-sfm/src/main/java/boofcv/factory/sfm/FactoryVisualOdometry.java#L238-L275
train
lessthanoptimal/BoofCV
main/boofcv-sfm/src/main/java/boofcv/factory/sfm/FactoryVisualOdometry.java
FactoryVisualOdometry.stereoDualTrackerPnP
public static <T extends ImageGray<T>, Desc extends TupleDesc> StereoVisualOdometry<T> stereoDualTrackerPnP(int thresholdAdd, int thresholdRetire, double inlierPixelTol, double epipolarPixelTol, int ransacIterations, int refineIterations, PointTracker<T>...
java
public static <T extends ImageGray<T>, Desc extends TupleDesc> StereoVisualOdometry<T> stereoDualTrackerPnP(int thresholdAdd, int thresholdRetire, double inlierPixelTol, double epipolarPixelTol, int ransacIterations, int refineIterations, PointTracker<T>...
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Creates a stereo visual odometry algorithm that independently tracks features in left and right camera. @see VisOdomDualTrackPnP @param thresholdAdd When the number of inliers is below this number new features are detected @param thresholdRetire When a feature has not been in the inlier list for this many ticks it is...
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-sfm/src/main/java/boofcv/factory/sfm/FactoryVisualOdometry.java#L293-L340
train
lessthanoptimal/BoofCV
main/boofcv-geo/src/main/java/boofcv/alg/geo/pose/UtilLepetitEPnP.java
UtilLepetitEPnP.computeCameraControl
public static void computeCameraControl(double beta[], List<Point3D_F64> nullPts[], FastQueue<Point3D_F64> cameraPts , int numControl ) { cameraPts.reset(); for( int i = 0; i < numControl; i++ ) { cameraPts.grow().set(0,0,0); } for( int i = 0; i < numControl; i++ ) { dou...
java
public static void computeCameraControl(double beta[], List<Point3D_F64> nullPts[], FastQueue<Point3D_F64> cameraPts , int numControl ) { cameraPts.reset(); for( int i = 0; i < numControl; i++ ) { cameraPts.grow().set(0,0,0); } for( int i = 0; i < numControl; i++ ) { dou...
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Computes the camera control points as weighted sum of null points. @param beta Beta values which describe the weights of null points @param nullPts Null points that the camera point is a weighted sum of @param cameraPts The output
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-geo/src/main/java/boofcv/alg/geo/pose/UtilLepetitEPnP.java#L41-L63
train
lessthanoptimal/BoofCV
main/boofcv-geo/src/main/java/boofcv/alg/geo/pose/UtilLepetitEPnP.java
UtilLepetitEPnP.constraintMatrix6x3
public static void constraintMatrix6x3( DMatrixRMaj L_6x10 , DMatrixRMaj L_6x3 ) { int index = 0; for( int i = 0; i < 6; i++ ) { L_6x3.data[index++] = L_6x10.get(i,0); L_6x3.data[index++] = L_6x10.get(i,1); L_6x3.data[index++] = L_6x10.get(i,4); } }
java
public static void constraintMatrix6x3( DMatrixRMaj L_6x10 , DMatrixRMaj L_6x3 ) { int index = 0; for( int i = 0; i < 6; i++ ) { L_6x3.data[index++] = L_6x10.get(i,0); L_6x3.data[index++] = L_6x10.get(i,1); L_6x3.data[index++] = L_6x10.get(i,4); } }
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Extracts the linear constraint matrix for case 2 from the full 6x10 constraint matrix.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-geo/src/main/java/boofcv/alg/geo/pose/UtilLepetitEPnP.java#L82-L90
train
lessthanoptimal/BoofCV
main/boofcv-geo/src/main/java/boofcv/alg/geo/pose/UtilLepetitEPnP.java
UtilLepetitEPnP.constraintMatrix6x6
public static void constraintMatrix6x6( DMatrixRMaj L_6x10 , DMatrixRMaj L_6x6 ) { int index = 0; for( int i = 0; i < 6; i++ ) { L_6x6.data[index++] = L_6x10.get(i,0); L_6x6.data[index++] = L_6x10.get(i,1); L_6x6.data[index++] = L_6x10.get(i,2); L_6x6.data[index++] = L_6x10.get(i,4); L_6x6.data[inde...
java
public static void constraintMatrix6x6( DMatrixRMaj L_6x10 , DMatrixRMaj L_6x6 ) { int index = 0; for( int i = 0; i < 6; i++ ) { L_6x6.data[index++] = L_6x10.get(i,0); L_6x6.data[index++] = L_6x10.get(i,1); L_6x6.data[index++] = L_6x10.get(i,2); L_6x6.data[index++] = L_6x10.get(i,4); L_6x6.data[inde...
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Extracts the linear constraint matrix for case 3 from the full 6x10 constraint matrix.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-geo/src/main/java/boofcv/alg/geo/pose/UtilLepetitEPnP.java#L95-L106
train
lessthanoptimal/BoofCV
main/boofcv-geo/src/main/java/boofcv/alg/geo/pose/UtilLepetitEPnP.java
UtilLepetitEPnP.constraintMatrix3x3
public static void constraintMatrix3x3( DMatrixRMaj L_3x6 , DMatrixRMaj L_6x3 ) { int index = 0; for( int i = 0; i < 3; i++ ) { L_6x3.data[index++] = L_3x6.get(i,0); L_6x3.data[index++] = L_3x6.get(i,1); L_6x3.data[index++] = L_3x6.get(i,3); } }
java
public static void constraintMatrix3x3( DMatrixRMaj L_3x6 , DMatrixRMaj L_6x3 ) { int index = 0; for( int i = 0; i < 3; i++ ) { L_6x3.data[index++] = L_3x6.get(i,0); L_6x3.data[index++] = L_3x6.get(i,1); L_6x3.data[index++] = L_3x6.get(i,3); } }
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Extracts the linear constraint matrix for planar case 2 from the full 4x6 constraint matrix.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-geo/src/main/java/boofcv/alg/geo/pose/UtilLepetitEPnP.java#L194-L203
train
lessthanoptimal/BoofCV
main/boofcv-geo/src/main/java/boofcv/alg/geo/pose/UtilLepetitEPnP.java
UtilLepetitEPnP.constraintMatrix3x6
public static void constraintMatrix3x6( DMatrixRMaj L , DMatrixRMaj y , FastQueue<Point3D_F64> controlWorldPts , List<Point3D_F64> nullPts[] ) { int row = 0; for( int i = 0; i < 3; i++ ) { Point3D_F64 ci = controlWorldPts.get(i); Point3D_F64 vai = nullPts[0].get(i); Point3D_F64 vbi = ...
java
public static void constraintMatrix3x6( DMatrixRMaj L , DMatrixRMaj y , FastQueue<Point3D_F64> controlWorldPts , List<Point3D_F64> nullPts[] ) { int row = 0; for( int i = 0; i < 3; i++ ) { Point3D_F64 ci = controlWorldPts.get(i); Point3D_F64 vai = nullPts[0].get(i); Point3D_F64 vbi = ...
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Linear constraint matrix for case 4 in the planar case @param L Constraint matrix @param y Vector containing distance between world control points @param controlWorldPts List of world control points @param nullPts Null points
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-geo/src/main/java/boofcv/alg/geo/pose/UtilLepetitEPnP.java#L213-L259
train
lessthanoptimal/BoofCV
main/boofcv-geo/src/main/java/boofcv/alg/geo/pose/UtilLepetitEPnP.java
UtilLepetitEPnP.jacobian_Control4
public static void jacobian_Control4( DMatrixRMaj L_full , double beta[] , DMatrixRMaj A ) { int indexA = 0; double b0 = beta[0]; double b1 = beta[1]; double b2 = beta[2]; double b3 = beta[3]; final double ld[] = L_full.data; for( int i = 0; i < 6; i++ ) { int li = L_full.numCols*i; A.data...
java
public static void jacobian_Control4( DMatrixRMaj L_full , double beta[] , DMatrixRMaj A ) { int indexA = 0; double b0 = beta[0]; double b1 = beta[1]; double b2 = beta[2]; double b3 = beta[3]; final double ld[] = L_full.data; for( int i = 0; i < 6; i++ ) { int li = L_full.numCols*i; A.data...
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Computes the Jacobian given 4 control points.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-geo/src/main/java/boofcv/alg/geo/pose/UtilLepetitEPnP.java#L316-L332
train
lessthanoptimal/BoofCV
main/boofcv-geo/src/main/java/boofcv/alg/geo/pose/UtilLepetitEPnP.java
UtilLepetitEPnP.jacobian_Control3
public static void jacobian_Control3( DMatrixRMaj L_full , double beta[] , DMatrixRMaj A) { int indexA = 0; double b0 = beta[0]; double b1 = beta[1]; double b2 = beta[2]; final double ld[] = L_full.data; for( int i = 0; i < 3; i++ ) { int li = L_full.numCols*i; A.data[indexA++] = 2*ld[li+...
java
public static void jacobian_Control3( DMatrixRMaj L_full , double beta[] , DMatrixRMaj A) { int indexA = 0; double b0 = beta[0]; double b1 = beta[1]; double b2 = beta[2]; final double ld[] = L_full.data; for( int i = 0; i < 3; i++ ) { int li = L_full.numCols*i; A.data[indexA++] = 2*ld[li+...
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Computes the Jacobian given 3 control points.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-geo/src/main/java/boofcv/alg/geo/pose/UtilLepetitEPnP.java#L337-L352
train
lessthanoptimal/BoofCV
main/boofcv-feature/src/main/java/boofcv/alg/flow/DenseOpticalFlowBlockPyramid.java
DenseOpticalFlowBlockPyramid.process
public void process( ImagePyramid<T> pyramidPrev , ImagePyramid<T> pyramidCurr ) { InputSanityCheck.checkSameShape(pyramidPrev, pyramidCurr); int numLayers = pyramidPrev.getNumLayers(); for( int i = numLayers-1; i >= 0; i-- ) { T prev = pyramidPrev.getLayer(i); T curr = pyramidCurr.getLayer(i); flow...
java
public void process( ImagePyramid<T> pyramidPrev , ImagePyramid<T> pyramidCurr ) { InputSanityCheck.checkSameShape(pyramidPrev, pyramidCurr); int numLayers = pyramidPrev.getNumLayers(); for( int i = numLayers-1; i >= 0; i-- ) { T prev = pyramidPrev.getLayer(i); T curr = pyramidCurr.getLayer(i); flow...
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Computes the optical flow form 'prev' to 'curr' and stores the output into output @param pyramidPrev Previous image @param pyramidCurr Current image
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-feature/src/main/java/boofcv/alg/flow/DenseOpticalFlowBlockPyramid.java#L103-L179
train
lessthanoptimal/BoofCV
main/boofcv-geo/src/main/java/boofcv/alg/distort/spherical/EquirectangularDistortBase_F64.java
EquirectangularDistortBase_F64.setDirection
public void setDirection(double yaw, double pitch, double roll ) { ConvertRotation3D_F64.eulerToMatrix(EulerType.YZX,pitch,yaw,roll,R); }
java
public void setDirection(double yaw, double pitch, double roll ) { ConvertRotation3D_F64.eulerToMatrix(EulerType.YZX,pitch,yaw,roll,R); }
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Specifies the rotation offset from the canonical location using yaw and pitch. @param yaw Radian from -pi to pi @param pitch Radian from -pi/2 to pi/2 @param roll Radian from -pi to pi
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-geo/src/main/java/boofcv/alg/distort/spherical/EquirectangularDistortBase_F64.java#L69-L71
train
lessthanoptimal/BoofCV
main/boofcv-geo/src/main/java/boofcv/alg/distort/spherical/EquirectangularDistortBase_F64.java
EquirectangularDistortBase_F64.declareVectors
protected void declareVectors( int width , int height ) { this.outWidth = width; if( vectors.length < width*height ) { Point3D_F64[] tmp = new Point3D_F64[width*height]; System.arraycopy(vectors,0,tmp,0,vectors.length); for (int i = vectors.length; i < tmp.length; i++) { tmp[i] = new Point3D_F64(); ...
java
protected void declareVectors( int width , int height ) { this.outWidth = width; if( vectors.length < width*height ) { Point3D_F64[] tmp = new Point3D_F64[width*height]; System.arraycopy(vectors,0,tmp,0,vectors.length); for (int i = vectors.length; i < tmp.length; i++) { tmp[i] = new Point3D_F64(); ...
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Declares storage for precomputed pointing vectors to output image @param width output image width @param height output image height
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-geo/src/main/java/boofcv/alg/distort/spherical/EquirectangularDistortBase_F64.java#L87-L99
train
lessthanoptimal/BoofCV
main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/qrcode/GaliosFieldTableOps.java
GaliosFieldTableOps.polyScale
public void polyScale(GrowQueue_I8 input , int scale , GrowQueue_I8 output) { output.resize(input.size); for (int i = 0; i < input.size; i++) { output.data[i] = (byte)multiply(input.data[i]&0xFF, scale); } }
java
public void polyScale(GrowQueue_I8 input , int scale , GrowQueue_I8 output) { output.resize(input.size); for (int i = 0; i < input.size; i++) { output.data[i] = (byte)multiply(input.data[i]&0xFF, scale); } }
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Scales the polynomial. <p>Coefficients for largest powers are first, e.g. 2*x**3 + 8*x**2+1 = [2,8,0,1]</p> @param input Input polynomial. @param scale scale @param output Output polynomial.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/qrcode/GaliosFieldTableOps.java#L129-L136
train
lessthanoptimal/BoofCV
main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/qrcode/GaliosFieldTableOps.java
GaliosFieldTableOps.polyAdd
public void polyAdd(GrowQueue_I8 polyA , GrowQueue_I8 polyB , GrowQueue_I8 output ) { output.resize(Math.max(polyA.size,polyB.size)); // compute offset that would align the smaller polynomial with the larger polynomial int offsetA = Math.max(0,polyB.size-polyA.size); int offsetB = Math.max(0,polyA.size-polyB.s...
java
public void polyAdd(GrowQueue_I8 polyA , GrowQueue_I8 polyB , GrowQueue_I8 output ) { output.resize(Math.max(polyA.size,polyB.size)); // compute offset that would align the smaller polynomial with the larger polynomial int offsetA = Math.max(0,polyB.size-polyA.size); int offsetB = Math.max(0,polyA.size-polyB.s...
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Adds two polynomials together. output = polyA + polyB <p>Coefficients for largest powers are first, e.g. 2*x**3 + 8*x**2+1 = [2,8,0,1]</p> @param polyA (Input) First polynomial @param polyB (Input) Second polynomial @param output (Output) Results of addition
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/qrcode/GaliosFieldTableOps.java#L147-L164
train
lessthanoptimal/BoofCV
main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/qrcode/GaliosFieldTableOps.java
GaliosFieldTableOps.polyAdd_S
public void polyAdd_S(GrowQueue_I8 polyA , GrowQueue_I8 polyB , GrowQueue_I8 output ) { output.resize(Math.max(polyA.size,polyB.size)); int M = Math.min(polyA.size, polyB.size); for (int i = M; i < polyA.size; i++) { output.data[i] = polyA.data[i]; } for (int i = M; i < polyB.size; i++) { output.data[i...
java
public void polyAdd_S(GrowQueue_I8 polyA , GrowQueue_I8 polyB , GrowQueue_I8 output ) { output.resize(Math.max(polyA.size,polyB.size)); int M = Math.min(polyA.size, polyB.size); for (int i = M; i < polyA.size; i++) { output.data[i] = polyA.data[i]; } for (int i = M; i < polyB.size; i++) { output.data[i...
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Adds two polynomials together. <p>Coefficients for smallest powers are first, e.g. 2*x**3 + 8*x**2+1 = [1,0,2,8]</p> @param polyA (Input) First polynomial @param polyB (Input) Second polynomial @param output (Output) Results of addition
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/qrcode/GaliosFieldTableOps.java#L175-L189
train
lessthanoptimal/BoofCV
main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/qrcode/GaliosFieldTableOps.java
GaliosFieldTableOps.polyAddScaleB
public void polyAddScaleB(GrowQueue_I8 polyA , GrowQueue_I8 polyB , int scaleB , GrowQueue_I8 output ) { output.resize(Math.max(polyA.size,polyB.size)); // compute offset that would align the smaller polynomial with the larger polynomial int offsetA = Math.max(0,polyB.size-polyA.size); int offsetB = Math.max(0...
java
public void polyAddScaleB(GrowQueue_I8 polyA , GrowQueue_I8 polyB , int scaleB , GrowQueue_I8 output ) { output.resize(Math.max(polyA.size,polyB.size)); // compute offset that would align the smaller polynomial with the larger polynomial int offsetA = Math.max(0,polyB.size-polyA.size); int offsetB = Math.max(0...
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Adds two polynomials together while scaling the second. <p>Coefficients for largest powers are first, e.g. 2*x**3 + 8*x**2+1 = [2,8,0,1]</p> @param polyA (Input) First polynomial @param polyB (Input) Second polynomial @param scaleB (Input) Scale factor applied to polyB @param output (Output) Results of addition
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/qrcode/GaliosFieldTableOps.java#L201-L218
train
lessthanoptimal/BoofCV
main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/qrcode/GaliosFieldTableOps.java
GaliosFieldTableOps.polyEval
public int polyEval(GrowQueue_I8 input , int x ) { int y = input.data[0]&0xFF; for (int i = 1; i < input.size; i++) { y = multiply(y,x) ^ (input.data[i]&0xFF); } return y; }
java
public int polyEval(GrowQueue_I8 input , int x ) { int y = input.data[0]&0xFF; for (int i = 1; i < input.size; i++) { y = multiply(y,x) ^ (input.data[i]&0xFF); } return y; }
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Evaluate the polynomial using Horner's method. Avoids explicit calculating the powers of x. <p>01x**4 + 0fx**3 + 36x**2 + 78x + 40 = (((01 x + 0f) x + 36) x + 78) x + 40</p> <p>Coefficients for largest powers are first, e.g. 2*x**3 + 8*x**2+1 = [2,8,0,1]</p> @param input Polynomial being evaluated @param x Value of...
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/qrcode/GaliosFieldTableOps.java#L295-L303
train
lessthanoptimal/BoofCV
main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/qrcode/GaliosFieldTableOps.java
GaliosFieldTableOps.polyEvalContinue
public int polyEvalContinue( int previousOutput, GrowQueue_I8 part , int x ) { int y = previousOutput; for (int i = 0; i < part.size; i++) { y = multiply(y,x) ^ (part.data[i]&0xFF); } return y; }
java
public int polyEvalContinue( int previousOutput, GrowQueue_I8 part , int x ) { int y = previousOutput; for (int i = 0; i < part.size; i++) { y = multiply(y,x) ^ (part.data[i]&0xFF); } return y; }
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Continue evaluating a polynomial which has been broken up into multiple arrays. @param previousOutput Output from the evaluation of the prior part of the polynomial @param part Additional segment of the polynomial @param x Point it's being evaluated at @return results
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/qrcode/GaliosFieldTableOps.java#L335-L342
train
lessthanoptimal/BoofCV
main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/qrcode/GaliosFieldTableOps.java
GaliosFieldTableOps.polyDivide
public void polyDivide(GrowQueue_I8 dividend , GrowQueue_I8 divisor , GrowQueue_I8 quotient, GrowQueue_I8 remainder ) { // handle special case if( divisor.size > dividend.size ) { remainder.setTo(dividend); quotient.resize(0); return; } else { remainder.resize(divisor.size-1); quotient.se...
java
public void polyDivide(GrowQueue_I8 dividend , GrowQueue_I8 divisor , GrowQueue_I8 quotient, GrowQueue_I8 remainder ) { // handle special case if( divisor.size > dividend.size ) { remainder.setTo(dividend); quotient.resize(0); return; } else { remainder.resize(divisor.size-1); quotient.se...
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Performs polynomial division using a synthetic division algorithm. <p>Coefficients for largest powers are first, e.g. 2*x**3 + 8*x**2+1 = [2,8,0,1]</p> @param dividend (Input) Polynomial dividend @param divisor (Input) Polynomial divisor @param quotient (Output) Division's quotient @param remainder (Output) Divisions...
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/qrcode/GaliosFieldTableOps.java#L354-L388
train
lessthanoptimal/BoofCV
main/boofcv-recognition/src/main/java/boofcv/factory/fiducial/ConfigQrCode.java
ConfigQrCode.fast
public static ConfigQrCode fast() { // A global threshold is faster than any local algorithm // plus it will generate a simpler set of internal contours speeding up that process ConfigQrCode config = new ConfigQrCode(); config.threshold = ConfigThreshold.global(ThresholdType.GLOBAL_OTSU); return config; }
java
public static ConfigQrCode fast() { // A global threshold is faster than any local algorithm // plus it will generate a simpler set of internal contours speeding up that process ConfigQrCode config = new ConfigQrCode(); config.threshold = ConfigThreshold.global(ThresholdType.GLOBAL_OTSU); return config; }
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Default configuration for a QR Code detector which is optimized for speed
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/factory/fiducial/ConfigQrCode.java#L96-L102
train
lessthanoptimal/BoofCV
integration/boofcv-swing/src/main/java/boofcv/gui/feature/AssociationScorePanel.java
AssociationScorePanel.drawDistribution
private void drawDistribution( Graphics2D g2 , List<Point2D_F64> candidates , int offX, int offY , double scale) { findStatistics(); // draw all the features, adjusting their size based on the first score g2.setColor(Color.RED); g2.setStroke(new BasicStroke(3)); double normalizer; if( scorer.getSco...
java
private void drawDistribution( Graphics2D g2 , List<Point2D_F64> candidates , int offX, int offY , double scale) { findStatistics(); // draw all the features, adjusting their size based on the first score g2.setColor(Color.RED); g2.setStroke(new BasicStroke(3)); double normalizer; if( scorer.getSco...
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Visualizes score distribution. Larger circles mean its closer to the best fit score.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/integration/boofcv-swing/src/main/java/boofcv/gui/feature/AssociationScorePanel.java#L138-L178
train
lessthanoptimal/BoofCV
main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterFinder.java
ChessboardCornerClusterFinder.process
public void process(List<ChessboardCorner> corners ) { this.corners = corners; // reset internal data structures vertexes.reset(); edges.reset(); clusters.reset(); // Create a vertex for each corner for (int idx = 0; idx < corners.size(); idx++) { Vertex v = vertexes.grow(); v.reset(); v.index ...
java
public void process(List<ChessboardCorner> corners ) { this.corners = corners; // reset internal data structures vertexes.reset(); edges.reset(); clusters.reset(); // Create a vertex for each corner for (int idx = 0; idx < corners.size(); idx++) { Vertex v = vertexes.grow(); v.reset(); v.index ...
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Processes corners and finds clusters of chessboard patterns @param corners Detected chessboard patterns. Not modified.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterFinder.java#L137-L208
train
lessthanoptimal/BoofCV
main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterFinder.java
ChessboardCornerClusterFinder.printDualGraph
public void printDualGraph() { System.out.println("============= Dual"); int l = BoofMiscOps.numDigits(vertexes.size); String format = "%"+l+"d"; for( Vertex n : vertexes.toList() ) { ChessboardCorner c = corners.get(n.index); System.out.printf("["+format+"] {%3.0f, %3.0f} -> 90[ ",n.index,c.x,c.y); ...
java
public void printDualGraph() { System.out.println("============= Dual"); int l = BoofMiscOps.numDigits(vertexes.size); String format = "%"+l+"d"; for( Vertex n : vertexes.toList() ) { ChessboardCorner c = corners.get(n.index); System.out.printf("["+format+"] {%3.0f, %3.0f} -> 90[ ",n.index,c.x,c.y); ...
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Prints the graph. Used for debugging the code.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterFinder.java#L213-L233
train
lessthanoptimal/BoofCV
main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterFinder.java
ChessboardCornerClusterFinder.findVertexNeighbors
void findVertexNeighbors(Vertex target , List<ChessboardCorner> corners ) { // if( target.index == 18 ) { // System.out.println("Vertex Neighbors "+target.index); // } ChessboardCorner targetCorner = corners.get(target.index); // distance is Euclidean squared double maxDist = Double.MAX_VALUE==maxNeighborDi...
java
void findVertexNeighbors(Vertex target , List<ChessboardCorner> corners ) { // if( target.index == 18 ) { // System.out.println("Vertex Neighbors "+target.index); // } ChessboardCorner targetCorner = corners.get(target.index); // distance is Euclidean squared double maxDist = Double.MAX_VALUE==maxNeighborDi...
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Use nearest neighbor search to find closest corners. Split those into two groups, parallel and perpendicular.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterFinder.java#L255-L326
train
lessthanoptimal/BoofCV
main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterFinder.java
ChessboardCornerClusterFinder.handleAmbiguousVertexes
void handleAmbiguousVertexes(List<ChessboardCorner> corners) { List<Vertex> candidates = new ArrayList<>(); for (int idx = 0; idx < vertexes.size(); idx++) { Vertex target = vertexes.get(idx); // median distance was previously found based on the closer neighbors. In an actual chessboard // there are solid...
java
void handleAmbiguousVertexes(List<ChessboardCorner> corners) { List<Vertex> candidates = new ArrayList<>(); for (int idx = 0; idx < vertexes.size(); idx++) { Vertex target = vertexes.get(idx); // median distance was previously found based on the closer neighbors. In an actual chessboard // there are solid...
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Identify ambiguous vertexes which are too close to each other. Select the corner with the highest intensity score and remove the rest
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterFinder.java#L332-L376
train
lessthanoptimal/BoofCV
main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterFinder.java
ChessboardCornerClusterFinder.disconnectInvalidVertices
void disconnectInvalidVertices() { // add elements with 1 or 2 edges openVertexes.clear(); for (int idxVert = 0; idxVert < vertexes.size; idxVert++) { Vertex n = vertexes.get(idxVert); if( n.connections.size() == 1 || n.connections.size()==2) { openVertexes.add(n); } } // continue until there ar...
java
void disconnectInvalidVertices() { // add elements with 1 or 2 edges openVertexes.clear(); for (int idxVert = 0; idxVert < vertexes.size; idxVert++) { Vertex n = vertexes.get(idxVert); if( n.connections.size() == 1 || n.connections.size()==2) { openVertexes.add(n); } } // continue until there ar...
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Disconnect the edges from invalid vertices. Invalid ones have only one edge or two edges which do not connect to a common vertex, i.e. they are point 180 degrees away from each other.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterFinder.java#L382-L433
train
lessthanoptimal/BoofCV
main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterFinder.java
ChessboardCornerClusterFinder.removeReferences
void removeReferences( Vertex remove , EdgeType type ) { EdgeSet removeSet = remove.getEdgeSet(type); for (int i = removeSet.size()-1; i >= 0; i--) { Vertex v = removeSet.get(i).dst; EdgeSet setV = v.getEdgeSet(type); // remove the connection from v to 'remove'. Be careful since the connection isn't always...
java
void removeReferences( Vertex remove , EdgeType type ) { EdgeSet removeSet = remove.getEdgeSet(type); for (int i = removeSet.size()-1; i >= 0; i--) { Vertex v = removeSet.get(i).dst; EdgeSet setV = v.getEdgeSet(type); // remove the connection from v to 'remove'. Be careful since the connection isn't always...
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Go through all the vertexes that 'remove' is connected to and remove that link. if it is in the connected list swap it with 'replaceWith'.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterFinder.java#L439-L451
train
lessthanoptimal/BoofCV
main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterFinder.java
ChessboardCornerClusterFinder.selectConnections
void selectConnections( Vertex target ) { // There needs to be at least two corners if( target.perpendicular.size() <= 1 ) return; // if( target.index == 16 ) { // System.out.println("ASDSAD"); // } // System.out.println("======= Connecting "+target.index); double bestError = Double.MAX_VALUE; List<Ed...
java
void selectConnections( Vertex target ) { // There needs to be at least two corners if( target.perpendicular.size() <= 1 ) return; // if( target.index == 16 ) { // System.out.println("ASDSAD"); // } // System.out.println("======= Connecting "+target.index); double bestError = Double.MAX_VALUE; List<Ed...
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Select the best 2,3, or 4 perpendicular vertexes to connect to. These are the output grid connections.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterFinder.java#L456-L515
train
lessthanoptimal/BoofCV
main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterFinder.java
ChessboardCornerClusterFinder.findNext
boolean findNext( int firstIdx , EdgeSet splitterSet , EdgeSet candidateSet , double parallel, SearchResults results ) { Edge e0 = candidateSet.get(firstIdx); results.index = -1; results.error = Double.MAX_VALUE; boolean checkParallel = !Double.isNaN(parallel); for (int i = 0; i < candidateSet...
java
boolean findNext( int firstIdx , EdgeSet splitterSet , EdgeSet candidateSet , double parallel, SearchResults results ) { Edge e0 = candidateSet.get(firstIdx); results.index = -1; results.error = Double.MAX_VALUE; boolean checkParallel = !Double.isNaN(parallel); for (int i = 0; i < candidateSet...
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Greedily select the next edge that will belong to the final graph. @param firstIdx Index of the edge CW of the one being considered @param splitterSet Set of edges that the splitter can belong to @param candidateSet Set of edges that the next edge can belong to @param parallel if NaN this is the angle the edge should ...
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterFinder.java#L527-L598
train
lessthanoptimal/BoofCV
main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterFinder.java
ChessboardCornerClusterFinder.findSplitter
boolean findSplitter(double ccw0 , double ccw1 , EdgeSet master , EdgeSet other1 , EdgeSet other2 , TupleI32 output ) { double bestDistance = Double.MAX_VALUE; for (int i = 0; i < master.size(); i++) { // select the splitter Edge me = master.get(i); // TODO decide if this is helpful or not...
java
boolean findSplitter(double ccw0 , double ccw1 , EdgeSet master , EdgeSet other1 , EdgeSet other2 , TupleI32 output ) { double bestDistance = Double.MAX_VALUE; for (int i = 0; i < master.size(); i++) { // select the splitter Edge me = master.get(i); // TODO decide if this is helpful or not...
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Splitter is a vertex that has an angle between two edges being considered. @param ccw0 angle of edge 0 @param ccw1 angle of edge 1 @param master Set of edges that contains all potential spitters @param other1 set of perpendicular edges to vertex ccw0 @param other2 set of perpendicular edges to vertex ccw1 @param outpu...
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterFinder.java#L611-L665
train
lessthanoptimal/BoofCV
main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterFinder.java
ChessboardCornerClusterFinder.repairVertexes
private void repairVertexes() { // System.out.println("######## Repair"); for (int idxV = 0; idxV < dirtyVertexes.size(); idxV++) { final Vertex v = dirtyVertexes.get(idxV); // System.out.println(" dirty="+v.index); bestSolution.clear(); for (int idxE = 0; idxE < v.perpendicular.size(); idxE++) { /...
java
private void repairVertexes() { // System.out.println("######## Repair"); for (int idxV = 0; idxV < dirtyVertexes.size(); idxV++) { final Vertex v = dirtyVertexes.get(idxV); // System.out.println(" dirty="+v.index); bestSolution.clear(); for (int idxE = 0; idxE < v.perpendicular.size(); idxE++) { /...
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Given the current graph, attempt to replace edges from vertexes which lost them in an apparent bad decision. This is a very simple algorithm and gives up if the graph around the current node is less than perfect. 1) Can only connect to vertexes which lost edges 2) Can't modify an existing edge 3) Parallel lines must b...
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterFinder.java#L677-L765
train
lessthanoptimal/BoofCV
main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterFinder.java
ChessboardCornerClusterFinder.convertToOutput
private void convertToOutput(List<ChessboardCorner> corners) { c2n.resize(corners.size()); n2c.resize(vertexes.size()); open.reset(); n2c.fill(-1); c2n.fill(-1); for (int seedIdx = 0; seedIdx < vertexes.size; seedIdx++) { Vertex seedN = vertexes.get(seedIdx); if( seedN.marked) continue; Chess...
java
private void convertToOutput(List<ChessboardCorner> corners) { c2n.resize(corners.size()); n2c.resize(vertexes.size()); open.reset(); n2c.fill(-1); c2n.fill(-1); for (int seedIdx = 0; seedIdx < vertexes.size; seedIdx++) { Vertex seedN = vertexes.get(seedIdx); if( seedN.marked) continue; Chess...
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Converts the internal graphs into unordered chessboard grids.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterFinder.java#L771-L815
train
lessthanoptimal/BoofCV
main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterFinder.java
ChessboardCornerClusterFinder.growCluster
private void growCluster(List<ChessboardCorner> corners, int seedIdx, ChessboardCornerGraph graph) { // open contains corner list indexes open.add(seedIdx); while( open.size > 0 ) { int cornerIdx = open.pop(); Vertex v = vertexes.get(cornerIdx); // make sure it hasn't already been processed if( v.mar...
java
private void growCluster(List<ChessboardCorner> corners, int seedIdx, ChessboardCornerGraph graph) { // open contains corner list indexes open.add(seedIdx); while( open.size > 0 ) { int cornerIdx = open.pop(); Vertex v = vertexes.get(cornerIdx); // make sure it hasn't already been processed if( v.mar...
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Given the initial seed, add all connected nodes to the output cluster while keeping track of how to convert one node index into another one, between the two graphs
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterFinder.java#L821-L847
train
lessthanoptimal/BoofCV
main/boofcv-feature/src/main/java/boofcv/alg/shapes/edge/BaseIntegralEdge.java
BaseIntegralEdge.setTransform
public void setTransform( PixelTransform<Point2D_F32> undistToDist ) { if( undistToDist != null ) { InterpolatePixelS<T> interpolate = FactoryInterpolation.bilinearPixelS(imageType, BorderType.EXTENDED); integralImage = new GImageGrayDistorted<>(undistToDist, interpolate); } else { integralImage = FactoryG...
java
public void setTransform( PixelTransform<Point2D_F32> undistToDist ) { if( undistToDist != null ) { InterpolatePixelS<T> interpolate = FactoryInterpolation.bilinearPixelS(imageType, BorderType.EXTENDED); integralImage = new GImageGrayDistorted<>(undistToDist, interpolate); } else { integralImage = FactoryG...
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Used to specify a transform that is applied to pixel coordinates to bring them back into original input image coordinates. For example if the input image has lens distortion but the edge were found in undistorted coordinates this code needs to know how to go from undistorted back into distorted image coordinates in or...
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-feature/src/main/java/boofcv/alg/shapes/edge/BaseIntegralEdge.java#L58-L65
train
lessthanoptimal/BoofCV
main/boofcv-geo/src/main/java/boofcv/alg/geo/trifocal/EnforceTrifocalGeometry.java
EnforceTrifocalGeometry.process
public void process( Point3D_F64 e2 , Point3D_F64 e3 , DMatrixRMaj A ) { // construct the linear system that the solution which solves the unknown square // matrices in the camera matrices constructE(e2, e3); // Computes U, which is used to map the 18 unknowns onto the 27 trifocal unknowns svdU.decompose(E);...
java
public void process( Point3D_F64 e2 , Point3D_F64 e3 , DMatrixRMaj A ) { // construct the linear system that the solution which solves the unknown square // matrices in the camera matrices constructE(e2, e3); // Computes U, which is used to map the 18 unknowns onto the 27 trifocal unknowns svdU.decompose(E);...
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Computes a trifocal tensor which minimizes the algebraic error given the two epipoles and the linear constraint matrix. The epipoles are from a previously computed trifocal tensor. @param e2 Epipole of first image in the second image @param e3 Epipole of first image in the third image @param A Linear constraint matri...
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-geo/src/main/java/boofcv/alg/geo/trifocal/EnforceTrifocalGeometry.java#L85-L117
train
lessthanoptimal/BoofCV
main/boofcv-geo/src/main/java/boofcv/alg/geo/trifocal/EnforceTrifocalGeometry.java
EnforceTrifocalGeometry.constructE
protected void constructE( Point3D_F64 e2 , Point3D_F64 e3 ) { E.zero(); for( int i = 0; i < 3; i++ ) { for( int j = 0; j < 3; j++ ) { for( int k = 0; k < 3; k++ ) { // which element in the trifocal tensor is being manipulated int row = 9*i + 3*j + k; // which unknowns are being multiplied by...
java
protected void constructE( Point3D_F64 e2 , Point3D_F64 e3 ) { E.zero(); for( int i = 0; i < 3; i++ ) { for( int j = 0; j < 3; j++ ) { for( int k = 0; k < 3; k++ ) { // which element in the trifocal tensor is being manipulated int row = 9*i + 3*j + k; // which unknowns are being multiplied by...
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The matrix E is a linear system for computing the trifocal tensor. The columns are the unknown square matrices from view 2 and 3. The right most column in both projection matrices are the provided epipoles, whose values are inserted into E
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-geo/src/main/java/boofcv/alg/geo/trifocal/EnforceTrifocalGeometry.java#L140-L157
train
lessthanoptimal/BoofCV
main/boofcv-geo/src/main/java/boofcv/struct/geo/TrifocalTensor.java
TrifocalTensor.copy
public TrifocalTensor copy() { TrifocalTensor ret = new TrifocalTensor(); ret.T1.set(T1); ret.T2.set(T2); ret.T3.set(T3); return ret; }
java
public TrifocalTensor copy() { TrifocalTensor ret = new TrifocalTensor(); ret.T1.set(T1); ret.T2.set(T2); ret.T3.set(T3); return ret; }
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Returns a new copy of the TrifocalTensor @return Copy of the trifocal tensor
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-geo/src/main/java/boofcv/struct/geo/TrifocalTensor.java#L101-L107
train
lessthanoptimal/BoofCV
main/boofcv-feature/src/main/java/boofcv/alg/feature/disparity/DisparitySparseScoreSadRect.java
DisparitySparseScoreSadRect.setImages
public void setImages( Input left , Input right ) { InputSanityCheck.checkSameShape(left, right); this.left = left; this.right = right; }
java
public void setImages( Input left , Input right ) { InputSanityCheck.checkSameShape(left, right); this.left = left; this.right = right; }
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Specify inputs for left and right camera images. @param left Rectified left camera image. @param right Rectified right camera image.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-feature/src/main/java/boofcv/alg/feature/disparity/DisparitySparseScoreSadRect.java#L72-L77
train
lessthanoptimal/BoofCV
demonstrations/src/main/java/boofcv/gui/DemonstrationBase.java
DemonstrationBase.getImageType
protected <T extends ImageBase> ImageType<T> getImageType( int which ) { synchronized ( inputStreams ) { return inputStreams.get(which).imageType; } }
java
protected <T extends ImageBase> ImageType<T> getImageType( int which ) { synchronized ( inputStreams ) { return inputStreams.get(which).imageType; } }
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Get input input type for a stream safely
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/demonstrations/src/main/java/boofcv/gui/DemonstrationBase.java#L150-L154
train
lessthanoptimal/BoofCV
demonstrations/src/main/java/boofcv/gui/DemonstrationBase.java
DemonstrationBase.updateRecentItems
private void updateRecentItems() { if( menuRecent == null ) return; menuRecent.removeAll(); List<String> recentFiles = BoofSwingUtil.getListOfRecentFiles(this); for( String filePath : recentFiles ) { final File f = new File(filePath); JMenuItem recentItem = new JMenuItem(f.getName()); recentItem.add...
java
private void updateRecentItems() { if( menuRecent == null ) return; menuRecent.removeAll(); List<String> recentFiles = BoofSwingUtil.getListOfRecentFiles(this); for( String filePath : recentFiles ) { final File f = new File(filePath); JMenuItem recentItem = new JMenuItem(f.getName()); recentItem.add...
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Updates the list in recent menu
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/demonstrations/src/main/java/boofcv/gui/DemonstrationBase.java#L230-L246
train
lessthanoptimal/BoofCV
demonstrations/src/main/java/boofcv/gui/DemonstrationBase.java
DemonstrationBase.openExample
public void openExample( Object o ) { if (o instanceof PathLabel) { PathLabel p = (PathLabel)o; if( p.path.length == 1 ) openFile(new File(p.path[0])); else { // openFile(new File(p.path[0])); openImageSet(p.path); } } else if (o instanceof String) { openFile(new File((String) o)); } els...
java
public void openExample( Object o ) { if (o instanceof PathLabel) { PathLabel p = (PathLabel)o; if( p.path.length == 1 ) openFile(new File(p.path[0])); else { // openFile(new File(p.path[0])); openImageSet(p.path); } } else if (o instanceof String) { openFile(new File((String) o)); } els...
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Function that is invoked when an example has been selected
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/demonstrations/src/main/java/boofcv/gui/DemonstrationBase.java#L251-L265
train
lessthanoptimal/BoofCV
demonstrations/src/main/java/boofcv/gui/DemonstrationBase.java
DemonstrationBase.stopAllInputProcessing
public void stopAllInputProcessing() { ProcessThread threadProcess; synchronized (inputStreams) { threadProcess = this.threadProcess; if( threadProcess != null ) { if( threadProcess.running ) { threadProcess.requestStop = true; } else { threadProcess = this.threadProcess = null; } } ...
java
public void stopAllInputProcessing() { ProcessThread threadProcess; synchronized (inputStreams) { threadProcess = this.threadProcess; if( threadProcess != null ) { if( threadProcess.running ) { threadProcess.requestStop = true; } else { threadProcess = this.threadProcess = null; } } ...
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Blocks until it kills all input streams from running
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/demonstrations/src/main/java/boofcv/gui/DemonstrationBase.java#L270-L304
train
lessthanoptimal/BoofCV
demonstrations/src/main/java/boofcv/gui/DemonstrationBase.java
DemonstrationBase.openFile
public void openFile(File file) { final String path = massageFilePath(file); if( path == null ) return; inputFilePath = path; // update recent items menu BoofSwingUtil.invokeNowOrLater(() -> { BoofSwingUtil.addToRecentFiles(DemonstrationBase.this,path); updateRecentItems(); }); BufferedImage bu...
java
public void openFile(File file) { final String path = massageFilePath(file); if( path == null ) return; inputFilePath = path; // update recent items menu BoofSwingUtil.invokeNowOrLater(() -> { BoofSwingUtil.addToRecentFiles(DemonstrationBase.this,path); updateRecentItems(); }); BufferedImage bu...
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Opens a file. First it will attempt to open it as an image. If that fails it will try opening it as a video. If all else fails tell the user it has failed. If a streaming source was running before it will be stopped.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/demonstrations/src/main/java/boofcv/gui/DemonstrationBase.java#L346-L365
train
lessthanoptimal/BoofCV
demonstrations/src/main/java/boofcv/gui/DemonstrationBase.java
DemonstrationBase.openImageSet
public void openImageSet(String ...files ) { synchronized (lockStartingProcess) { if( startingProcess ) { System.out.println("Ignoring open image set request. Detected spamming"); return; } startingProcess = true; } stopAllInputProcessing(); synchronized (inputStreams) { inputMethod = Inp...
java
public void openImageSet(String ...files ) { synchronized (lockStartingProcess) { if( startingProcess ) { System.out.println("Ignoring open image set request. Detected spamming"); return; } startingProcess = true; } stopAllInputProcessing(); synchronized (inputStreams) { inputMethod = Inp...
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Opens a set of images @param files
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/demonstrations/src/main/java/boofcv/gui/DemonstrationBase.java#L404-L424
train
lessthanoptimal/BoofCV
demonstrations/src/main/java/boofcv/gui/DemonstrationBase.java
DemonstrationBase.openNextFile
public void openNextFile() { if( inputFilePath == null || inputMethod != InputMethod.IMAGE ) return; String path; try { // need to remove annoying %20 from the path is there is whitespace path = URLDecoder.decode(inputFilePath, "utf-8"); } catch (UnsupportedEncodingException e) { e.printStackTrace(...
java
public void openNextFile() { if( inputFilePath == null || inputMethod != InputMethod.IMAGE ) return; String path; try { // need to remove annoying %20 from the path is there is whitespace path = URLDecoder.decode(inputFilePath, "utf-8"); } catch (UnsupportedEncodingException e) { e.printStackTrace(...
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Opens the next file in the directory by lexicographical order.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/demonstrations/src/main/java/boofcv/gui/DemonstrationBase.java#L429-L474
train
lessthanoptimal/BoofCV
demonstrations/src/main/java/boofcv/gui/DemonstrationBase.java
DemonstrationBase.openVideo
protected void openVideo(boolean reopen , String ...filePaths) { synchronized (lockStartingProcess) { if( startingProcess ) { System.out.println("Ignoring video request. Detected spamming"); return; } startingProcess = true; } synchronized (inputStreams) { if (inputStreams.size() != filePath...
java
protected void openVideo(boolean reopen , String ...filePaths) { synchronized (lockStartingProcess) { if( startingProcess ) { System.out.println("Ignoring video request. Detected spamming"); return; } startingProcess = true; } synchronized (inputStreams) { if (inputStreams.size() != filePath...
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Before invoking this function make sure waitingToOpenImage is false AND that the previous input has been stopped
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/demonstrations/src/main/java/boofcv/gui/DemonstrationBase.java#L479-L541
train
lessthanoptimal/BoofCV
demonstrations/src/main/java/boofcv/gui/DemonstrationBase.java
DemonstrationBase.display
public void display(String appName ) { waitUntilInputSizeIsKnown(); this.appName = appName; window = ShowImages.showWindow(this,appName,true); window.setJMenuBar(menuBar); }
java
public void display(String appName ) { waitUntilInputSizeIsKnown(); this.appName = appName; window = ShowImages.showWindow(this,appName,true); window.setJMenuBar(menuBar); }
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Opens a window with this application inside of it @param appName Name of the application
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/demonstrations/src/main/java/boofcv/gui/DemonstrationBase.java#L658-L663
train
lessthanoptimal/BoofCV
demonstrations/src/main/java/boofcv/gui/DemonstrationBase.java
DemonstrationBase.openFileMenuBar
protected void openFileMenuBar() { List<BoofSwingUtil.FileTypes> types = new ArrayList<>(); if( allowImages ) types.add(BoofSwingUtil.FileTypes.IMAGES); if( allowVideos ) types.add(BoofSwingUtil.FileTypes.VIDEOS); BoofSwingUtil.FileTypes array[] = types.toArray(new BoofSwingUtil.FileTypes[0]); File fil...
java
protected void openFileMenuBar() { List<BoofSwingUtil.FileTypes> types = new ArrayList<>(); if( allowImages ) types.add(BoofSwingUtil.FileTypes.IMAGES); if( allowVideos ) types.add(BoofSwingUtil.FileTypes.VIDEOS); BoofSwingUtil.FileTypes array[] = types.toArray(new BoofSwingUtil.FileTypes[0]); File fil...
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Open file in the menu bar was invoked by the user
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/demonstrations/src/main/java/boofcv/gui/DemonstrationBase.java#L693-L705
train
lessthanoptimal/BoofCV
demonstrations/src/main/java/boofcv/gui/DemonstrationBase.java
DemonstrationBase.reprocessInput
public void reprocessInput() { if ( inputMethod == InputMethod.VIDEO ) { openVideo(true,inputFilePath); } else if( inputMethod == InputMethod.IMAGE ) { BufferedImage buff = inputStreams.get(0).getBufferedImage(); openImage(true,new File(inputFilePath).getName(),buff);// TODO still does a pointless image co...
java
public void reprocessInput() { if ( inputMethod == InputMethod.VIDEO ) { openVideo(true,inputFilePath); } else if( inputMethod == InputMethod.IMAGE ) { BufferedImage buff = inputStreams.get(0).getBufferedImage(); openImage(true,new File(inputFilePath).getName(),buff);// TODO still does a pointless image co...
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If just a single image was processed it will process it again. If it's a stream there is no need to reprocess, the next image will be handled soon enough.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/demonstrations/src/main/java/boofcv/gui/DemonstrationBase.java#L880-L889
train
lessthanoptimal/BoofCV
main/boofcv-feature/src/main/java/boofcv/alg/feature/detect/interest/GeneralFeatureDetector.java
GeneralFeatureDetector.process
public void process(I image, D derivX, D derivY, D derivXX, D derivYY, D derivXY) { intensity.process(image, derivX, derivY, derivXX, derivYY, derivXY); GrayF32 intensityImage = intensity.getIntensity(); int numSelectMin = -1; int numSelectMax = -1; if( maxFeatures > 0 ) { if( intensity.localMinimums() ) ...
java
public void process(I image, D derivX, D derivY, D derivXX, D derivYY, D derivXY) { intensity.process(image, derivX, derivY, derivXX, derivYY, derivXY); GrayF32 intensityImage = intensity.getIntensity(); int numSelectMin = -1; int numSelectMax = -1; if( maxFeatures > 0 ) { if( intensity.localMinimums() ) ...
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Computes point features from image gradients. @param image Original image. @param derivX image derivative in along the x-axis. Only needed if {@link #getRequiresGradient()} is true. @param derivY image derivative in along the y-axis. Only needed if {@link #getRequiresGradient()} is true. @param derivXX Second deri...
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-feature/src/main/java/boofcv/alg/feature/detect/interest/GeneralFeatureDetector.java#L107-L149
train
lessthanoptimal/BoofCV
main/boofcv-feature/src/main/java/boofcv/factory/feature/describe/FactoryDescribeRegionPoint.java
FactoryDescribeRegionPoint.surfColorStable
public static <T extends ImageBase<T>, II extends ImageGray<II>> DescribeRegionPoint<T,BrightFeature> surfColorStable(ConfigSurfDescribe.Stability config, ImageType<T> imageType) { Class bandType = imageType.getImageClass(); Class<II> integralType = GIntegralImageOps.getIntegralType(bandType); DescribePointSur...
java
public static <T extends ImageBase<T>, II extends ImageGray<II>> DescribeRegionPoint<T,BrightFeature> surfColorStable(ConfigSurfDescribe.Stability config, ImageType<T> imageType) { Class bandType = imageType.getImageClass(); Class<II> integralType = GIntegralImageOps.getIntegralType(bandType); DescribePointSur...
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Color variant of the SURF descriptor which has been designed for stability. @see DescribePointSurfPlanar @param config SURF configuration. Pass in null for default options. @param imageType Type of input image. @return SURF color description extractor
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-feature/src/main/java/boofcv/factory/feature/describe/FactoryDescribeRegionPoint.java#L127-L142
train
lessthanoptimal/BoofCV
main/boofcv-feature/src/main/java/boofcv/factory/feature/describe/FactoryDescribeRegionPoint.java
FactoryDescribeRegionPoint.pixel
@SuppressWarnings({"unchecked"}) public static <T extends ImageGray<T>, D extends TupleDesc> DescribeRegionPoint<T,D> pixel( int regionWidth , int regionHeight , Class<T> imageType ) { return new WrapDescribePixelRegion( FactoryDescribePointAlgs.pixelRegion(regionWidth,regionHeight,imageType),imageType); }
java
@SuppressWarnings({"unchecked"}) public static <T extends ImageGray<T>, D extends TupleDesc> DescribeRegionPoint<T,D> pixel( int regionWidth , int regionHeight , Class<T> imageType ) { return new WrapDescribePixelRegion( FactoryDescribePointAlgs.pixelRegion(regionWidth,regionHeight,imageType),imageType); }
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Creates a region descriptor based on pixel intensity values alone. A classic and fast to compute descriptor, but much less stable than more modern ones. @see boofcv.alg.feature.describe.DescribePointPixelRegion @param regionWidth How wide the pixel region is. @param regionHeight How tall the pixel region is. @param ...
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-feature/src/main/java/boofcv/factory/feature/describe/FactoryDescribeRegionPoint.java#L215-L220
train
lessthanoptimal/BoofCV
main/boofcv-feature/src/main/java/boofcv/factory/feature/describe/FactoryDescribeRegionPoint.java
FactoryDescribeRegionPoint.pixelNCC
@SuppressWarnings({"unchecked"}) public static <T extends ImageGray<T>> DescribeRegionPoint<T,NccFeature> pixelNCC( int regionWidth , int regionHeight , Class<T> imageType ) { return new WrapDescribePixelRegionNCC( FactoryDescribePointAlgs.pixelRegionNCC(regionWidth,regionHeight,imageType),imageType); }
java
@SuppressWarnings({"unchecked"}) public static <T extends ImageGray<T>> DescribeRegionPoint<T,NccFeature> pixelNCC( int regionWidth , int regionHeight , Class<T> imageType ) { return new WrapDescribePixelRegionNCC( FactoryDescribePointAlgs.pixelRegionNCC(regionWidth,regionHeight,imageType),imageType); }
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Creates a region descriptor based on normalized pixel intensity values alone. This descriptor is designed to be light invariance, but is still less stable than more modern ones. @see boofcv.alg.feature.describe.DescribePointPixelRegionNCC @param regionWidth How wide the pixel region is. @param regionHeight How tall ...
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-feature/src/main/java/boofcv/factory/feature/describe/FactoryDescribeRegionPoint.java#L233-L238
train
lessthanoptimal/BoofCV
main/boofcv-io/src/main/java/boofcv/io/calibration/CalibrationIO.java
CalibrationIO.save
public static <T extends CameraPinhole> void save(T parameters , Writer outputWriter ) { PrintWriter out = new PrintWriter(outputWriter); Yaml yaml = createYmlObject(); Map<String, Object> data = new HashMap<>(); if( parameters instanceof CameraPinholeBrown) { out.println("# Pinhole camera model with radi...
java
public static <T extends CameraPinhole> void save(T parameters , Writer outputWriter ) { PrintWriter out = new PrintWriter(outputWriter); Yaml yaml = createYmlObject(); Map<String, Object> data = new HashMap<>(); if( parameters instanceof CameraPinholeBrown) { out.println("# Pinhole camera model with radi...
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Saves intrinsic camera model to disk @param parameters Camera parameters @param outputWriter Path to where it should be saved
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-io/src/main/java/boofcv/io/calibration/CalibrationIO.java#L56-L89
train
lessthanoptimal/BoofCV
main/boofcv-io/src/main/java/boofcv/io/calibration/CalibrationIO.java
CalibrationIO.save
public static void save(StereoParameters parameters , Writer outputWriter ) { Map<String, Object> map = new HashMap<>(); map.put("model",MODEL_STEREO); map.put(VERSION,0); map.put("left",putModelRadial(parameters.left,null)); map.put("right",putModelRadial(parameters.right,null)); map.put("rightToLeft",put...
java
public static void save(StereoParameters parameters , Writer outputWriter ) { Map<String, Object> map = new HashMap<>(); map.put("model",MODEL_STEREO); map.put(VERSION,0); map.put("left",putModelRadial(parameters.left,null)); map.put("right",putModelRadial(parameters.right,null)); map.put("rightToLeft",put...
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Saves stereo camera model to disk @param parameters Camera parameters @param outputWriter Stream to save the parameters to
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-io/src/main/java/boofcv/io/calibration/CalibrationIO.java#L115-L129
train
lessthanoptimal/BoofCV
main/boofcv-io/src/main/java/boofcv/io/calibration/CalibrationIO.java
CalibrationIO.load
public static <T> T load(Reader reader ) { Yaml yaml = createYmlObject(); Map<String,Object> data = (Map<String, Object>) yaml.load(reader); try { reader.close(); } catch (IOException e) { throw new RuntimeException(e); } return load(data); }
java
public static <T> T load(Reader reader ) { Yaml yaml = createYmlObject(); Map<String,Object> data = (Map<String, Object>) yaml.load(reader); try { reader.close(); } catch (IOException e) { throw new RuntimeException(e); } return load(data); }
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Loads intrinsic parameters from disk @param reader Reader @return Camera model
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-io/src/main/java/boofcv/io/calibration/CalibrationIO.java#L238-L250
train
lessthanoptimal/BoofCV
main/boofcv-calibration/src/main/java/boofcv/alg/geo/calibration/CalibrationPlanarGridZhang99.java
CalibrationPlanarGridZhang99.process
public boolean process( List<CalibrationObservation> observations ) { // compute initial parameter estimates using linear algebra if( !linearEstimate(observations) ) return false; status("Non-linear refinement"); // perform non-linear optimization to improve results if( !performBundleAdjustment()) ret...
java
public boolean process( List<CalibrationObservation> observations ) { // compute initial parameter estimates using linear algebra if( !linearEstimate(observations) ) return false; status("Non-linear refinement"); // perform non-linear optimization to improve results if( !performBundleAdjustment()) ret...
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Processes observed calibration point coordinates and computes camera intrinsic and extrinsic parameters. @param observations Set of observed grid locations in pixel coordinates. @return true if successful and false if it failed
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-calibration/src/main/java/boofcv/alg/geo/calibration/CalibrationPlanarGridZhang99.java#L122-L134
train
lessthanoptimal/BoofCV
main/boofcv-calibration/src/main/java/boofcv/alg/geo/calibration/CalibrationPlanarGridZhang99.java
CalibrationPlanarGridZhang99.linearEstimate
protected boolean linearEstimate(List<CalibrationObservation> observations ) { status("Estimating Homographies"); List<DMatrixRMaj> homographies = new ArrayList<>(); List<Se3_F64> motions = new ArrayList<>(); for( CalibrationObservation obs : observations ) { if( !computeHomography.computeHomography(obs) ...
java
protected boolean linearEstimate(List<CalibrationObservation> observations ) { status("Estimating Homographies"); List<DMatrixRMaj> homographies = new ArrayList<>(); List<Se3_F64> motions = new ArrayList<>(); for( CalibrationObservation obs : observations ) { if( !computeHomography.computeHomography(obs) ...
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Find an initial estimate for calibration parameters using linear techniques.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-calibration/src/main/java/boofcv/alg/geo/calibration/CalibrationPlanarGridZhang99.java#L139-L171
train
lessthanoptimal/BoofCV
main/boofcv-calibration/src/main/java/boofcv/alg/geo/calibration/CalibrationPlanarGridZhang99.java
CalibrationPlanarGridZhang99.performBundleAdjustment
public boolean performBundleAdjustment() { // Configure the sparse Levenberg-Marquardt solver ConfigLevenbergMarquardt configLM = new ConfigLevenbergMarquardt(); configLM.hessianScaling = false; ConfigBundleAdjustment configSBA = new ConfigBundleAdjustment(); configSBA.configOptimizer = configLM; BundleA...
java
public boolean performBundleAdjustment() { // Configure the sparse Levenberg-Marquardt solver ConfigLevenbergMarquardt configLM = new ConfigLevenbergMarquardt(); configLM.hessianScaling = false; ConfigBundleAdjustment configSBA = new ConfigBundleAdjustment(); configSBA.configOptimizer = configLM; BundleA...
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Use non-linear optimization to improve the parameter estimates
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-calibration/src/main/java/boofcv/alg/geo/calibration/CalibrationPlanarGridZhang99.java#L183-L206
train
lessthanoptimal/BoofCV
main/boofcv-calibration/src/main/java/boofcv/alg/geo/calibration/CalibrationPlanarGridZhang99.java
CalibrationPlanarGridZhang99.applyDistortion
public static void applyDistortion(Point2D_F64 normPt, double[] radial, double t1 , double t2 ) { final double x = normPt.x; final double y = normPt.y; double a = 0; double r2 = x*x + y*y; double r2i = r2; for( int i = 0; i < radial.length; i++ ) { a += radial[i]*r2i; r2i *= r2; } normPt.x = x ...
java
public static void applyDistortion(Point2D_F64 normPt, double[] radial, double t1 , double t2 ) { final double x = normPt.x; final double y = normPt.y; double a = 0; double r2 = x*x + y*y; double r2i = r2; for( int i = 0; i < radial.length; i++ ) { a += radial[i]*r2i; r2i *= r2; } normPt.x = x ...
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Applies radial and tangential distortion to the normalized image coordinate. @param normPt point in normalized image coordinates @param radial radial distortion parameters @param t1 tangential parameter @param t2 tangential parameter
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-calibration/src/main/java/boofcv/alg/geo/calibration/CalibrationPlanarGridZhang99.java#L303-L318
train
lessthanoptimal/BoofCV
main/boofcv-geo/src/main/java/boofcv/alg/geo/robust/DistanceSe3SymmetricSq.java
DistanceSe3SymmetricSq.computeDistance
@Override public double computeDistance(AssociatedPair obs) { // triangulate the point in 3D space triangulate.triangulate(obs.p1,obs.p2,keyToCurr,p); if( p.z < 0 ) return Double.MAX_VALUE; // compute observational error in each view double error = errorCam1.errorSq(obs.p1.x,obs.p1.y,p.x/p.z,p.y/p.z); ...
java
@Override public double computeDistance(AssociatedPair obs) { // triangulate the point in 3D space triangulate.triangulate(obs.p1,obs.p2,keyToCurr,p); if( p.z < 0 ) return Double.MAX_VALUE; // compute observational error in each view double error = errorCam1.errorSq(obs.p1.x,obs.p1.y,p.x/p.z,p.y/p.z); ...
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Computes the error given the motion model @param obs Observation in normalized pixel coordinates @return observation error
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-geo/src/main/java/boofcv/alg/geo/robust/DistanceSe3SymmetricSq.java#L93-L112
train
lessthanoptimal/BoofCV
main/boofcv-ip/src/main/java/boofcv/alg/filter/derivative/GImageDerivativeOps.java
GImageDerivativeOps.getDerivativeType
public static <I extends ImageGray<I>, D extends ImageGray<D>> Class<D> getDerivativeType( Class<I> imageType ) { if( imageType == GrayF32.class ) { return (Class<D>) GrayF32.class; } else if( imageType == GrayU8.class ) { return (Class<D>) GrayS16.class; } else if( imageType == GrayU16.class ) { retur...
java
public static <I extends ImageGray<I>, D extends ImageGray<D>> Class<D> getDerivativeType( Class<I> imageType ) { if( imageType == GrayF32.class ) { return (Class<D>) GrayF32.class; } else if( imageType == GrayU8.class ) { return (Class<D>) GrayS16.class; } else if( imageType == GrayU16.class ) { retur...
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Returns the type of image the derivative should be for the specified input type. @param imageType Input image type. @return Appropriate output image type.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-ip/src/main/java/boofcv/alg/filter/derivative/GImageDerivativeOps.java#L57-L68
train
lessthanoptimal/BoofCV
main/boofcv-ip/src/main/java/boofcv/alg/filter/derivative/GImageDerivativeOps.java
GImageDerivativeOps.hessian
public static <I extends ImageGray<I>, D extends ImageGray<D>> void hessian( DerivativeType type , I input , D derivXX , D derivYY , D derivXY , BorderType borderType ) { ImageBorder<I> border = BorderType.SKIP == borderType ? null : FactoryImageBorder.wrap(borderType, input); switch( type ) { case SOBEL: ...
java
public static <I extends ImageGray<I>, D extends ImageGray<D>> void hessian( DerivativeType type , I input , D derivXX , D derivYY , D derivXY , BorderType borderType ) { ImageBorder<I> border = BorderType.SKIP == borderType ? null : FactoryImageBorder.wrap(borderType, input); switch( type ) { case SOBEL: ...
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Computes the hessian from the original input image. Only Sobel and Three supported. @param type Type of gradient to compute @param input Input image @param derivXX Output. Derivative XX @param derivYY Output. Derivative YY @param derivXY Output. Derivative XY @param borderType How it should handle borders. null == ...
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-ip/src/main/java/boofcv/alg/filter/derivative/GImageDerivativeOps.java#L181-L209
train
lessthanoptimal/BoofCV
main/boofcv-ip/src/main/java/boofcv/alg/filter/derivative/GImageDerivativeOps.java
GImageDerivativeOps.hessian
public static <D extends ImageGray<D>> void hessian( DerivativeType type , D derivX , D derivY , D derivXX , D derivYY , D derivXY , BorderType borderType ) { ImageBorder<D> border = BorderType.SKIP == borderType ? null : FactoryImageBorder.wrap(borderType, derivX); switch( type ) { case PREWITT: if( deriv...
java
public static <D extends ImageGray<D>> void hessian( DerivativeType type , D derivX , D derivY , D derivXX , D derivYY , D derivXY , BorderType borderType ) { ImageBorder<D> border = BorderType.SKIP == borderType ? null : FactoryImageBorder.wrap(borderType, derivX); switch( type ) { case PREWITT: if( deriv...
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Computes the hessian from the gradient. Only Prewitt, Sobel and Three supported. @param type Type of gradient to compute @param derivX Input derivative X @param derivY Input derivative Y @param derivXX Output. Derivative XX @param derivYY Output. Derivative YY @param derivXY Output. Derivative XY @param borderType H...
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-ip/src/main/java/boofcv/alg/filter/derivative/GImageDerivativeOps.java#L222-L260
train
lessthanoptimal/BoofCV
main/boofcv-ip/src/main/java/boofcv/alg/filter/derivative/GImageDerivativeOps.java
GImageDerivativeOps.lookupKernelX
public static KernelBase lookupKernelX( DerivativeType type , boolean isInteger) { switch( type ) { case PREWITT: return GradientPrewitt.getKernelX(isInteger); case SOBEL: return GradientSobel.getKernelX(isInteger); case THREE: return GradientThree.getKernelX(isInteger); case TWO_0: ret...
java
public static KernelBase lookupKernelX( DerivativeType type , boolean isInteger) { switch( type ) { case PREWITT: return GradientPrewitt.getKernelX(isInteger); case SOBEL: return GradientSobel.getKernelX(isInteger); case THREE: return GradientThree.getKernelX(isInteger); case TWO_0: ret...
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Returns the kernel for finding the X derivative. @param type Type of gradient @param isInteger integer or floating point kernels @return The kernel. Can be 1D or 2D
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-ip/src/main/java/boofcv/alg/filter/derivative/GImageDerivativeOps.java#L268-L287
train
lessthanoptimal/BoofCV
main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/circle/KeyPointsCircleHexagonalGrid.java
KeyPointsCircleHexagonalGrid.computeEllipseCenters
boolean computeEllipseCenters() { keypoints.reset(); for (int tangentIdx = 0; tangentIdx < tangents.size(); tangentIdx++) { // System.out.println("tangent id "+tangentIdx); Tangents t = tangents.get(tangentIdx); Point2D_F64 center = keypoints.grow(); center.set(0,0); double totalWeight = 0; for (...
java
boolean computeEllipseCenters() { keypoints.reset(); for (int tangentIdx = 0; tangentIdx < tangents.size(); tangentIdx++) { // System.out.println("tangent id "+tangentIdx); Tangents t = tangents.get(tangentIdx); Point2D_F64 center = keypoints.grow(); center.set(0,0); double totalWeight = 0; for (...
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Finds the intersection of all the tangent lines with each other the computes the average of those points. That location is where the center is set to. Each intersection of lines is weighted by the acute angle. lines which are 90 degrees to each other are less sensitive to noise
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/circle/KeyPointsCircleHexagonalGrid.java#L190-L237
train
lessthanoptimal/BoofCV
main/boofcv-types/src/main/java/boofcv/struct/image/Planar.java
Planar.getBand
public T getBand(int band) { if (band >= bands.length || band < 0) throw new IllegalArgumentException("The specified band is out of bounds: "+band); return bands[band]; }
java
public T getBand(int band) { if (band >= bands.length || band < 0) throw new IllegalArgumentException("The specified band is out of bounds: "+band); return bands[band]; }
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Returns a band in the multi-band image. @param band Which band should be returned. @return Image band
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-types/src/main/java/boofcv/struct/image/Planar.java#L132-L137
train
lessthanoptimal/BoofCV
main/boofcv-types/src/main/java/boofcv/struct/image/Planar.java
Planar.setTo
@Override public void setTo( Planar<T> orig) { if (orig.width != width || orig.height != height) reshape(orig.width,orig.height); if( orig.getBandType() != getBandType() ) throw new IllegalArgumentException("The band type must be the same"); int N = orig.getNumBands(); if( N != getNumBands() ) { setN...
java
@Override public void setTo( Planar<T> orig) { if (orig.width != width || orig.height != height) reshape(orig.width,orig.height); if( orig.getBandType() != getBandType() ) throw new IllegalArgumentException("The band type must be the same"); int N = orig.getNumBands(); if( N != getNumBands() ) { setN...
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Sets the values of each pixel equal to the pixels in the specified matrix. Automatically resized to match the input image. @param orig The original image whose value is to be copied into this one
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-types/src/main/java/boofcv/struct/image/Planar.java#L181-L196
train
lessthanoptimal/BoofCV
main/boofcv-types/src/main/java/boofcv/struct/image/Planar.java
Planar.createNew
@Override public Planar<T> createNew(int imgWidth, int imgHeight) { return new Planar<>(type, imgWidth, imgHeight, bands.length); }
java
@Override public Planar<T> createNew(int imgWidth, int imgHeight) { return new Planar<>(type, imgWidth, imgHeight, bands.length); }
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Creates a new image of the same type and number of bands @param imgWidth image width @param imgHeight image height @return new image
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-types/src/main/java/boofcv/struct/image/Planar.java#L255-L258
train
lessthanoptimal/BoofCV
main/boofcv-types/src/main/java/boofcv/struct/image/Planar.java
Planar.reorderBands
public void reorderBands( int ...order ) { T[] bands = (T[]) Array.newInstance(type, order.length); for (int i = 0; i < order.length; i++) { bands[i] = this.bands[order[i]]; } this.bands = bands; }
java
public void reorderBands( int ...order ) { T[] bands = (T[]) Array.newInstance(type, order.length); for (int i = 0; i < order.length; i++) { bands[i] = this.bands[order[i]]; } this.bands = bands; }
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Changes the bands order @param order The new band order
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-types/src/main/java/boofcv/struct/image/Planar.java#L284-L291
train
lessthanoptimal/BoofCV
main/boofcv-types/src/main/java/boofcv/struct/image/Planar.java
Planar.setNumberOfBands
@Override public void setNumberOfBands( int numberOfBands ) { if( numberOfBands == this.bands.length ) return; T[] bands = (T[]) Array.newInstance(type, numberOfBands); int N = Math.min(numberOfBands, this.bands.length ); for (int i = 0; i < N; i++) { bands[i] = this.bands[i]; } for (int i = N; i < ...
java
@Override public void setNumberOfBands( int numberOfBands ) { if( numberOfBands == this.bands.length ) return; T[] bands = (T[]) Array.newInstance(type, numberOfBands); int N = Math.min(numberOfBands, this.bands.length ); for (int i = 0; i < N; i++) { bands[i] = this.bands[i]; } for (int i = N; i < ...
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Changes the number of bands in the image. A new array is declared and individual bands are recycled if possible @param numberOfBands New number of bands in the image.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-types/src/main/java/boofcv/struct/image/Planar.java#L298-L312
train
lessthanoptimal/BoofCV
main/boofcv-learning/src/main/java/boofcv/struct/learning/Confusion.java
Confusion.computeAccuracy
public double computeAccuracy() { double totalCorrect = 0; double totalIncorrect = 0; for (int i = 0; i < actualCounts.length; i++) { for (int j = 0; j < actualCounts.length; j++) { if( i == j ) { totalCorrect += matrix.get(i,j); } else { totalIncorrect += matrix.get(i,j); } } } ...
java
public double computeAccuracy() { double totalCorrect = 0; double totalIncorrect = 0; for (int i = 0; i < actualCounts.length; i++) { for (int j = 0; j < actualCounts.length; j++) { if( i == j ) { totalCorrect += matrix.get(i,j); } else { totalIncorrect += matrix.get(i,j); } } } ...
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Computes accuracy from the confusion matrix. This is the sum of the fraction correct divide by total number of types. The number of each sample for each type is not taken in account. @return overall accuracy
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-learning/src/main/java/boofcv/struct/learning/Confusion.java#L48-L63
train
lessthanoptimal/BoofCV
main/boofcv-calibration/src/main/java/boofcv/abst/geo/calibration/CalibrateMonoPlanar.java
CalibrateMonoPlanar.addImage
public void addImage( CalibrationObservation observation ) { if( imageWidth == 0 ) { this.imageWidth = observation.getWidth(); this.imageHeight = observation.getHeight(); } else if( observation.getWidth() != this.imageWidth || observation.getHeight() != this.imageHeight) { throw new IllegalArgumentExceptio...
java
public void addImage( CalibrationObservation observation ) { if( imageWidth == 0 ) { this.imageWidth = observation.getWidth(); this.imageHeight = observation.getHeight(); } else if( observation.getWidth() != this.imageWidth || observation.getHeight() != this.imageHeight) { throw new IllegalArgumentExceptio...
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Adds the observations from a calibration target detector @param observation Detected calibration points
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-calibration/src/main/java/boofcv/abst/geo/calibration/CalibrateMonoPlanar.java#L139-L147
train
lessthanoptimal/BoofCV
main/boofcv-calibration/src/main/java/boofcv/abst/geo/calibration/CalibrateMonoPlanar.java
CalibrateMonoPlanar.process
public <T extends CameraModel>T process() { if( zhang99 == null ) throw new IllegalArgumentException("Please call configure first."); zhang99.setVerbose(verbose,0); if( !zhang99.process(observations) ) { throw new RuntimeException("Zhang99 algorithm failed!"); } structure = zhang99.getStructure(); e...
java
public <T extends CameraModel>T process() { if( zhang99 == null ) throw new IllegalArgumentException("Please call configure first."); zhang99.setVerbose(verbose,0); if( !zhang99.process(observations) ) { throw new RuntimeException("Zhang99 algorithm failed!"); } structure = zhang99.getStructure(); e...
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After calibration points have been found this invokes the Zhang99 algorithm to estimate calibration parameters. Error statistics are also computed.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-calibration/src/main/java/boofcv/abst/geo/calibration/CalibrateMonoPlanar.java#L160-L177
train
lessthanoptimal/BoofCV
main/boofcv-calibration/src/main/java/boofcv/abst/geo/calibration/CalibrateMonoPlanar.java
CalibrateMonoPlanar.printErrors
public static void printErrors( List<ImageResults> results ) { double totalError = 0; for( int i = 0; i < results.size(); i++ ) { ImageResults r = results.get(i); totalError += r.meanError; System.out.printf("image %3d Euclidean ( mean = %7.1e max = %7.1e ) bias ( X = %8.1e Y %8.1e )\n",i,r.meanError,r.ma...
java
public static void printErrors( List<ImageResults> results ) { double totalError = 0; for( int i = 0; i < results.size(); i++ ) { ImageResults r = results.get(i); totalError += r.meanError; System.out.printf("image %3d Euclidean ( mean = %7.1e max = %7.1e ) bias ( X = %8.1e Y %8.1e )\n",i,r.meanError,r.ma...
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Prints out error information to standard out
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-calibration/src/main/java/boofcv/abst/geo/calibration/CalibrateMonoPlanar.java#L189-L198
train
lessthanoptimal/BoofCV
integration/boofcv-swing/src/main/java/boofcv/gui/learning/ConfusionMatrixPanel.java
ConfusionMatrixPanel.renderLabels
private void renderLabels(Graphics2D g2, double fontSize) { int numCategories = confusion.getNumRows(); int longestLabel = 0; if(renderLabels) { for (int i = 0; i < numCategories; i++) { longestLabel = Math.max(longestLabel,labels.get(i).length()); } } Font fontLabel = new Font("monospaced", Font....
java
private void renderLabels(Graphics2D g2, double fontSize) { int numCategories = confusion.getNumRows(); int longestLabel = 0; if(renderLabels) { for (int i = 0; i < numCategories; i++) { longestLabel = Math.max(longestLabel,labels.get(i).length()); } } Font fontLabel = new Font("monospaced", Font....
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Renders the names on each category to the side of the confusion matrix
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/integration/boofcv-swing/src/main/java/boofcv/gui/learning/ConfusionMatrixPanel.java#L200-L236
train
lessthanoptimal/BoofCV
integration/boofcv-swing/src/main/java/boofcv/gui/learning/ConfusionMatrixPanel.java
ConfusionMatrixPanel.renderMatrix
private void renderMatrix(Graphics2D g2, double fontSize) { int numCategories = confusion.getNumRows(); Font fontNumber = new Font("Serif", Font.BOLD, (int)(0.6*fontSize + 0.5)); g2.setFont(fontNumber); FontMetrics metrics = g2.getFontMetrics(fontNumber); for (int i = 0; i < numCategories; i++) { int y0 =...
java
private void renderMatrix(Graphics2D g2, double fontSize) { int numCategories = confusion.getNumRows(); Font fontNumber = new Font("Serif", Font.BOLD, (int)(0.6*fontSize + 0.5)); g2.setFont(fontNumber); FontMetrics metrics = g2.getFontMetrics(fontNumber); for (int i = 0; i < numCategories; i++) { int y0 =...
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Renders the confusion matrix and visualizes the value in each cell with a color and optionally a color.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/integration/boofcv-swing/src/main/java/boofcv/gui/learning/ConfusionMatrixPanel.java#L241-L290
train
lessthanoptimal/BoofCV
integration/boofcv-swing/src/main/java/boofcv/gui/learning/ConfusionMatrixPanel.java
ConfusionMatrixPanel.whatIsAtPoint
public LocationInfo whatIsAtPoint( int pixelX , int pixelY , LocationInfo output ) { if( output == null ) output = new LocationInfo(); int numCategories = confusion.getNumRows(); synchronized ( this ) { if( pixelX >= gridWidth ) { output.insideMatrix = false; output.col = output.row = pixelY*numCa...
java
public LocationInfo whatIsAtPoint( int pixelX , int pixelY , LocationInfo output ) { if( output == null ) output = new LocationInfo(); int numCategories = confusion.getNumRows(); synchronized ( this ) { if( pixelX >= gridWidth ) { output.insideMatrix = false; output.col = output.row = pixelY*numCa...
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Use to sample the panel to see what is being displayed at the location clicked. All coordinates are in panel coordinates. @param pixelX x-axis in panel coordinates @param pixelY y-axis in panel coordinates @param output (Optional) storage for output. @return Information on what is at the specified location
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/integration/boofcv-swing/src/main/java/boofcv/gui/learning/ConfusionMatrixPanel.java#L301-L319
train
lessthanoptimal/BoofCV
main/boofcv-sfm/src/main/java/boofcv/alg/sfm/d2/StitchingFromMotion2D.java
StitchingFromMotion2D.configure
public void configure( int widthStitch, int heightStitch , IT worldToInit ) { this.worldToInit = (IT)worldToCurr.createInstance(); if( worldToInit != null ) this.worldToInit.set(worldToInit); this.widthStitch = widthStitch; this.heightStitch = heightStitch; }
java
public void configure( int widthStitch, int heightStitch , IT worldToInit ) { this.worldToInit = (IT)worldToCurr.createInstance(); if( worldToInit != null ) this.worldToInit.set(worldToInit); this.widthStitch = widthStitch; this.heightStitch = heightStitch; }
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Specifies size of stitch image and the location of the initial coordinate system. @param widthStitch Width of the image being stitched into @param heightStitch Height of the image being stitched into @param worldToInit (Option) Used to change the location of the initial frame in stitched image. null means no transform...
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-sfm/src/main/java/boofcv/alg/sfm/d2/StitchingFromMotion2D.java#L120-L126
train
lessthanoptimal/BoofCV
main/boofcv-sfm/src/main/java/boofcv/alg/sfm/d2/StitchingFromMotion2D.java
StitchingFromMotion2D.reset
public void reset() { if( stitchedImage != null ) GImageMiscOps.fill(stitchedImage, 0); motion.reset(); worldToCurr.reset(); first = true; }
java
public void reset() { if( stitchedImage != null ) GImageMiscOps.fill(stitchedImage, 0); motion.reset(); worldToCurr.reset(); first = true; }
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Throws away current results and starts over again
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-sfm/src/main/java/boofcv/alg/sfm/d2/StitchingFromMotion2D.java#L155-L161
train
lessthanoptimal/BoofCV
main/boofcv-sfm/src/main/java/boofcv/alg/sfm/d2/StitchingFromMotion2D.java
StitchingFromMotion2D.checkLargeMotion
private boolean checkLargeMotion( int width , int height ) { if( first ) { getImageCorners(width,height,corners); previousArea = computeArea(corners); first = false; } else { getImageCorners(width,height,corners); double area = computeArea(corners); double change = Math.max(area/previousArea,pre...
java
private boolean checkLargeMotion( int width , int height ) { if( first ) { getImageCorners(width,height,corners); previousArea = computeArea(corners); first = false; } else { getImageCorners(width,height,corners); double area = computeArea(corners); double change = Math.max(area/previousArea,pre...
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Looks for sudden large changes in corner location to detect motion estimation faults. @param width image width @param height image height @return true for fault
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-sfm/src/main/java/boofcv/alg/sfm/d2/StitchingFromMotion2D.java#L169-L188
train
lessthanoptimal/BoofCV
main/boofcv-sfm/src/main/java/boofcv/alg/sfm/d2/StitchingFromMotion2D.java
StitchingFromMotion2D.update
private void update(I image) { computeCurrToInit_PixelTran(); // only process a cropped portion to speed up processing RectangleLength2D_I32 box = DistortImageOps.boundBox(image.width, image.height, stitchedImage.width, stitchedImage.height,work, tranCurrToWorld); int x0 = box.x0; int y0 = box.y0; int...
java
private void update(I image) { computeCurrToInit_PixelTran(); // only process a cropped portion to speed up processing RectangleLength2D_I32 box = DistortImageOps.boundBox(image.width, image.height, stitchedImage.width, stitchedImage.height,work, tranCurrToWorld); int x0 = box.x0; int y0 = box.y0; int...
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Adds the latest image into the stitched image @param image
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-sfm/src/main/java/boofcv/alg/sfm/d2/StitchingFromMotion2D.java#L200-L214
train
lessthanoptimal/BoofCV
main/boofcv-sfm/src/main/java/boofcv/alg/sfm/d2/StitchingFromMotion2D.java
StitchingFromMotion2D.resizeStitchImage
public void resizeStitchImage( int widthStitch, int heightStitch , IT newToOldStitch ) { // copy the old image into the new one workImage.reshape(widthStitch,heightStitch); GImageMiscOps.fill(workImage, 0); if( newToOldStitch != null ) { PixelTransform<Point2D_F32> newToOld = converter.convertPixel(newToOld...
java
public void resizeStitchImage( int widthStitch, int heightStitch , IT newToOldStitch ) { // copy the old image into the new one workImage.reshape(widthStitch,heightStitch); GImageMiscOps.fill(workImage, 0); if( newToOldStitch != null ) { PixelTransform<Point2D_F32> newToOld = converter.convertPixel(newToOld...
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Resizes the stitch image. If no transform is provided then the old stitch region is simply places on top of the new one and copied. Pixels which do not exist in the old image are filled with zero. @param widthStitch The new width of the stitch image. @param heightStitch The new height of the stitch image. @param new...
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-sfm/src/main/java/boofcv/alg/sfm/d2/StitchingFromMotion2D.java#L264-L292
train
lessthanoptimal/BoofCV
main/boofcv-sfm/src/main/java/boofcv/alg/sfm/d2/StitchingFromMotion2D.java
StitchingFromMotion2D.getImageCorners
public Corners getImageCorners( int width , int height , Corners corners ) { if( corners == null ) corners = new Corners(); int w = width; int h = height; tranCurrToWorld.compute(0,0,work); corners.p0.set(work.x, work.y); tranCurrToWorld.compute(w,0,work); corners.p1.set(work.x, work.y); tranCurrTo...
java
public Corners getImageCorners( int width , int height , Corners corners ) { if( corners == null ) corners = new Corners(); int w = width; int h = height; tranCurrToWorld.compute(0,0,work); corners.p0.set(work.x, work.y); tranCurrToWorld.compute(w,0,work); corners.p1.set(work.x, work.y); tranCurrTo...
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Returns the location of the input image's corners inside the stitch image. @return image corners
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-sfm/src/main/java/boofcv/alg/sfm/d2/StitchingFromMotion2D.java#L299-L313
train
lessthanoptimal/BoofCV
main/boofcv-geo/src/main/java/boofcv/alg/geo/trifocal/TrifocalAlgebraicPoint7.java
TrifocalAlgebraicPoint7.minimizeWithGeometricConstraints
private void minimizeWithGeometricConstraints() { extractEpipoles.setTensor(solutionN); extractEpipoles.extractEpipoles(e2,e3); // encode the parameters being optimized param[0] = e2.x; param[1] = e2.y; param[2] = e2.z; param[3] = e3.x; param[4] = e3.y; param[5] = e3.z; // adjust the error function for th...
java
private void minimizeWithGeometricConstraints() { extractEpipoles.setTensor(solutionN); extractEpipoles.extractEpipoles(e2,e3); // encode the parameters being optimized param[0] = e2.x; param[1] = e2.y; param[2] = e2.z; param[3] = e3.x; param[4] = e3.y; param[5] = e3.z; // adjust the error function for th...
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Minimize the algebraic error using LM. The two epipoles are the parameters being optimized.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-geo/src/main/java/boofcv/alg/geo/trifocal/TrifocalAlgebraicPoint7.java#L103-L127
train
lessthanoptimal/BoofCV
main/boofcv-geo/src/main/java/boofcv/alg/geo/PositiveDepthConstraintCheck.java
PositiveDepthConstraintCheck.checkConstraint
public boolean checkConstraint( Point2D_F64 viewA , Point2D_F64 viewB , Se3_F64 fromAtoB ) { triangulate.triangulate(viewA,viewB,fromAtoB,P); if( P.z > 0 ) { SePointOps_F64.transform(fromAtoB,P,P); return P.z > 0; } return false; }
java
public boolean checkConstraint( Point2D_F64 viewA , Point2D_F64 viewB , Se3_F64 fromAtoB ) { triangulate.triangulate(viewA,viewB,fromAtoB,P); if( P.z > 0 ) { SePointOps_F64.transform(fromAtoB,P,P); return P.z > 0; } return false; }
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Checks to see if a single point meets the constraint. @param viewA View of the 3D point from the first camera. Calibrated coordinates. @param viewB View of the 3D point from the second camera. Calibrated coordinates. @param fromAtoB Transform from the B to A camera frame. @return If the triangulated point appears in...
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-geo/src/main/java/boofcv/alg/geo/PositiveDepthConstraintCheck.java#L67-L76
train
lessthanoptimal/BoofCV
main/boofcv-sfm/src/main/java/boofcv/factory/sfm/FactoryMotion2D.java
FactoryMotion2D.createMotion2D
public static <I extends ImageBase<I>, IT extends InvertibleTransform> ImageMotion2D<I,IT> createMotion2D( int ransacIterations , double inlierThreshold,int outlierPrune, int absoluteMinimumTracks, double respawnTrackFraction, double respawnCoverageFraction, boolean refineEstimate , ...
java
public static <I extends ImageBase<I>, IT extends InvertibleTransform> ImageMotion2D<I,IT> createMotion2D( int ransacIterations , double inlierThreshold,int outlierPrune, int absoluteMinimumTracks, double respawnTrackFraction, double respawnCoverageFraction, boolean refineEstimate , ...
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Estimates the 2D motion of an image using different models. @param ransacIterations Number of RANSAC iterations @param inlierThreshold Threshold which defines an inlier. @param outlierPrune If a feature is an outlier for this many turns in a row it is dropped. Try 2 @param absoluteMinimumTracks New features will be re...
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-sfm/src/main/java/boofcv/factory/sfm/FactoryMotion2D.java#L73-L121
train
lessthanoptimal/BoofCV
main/boofcv-sfm/src/main/java/boofcv/factory/sfm/FactoryMotion2D.java
FactoryMotion2D.createVideoStitch
@SuppressWarnings("unchecked") public static <I extends ImageBase<I>, IT extends InvertibleTransform> StitchingFromMotion2D<I, IT> createVideoStitch( double maxJumpFraction , ImageMotion2D<I,IT> motion2D , ImageType<I> imageType ) { StitchingTransform<IT> transform; if( motion2D.getTransformType() == Affine2D_F...
java
@SuppressWarnings("unchecked") public static <I extends ImageBase<I>, IT extends InvertibleTransform> StitchingFromMotion2D<I, IT> createVideoStitch( double maxJumpFraction , ImageMotion2D<I,IT> motion2D , ImageType<I> imageType ) { StitchingTransform<IT> transform; if( motion2D.getTransformType() == Affine2D_F...
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Estimates the image motion then combines images together. Typically used for mosaics and stabilization. @param maxJumpFraction If the area changes by this much between two consecuative frames then the transform is reset. @param motion2D Estimates the image motion. @param imageType Type of image processed @param <I> I...
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-sfm/src/main/java/boofcv/factory/sfm/FactoryMotion2D.java#L134-L159
train
lessthanoptimal/BoofCV
main/boofcv-ip/src/main/java/boofcv/alg/misc/ImageStatistics.java
ImageStatistics.min
public static int min( GrayS32 input ) { if( BoofConcurrency.USE_CONCURRENT ) { return ImplImageStatistics_MT.min(input.data, input.startIndex, input.height, input.width , input.stride); } else { return ImplImageStatistics.min(input.data, input.startIndex, input.height, input.width , input.stride); } }
java
public static int min( GrayS32 input ) { if( BoofConcurrency.USE_CONCURRENT ) { return ImplImageStatistics_MT.min(input.data, input.startIndex, input.height, input.width , input.stride); } else { return ImplImageStatistics.min(input.data, input.startIndex, input.height, input.width , input.stride); } }
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Returns the minimum element value. @param input Input image. Not modified. @return Minimum pixel value.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-ip/src/main/java/boofcv/alg/misc/ImageStatistics.java#L971-L977
train
lessthanoptimal/BoofCV
main/boofcv-ip/src/main/java/boofcv/alg/misc/ImageStatistics.java
ImageStatistics.maxAbs
public static float maxAbs( InterleavedF32 input ) { if( BoofConcurrency.USE_CONCURRENT ) { return ImplImageStatistics_MT.maxAbs(input.data, input.startIndex, input.height, input.width*input.numBands , input.stride); } else { return ImplImageStatistics.maxAbs(input.data, input.startIndex, input.height, input....
java
public static float maxAbs( InterleavedF32 input ) { if( BoofConcurrency.USE_CONCURRENT ) { return ImplImageStatistics_MT.maxAbs(input.data, input.startIndex, input.height, input.width*input.numBands , input.stride); } else { return ImplImageStatistics.maxAbs(input.data, input.startIndex, input.height, input....
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Returns the maximum element value. @param input Input image. Not modified. @return Maximum pixel value.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-ip/src/main/java/boofcv/alg/misc/ImageStatistics.java#L1503-L1509
train
lessthanoptimal/BoofCV
main/boofcv-feature/src/main/java/boofcv/alg/feature/detect/line/ConnectLinesGrid.java
ConnectLinesGrid.connectToNeighbors
private void connectToNeighbors(int x, int y ) { List<LineSegment2D_F32> lines = grid.get(x,y); Iterator<LineSegment2D_F32> iter = lines.iterator(); while( iter.hasNext() ) { LineSegment2D_F32 l = iter.next(); boolean connected = false; if( connectTry(l,x+1,y) ) connected = true; if( !connecte...
java
private void connectToNeighbors(int x, int y ) { List<LineSegment2D_F32> lines = grid.get(x,y); Iterator<LineSegment2D_F32> iter = lines.iterator(); while( iter.hasNext() ) { LineSegment2D_F32 l = iter.next(); boolean connected = false; if( connectTry(l,x+1,y) ) connected = true; if( !connecte...
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Connect lines in the target region to lines in neighboring regions. Regions are selected such that no two regions are compared against each other more than once. @param x target region grid x-coordinate @param y target region grid y-coordinate
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-feature/src/main/java/boofcv/alg/feature/detect/line/ConnectLinesGrid.java#L113-L136
train
lessthanoptimal/BoofCV
main/boofcv-feature/src/main/java/boofcv/alg/feature/detect/line/ConnectLinesGrid.java
ConnectLinesGrid.connectTry
private boolean connectTry( LineSegment2D_F32 target , int x , int y ) { if( !grid.isInBounds(x,y) ) return false; List<LineSegment2D_F32> lines = grid.get(x,y); int index = findBestCompatible(target,lines,0); if( index == -1 ) return false; LineSegment2D_F32 b = lines.remove(index); // join the ...
java
private boolean connectTry( LineSegment2D_F32 target , int x , int y ) { if( !grid.isInBounds(x,y) ) return false; List<LineSegment2D_F32> lines = grid.get(x,y); int index = findBestCompatible(target,lines,0); if( index == -1 ) return false; LineSegment2D_F32 b = lines.remove(index); // join the ...
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See if there is a line that matches in this adjacent region. @param target Line being connected. @param x x-coordinate of adjacent region. @param y y-coordinate of adjacent region. @return true if a connection was made.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-feature/src/main/java/boofcv/alg/feature/detect/line/ConnectLinesGrid.java#L146-L171
train
lessthanoptimal/BoofCV
main/boofcv-feature/src/main/java/boofcv/alg/feature/detect/line/ConnectLinesGrid.java
ConnectLinesGrid.connectInSameElement
private void connectInSameElement(List<LineSegment2D_F32> lines ) { for( int i = 0; i < lines.size(); i++ ) { LineSegment2D_F32 a = lines.get(i); int index = findBestCompatible(a,lines,i+1); if( index == -1 ) continue; // remove the line from the index which it is being connected to LineSegment2D...
java
private void connectInSameElement(List<LineSegment2D_F32> lines ) { for( int i = 0; i < lines.size(); i++ ) { LineSegment2D_F32 a = lines.get(i); int index = findBestCompatible(a,lines,i+1); if( index == -1 ) continue; // remove the line from the index which it is being connected to LineSegment2D...
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Search for lines in the same region for it to be connected to. @param lines All the lines in the region.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-feature/src/main/java/boofcv/alg/feature/detect/line/ConnectLinesGrid.java#L178-L196
train
lessthanoptimal/BoofCV
main/boofcv-feature/src/main/java/boofcv/alg/feature/detect/line/ConnectLinesGrid.java
ConnectLinesGrid.findBestCompatible
private int findBestCompatible( LineSegment2D_F32 target , List<LineSegment2D_F32> candidates , int start ) { int bestIndex = -1; double bestDistance = Double.MAX_VALUE; int bestFarthest = 0; float targetAngle = UtilAngle.atanSafe(target.slopeY(),target.slopeX()); float cos = (float)Math.c...
java
private int findBestCompatible( LineSegment2D_F32 target , List<LineSegment2D_F32> candidates , int start ) { int bestIndex = -1; double bestDistance = Double.MAX_VALUE; int bestFarthest = 0; float targetAngle = UtilAngle.atanSafe(target.slopeY(),target.slopeX()); float cos = (float)Math.c...
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Searches for a line in the list which the target is compatible with and can be connected to. @param target Line being connected to. @param candidates List of candidate lines. @param start First index in the candidate list it should start searching at. @return Index of the candidate it can connect to. -1 if there is n...
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-feature/src/main/java/boofcv/alg/feature/detect/line/ConnectLinesGrid.java#L207-L263
train
lessthanoptimal/BoofCV
main/boofcv-feature/src/main/java/boofcv/alg/feature/detect/line/ConnectLinesGrid.java
ConnectLinesGrid.closestFarthestPoints
private void closestFarthestPoints(LineSegment2D_F32 a, LineSegment2D_F32 b) { dist[0] = a.a.distance2(b.a); dist[1] = a.a.distance2(b.b); dist[2] = a.b.distance2(b.a); dist[3] = a.b.distance2(b.b); // find the two points which are closest together and save which ones those are // for future reference f...
java
private void closestFarthestPoints(LineSegment2D_F32 a, LineSegment2D_F32 b) { dist[0] = a.a.distance2(b.a); dist[1] = a.a.distance2(b.b); dist[2] = a.b.distance2(b.a); dist[3] = a.b.distance2(b.b); // find the two points which are closest together and save which ones those are // for future reference f...
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Finds the points on each line which are closest and farthest away from each other.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-feature/src/main/java/boofcv/alg/feature/detect/line/ConnectLinesGrid.java#L268-L291
train
lessthanoptimal/BoofCV
main/boofcv-recognition/src/main/java/boofcv/abst/fiducial/CalibrationFiducialDetector.java
CalibrationFiducialDetector.selectBoundaryCorners
protected void selectBoundaryCorners() { List<Point2D_F64> layout = detector.getLayout(); Polygon2D_F64 hull = new Polygon2D_F64(); UtilPolygons2D_F64.convexHull(layout,hull); UtilPolygons2D_F64.removeAlmostParallel(hull,0.02); boundaryIndexes = new int[hull.size()]; for (int i = 0; i < hull.size(); i++) ...
java
protected void selectBoundaryCorners() { List<Point2D_F64> layout = detector.getLayout(); Polygon2D_F64 hull = new Polygon2D_F64(); UtilPolygons2D_F64.convexHull(layout,hull); UtilPolygons2D_F64.removeAlmostParallel(hull,0.02); boundaryIndexes = new int[hull.size()]; for (int i = 0; i < hull.size(); i++) ...
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Selects points which will be the corners in the boundary. Finds the convex hull.
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f01c0243da0ec086285ee722183804d5923bc3ac
https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/abst/fiducial/CalibrationFiducialDetector.java#L203-L225
train