id int32 0 165k | repo stringlengths 7 58 | path stringlengths 12 218 | func_name stringlengths 3 140 | original_string stringlengths 73 34.1k | language stringclasses 1
value | code stringlengths 73 34.1k | code_tokens list | docstring stringlengths 3 16k | docstring_tokens list | sha stringlengths 40 40 | url stringlengths 105 339 |
|---|---|---|---|---|---|---|---|---|---|---|---|
50,500 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/shapes/edge/EdgeIntensityPolygon.java | EdgeIntensityPolygon.checkIntensity | public boolean checkIntensity( boolean insideDark , double threshold ) {
if( insideDark )
return averageOutside-averageInside >= threshold;
else
return averageInside-averageOutside >= threshold;
} | java | public boolean checkIntensity( boolean insideDark , double threshold ) {
if( insideDark )
return averageOutside-averageInside >= threshold;
else
return averageInside-averageOutside >= threshold;
} | [
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dark: outside-inside ≥ threshold
light: inside-outside ≥ threshold
@param insideDark is the inside of the polygon supposed to be dark or light?
@param threshold threshold for average difference
@return true if the edge intensity is significant enough | [
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50,501 | lessthanoptimal/BoofCV | main/boofcv-calibration/src/main/java/boofcv/alg/geo/selfcalib/SelfCalibrationGuessAndCheckFocus.java | SelfCalibrationGuessAndCheckFocus.setCamera | public void setCamera( double skew , double cx , double cy , int width , int height ) {
// Define normalization matrix
// center points, remove skew, scale coordinates
double d = Math.sqrt(width*width + height*height);
V.zero();
V.set(0,0,d/2); V.set(0,1,skew); V.set(0,2,cx);
V.set(1,1,d/2); V.set(1,2,cy);... | java | public void setCamera( double skew , double cx , double cy , int width , int height ) {
// Define normalization matrix
// center points, remove skew, scale coordinates
double d = Math.sqrt(width*width + height*height);
V.zero();
V.set(0,0,d/2); V.set(0,1,skew); V.set(0,2,cx);
V.set(1,1,d/2); V.set(1,2,cy);... | [
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"... | Specifies known portions of camera intrinsic parameters
@param skew skew
@param cx image center x
@param cy image center y
@param width Image width
@param height Image height | [
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50,502 | lessthanoptimal/BoofCV | main/boofcv-calibration/src/main/java/boofcv/alg/geo/selfcalib/SelfCalibrationGuessAndCheckFocus.java | SelfCalibrationGuessAndCheckFocus.setSampling | public void setSampling( double min , double max , int total ) {
this.sampleMin = min;
this.sampleMax = max;
this.numSamples = total;
this.scores = new double[numSamples];
} | java | public void setSampling( double min , double max , int total ) {
this.sampleMin = min;
this.sampleMax = max;
this.numSamples = total;
this.scores = new double[numSamples];
} | [
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@param min min value. 0.3 is default
@param max max value. 3.0 is default
@param total Number of sample points. 50 is default | [
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50,503 | lessthanoptimal/BoofCV | main/boofcv-calibration/src/main/java/boofcv/alg/geo/selfcalib/SelfCalibrationGuessAndCheckFocus.java | SelfCalibrationGuessAndCheckFocus.computeRectifyH | boolean computeRectifyH( double f1 , double f2 , DMatrixRMaj P2, DMatrixRMaj H ) {
estimatePlaneInf.setCamera1(f1,f1,0,0,0);
estimatePlaneInf.setCamera2(f2,f2,0,0,0);
if( !estimatePlaneInf.estimatePlaneAtInfinity(P2,planeInf) )
return false;
// TODO add a cost for distance from nominal and scale other cos... | java | boolean computeRectifyH( double f1 , double f2 , DMatrixRMaj P2, DMatrixRMaj H ) {
estimatePlaneInf.setCamera1(f1,f1,0,0,0);
estimatePlaneInf.setCamera2(f2,f2,0,0,0);
if( !estimatePlaneInf.estimatePlaneAtInfinity(P2,planeInf) )
return false;
// TODO add a cost for distance from nominal and scale other cos... | [
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@param f1 view 1 focal length
@param f2 view 2 focal length
@param P2 projective camera matrix for view 2
@param H (Output) homography
@return true if successful | [
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50,504 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/circle/EllipseClustersIntoGrid.java | EllipseClustersIntoGrid.findLine | protected static List<NodeInfo> findLine(NodeInfo seed, NodeInfo next, int clusterSize, List<NodeInfo> line, boolean ccw ) {
if( next == null )
return null;
if( line == null )
line = new ArrayList<>();
else
line.clear();
next.marked = true;
double anglePrev = direction(next, seed);
double prevDis... | java | protected static List<NodeInfo> findLine(NodeInfo seed, NodeInfo next, int clusterSize, List<NodeInfo> line, boolean ccw ) {
if( next == null )
return null;
if( line == null )
line = new ArrayList<>();
else
line.clear();
next.marked = true;
double anglePrev = direction(next, seed);
double prevDis... | [
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"... | Finds all the nodes which form an approximate line
@param seed First ellipse
@param next Second ellipse, specified direction of line relative to seed
@param line
@return All the nodes along the line | [
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50,505 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/circle/EllipseClustersIntoGrid.java | EllipseClustersIntoGrid.findClosestEdge | protected static NodeInfo findClosestEdge( NodeInfo n , Point2D_F64 p ) {
double bestDistance = Double.MAX_VALUE;
NodeInfo best = null;
for (int i = 0; i < n.edges.size(); i++) {
Edge e = n.edges.get(i);
if( e.target.marked )
continue;
double d = e.target.ellipse.center.distance2(p);
if( d < bes... | java | protected static NodeInfo findClosestEdge( NodeInfo n , Point2D_F64 p ) {
double bestDistance = Double.MAX_VALUE;
NodeInfo best = null;
for (int i = 0; i < n.edges.size(); i++) {
Edge e = n.edges.get(i);
if( e.target.marked )
continue;
double d = e.target.ellipse.center.distance2(p);
if( d < bes... | [
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50,506 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/circle/EllipseClustersIntoGrid.java | EllipseClustersIntoGrid.checkDuplicates | boolean checkDuplicates(List<List<NodeInfo>> grid ) {
for (int i = 0; i < listInfo.size; i++) {
listInfo.get(i).marked = false;
}
for (int i = 0; i < grid.size(); i++) {
List<NodeInfo> list = grid.get(i);
for (int j = 0; j < list.size(); j++) {
NodeInfo n = list.get(j);
if( n.marked )
retu... | java | boolean checkDuplicates(List<List<NodeInfo>> grid ) {
for (int i = 0; i < listInfo.size; i++) {
listInfo.get(i).marked = false;
}
for (int i = 0; i < grid.size(); i++) {
List<NodeInfo> list = grid.get(i);
for (int j = 0; j < list.size(); j++) {
NodeInfo n = list.get(j);
if( n.marked )
retu... | [
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50,507 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/circle/EllipseClustersIntoGrid.java | EllipseClustersIntoGrid.addEdgesToInfo | void addEdgesToInfo(List<Node> cluster) {
for (int i = 0; i < cluster.size(); i++) {
Node n = cluster.get(i);
NodeInfo infoA = listInfo.get(i);
EllipseRotated_F64 a = infoA.ellipse;
// create the edges and order them based on their direction
for (int j = 0; j < n.connections.size(); j++) {
NodeInf... | java | void addEdgesToInfo(List<Node> cluster) {
for (int i = 0; i < cluster.size(); i++) {
Node n = cluster.get(i);
NodeInfo infoA = listInfo.get(i);
EllipseRotated_F64 a = infoA.ellipse;
// create the edges and order them based on their direction
for (int j = 0; j < n.connections.size(); j++) {
NodeInf... | [
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50,508 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/circle/EllipseClustersIntoGrid.java | EllipseClustersIntoGrid.pruneNearlyIdenticalAngles | void pruneNearlyIdenticalAngles() {
for (int i = 0; i < listInfo.size(); i++) {
NodeInfo infoN = listInfo.get(i);
for (int j = 0; j < infoN.edges.size(); ) {
int k = (j+1)%infoN.edges.size;
double angularDiff = UtilAngle.dist(infoN.edges.get(j).angle,infoN.edges.get(k).angle);
if( angularDiff < Ut... | java | void pruneNearlyIdenticalAngles() {
for (int i = 0; i < listInfo.size(); i++) {
NodeInfo infoN = listInfo.get(i);
for (int j = 0; j < infoN.edges.size(); ) {
int k = (j+1)%infoN.edges.size;
double angularDiff = UtilAngle.dist(infoN.edges.get(j).angle,infoN.edges.get(k).angle);
if( angularDiff < Ut... | [
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50,509 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/circle/EllipseClustersIntoGrid.java | EllipseClustersIntoGrid.findLargestAnglesForAllNodes | void findLargestAnglesForAllNodes() {
for (int i = 0; i < listInfo.size(); i++) {
NodeInfo info = listInfo.get(i);
if( info.edges.size < 2 )
continue;
for (int k = 0, j = info.edges.size-1; k < info.edges.size; j=k,k++) {
double angleA = info.edges.get(j).angle;
double angleB = info.edges.get(k... | java | void findLargestAnglesForAllNodes() {
for (int i = 0; i < listInfo.size(); i++) {
NodeInfo info = listInfo.get(i);
if( info.edges.size < 2 )
continue;
for (int k = 0, j = info.edges.size-1; k < info.edges.size; j=k,k++) {
double angleA = info.edges.get(j).angle;
double angleB = info.edges.get(k... | [
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50,510 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/circle/EllipseClustersIntoGrid.java | EllipseClustersIntoGrid.findContour | boolean findContour( boolean mustHaveInner ) {
// find the node with the largest angleBetween
NodeInfo seed = listInfo.get(0);
for (int i = 1; i < listInfo.size(); i++) {
NodeInfo info = listInfo.get(i);
if( info.angleBetween > seed.angleBetween ) {
seed = info;
}
}
// trace around the contour
... | java | boolean findContour( boolean mustHaveInner ) {
// find the node with the largest angleBetween
NodeInfo seed = listInfo.get(0);
for (int i = 1; i < listInfo.size(); i++) {
NodeInfo info = listInfo.get(i);
if( info.angleBetween > seed.angleBetween ) {
seed = info;
}
}
// trace around the contour
... | [
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50,511 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/circle/EllipseClustersIntoGrid.java | EllipseClustersIntoGrid.indexOf | public static int indexOf(List<Node> list , int value ) {
for (int i = 0; i < list.size(); i++) {
if( list.get(i).which == value )
return i;
}
return -1;
} | java | public static int indexOf(List<Node> list , int value ) {
for (int i = 0; i < list.size(); i++) {
if( list.get(i).which == value )
return i;
}
return -1;
} | [
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50,512 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/circle/EllipseClustersIntoGrid.java | EllipseClustersIntoGrid.selectSeedCorner | NodeInfo selectSeedCorner() {
NodeInfo best = null;
double bestAngle = 0;
for (int i = 0; i < contour.size; i++) {
NodeInfo info = contour.get(i);
if( info.angleBetween > bestAngle ) {
bestAngle = info.angleBetween;
best = info;
}
}
best.marked = true;
return best;
} | java | NodeInfo selectSeedCorner() {
NodeInfo best = null;
double bestAngle = 0;
for (int i = 0; i < contour.size; i++) {
NodeInfo info = contour.get(i);
if( info.angleBetween > bestAngle ) {
bestAngle = info.angleBetween;
best = info;
}
}
best.marked = true;
return best;
} | [
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50,513 | lessthanoptimal/BoofCV | main/boofcv-sfm/src/main/java/boofcv/alg/depth/VisualDepthOps.java | VisualDepthOps.depthTo3D | public static void depthTo3D(CameraPinholeBrown param , GrayU16 depth , FastQueue<Point3D_F64> cloud ) {
cloud.reset();
Point2Transform2_F64 p2n = LensDistortionFactory.narrow(param).undistort_F64(true,false);
Point2D_F64 n = new Point2D_F64();
for( int y = 0; y < depth.height; y++ ) {
int index = depth.s... | java | public static void depthTo3D(CameraPinholeBrown param , GrayU16 depth , FastQueue<Point3D_F64> cloud ) {
cloud.reset();
Point2Transform2_F64 p2n = LensDistortionFactory.narrow(param).undistort_F64(true,false);
Point2D_F64 n = new Point2D_F64();
for( int y = 0; y < depth.height; y++ ) {
int index = depth.s... | [
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50,514 | lessthanoptimal/BoofCV | main/boofcv-sfm/src/main/java/boofcv/alg/depth/VisualDepthOps.java | VisualDepthOps.depthTo3D | public static void depthTo3D(CameraPinholeBrown param , Planar<GrayU8> rgb , GrayU16 depth ,
FastQueue<Point3D_F64> cloud , FastQueueArray_I32 cloudColor ) {
cloud.reset();
cloudColor.reset();
RemoveBrownPtoN_F64 p2n = new RemoveBrownPtoN_F64();
p2n.setK(param.fx,param.fy,param.skew,param.cx,param.cy)... | java | public static void depthTo3D(CameraPinholeBrown param , Planar<GrayU8> rgb , GrayU16 depth ,
FastQueue<Point3D_F64> cloud , FastQueueArray_I32 cloudColor ) {
cloud.reset();
cloudColor.reset();
RemoveBrownPtoN_F64 p2n = new RemoveBrownPtoN_F64();
p2n.setK(param.fx,param.fy,param.skew,param.cx,param.cy)... | [
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@param param Intrinsic camera parameters for depth image
@param depth depth image. each value is in millimeters.
@param rgb Color image that's aligned to the depth.
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50,515 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/shapes/polyline/MinimizeEnergyPrune.java | MinimizeEnergyPrune.prune | public boolean prune(List<Point2D_I32> contour, GrowQueue_I32 input, GrowQueue_I32 output) {
this.contour = contour;
output.setTo(input);
removeDuplicates(output);
// can't prune a corner and it will still be a polygon
if( output.size() <= 3 )
return false;
computeSegmentEnergy(output);
double tota... | java | public boolean prune(List<Point2D_I32> contour, GrowQueue_I32 input, GrowQueue_I32 output) {
this.contour = contour;
output.setTo(input);
removeDuplicates(output);
// can't prune a corner and it will still be a polygon
if( output.size() <= 3 )
return false;
computeSegmentEnergy(output);
double tota... | [
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@param input Initial set of corners
@param output Pruned set of corners
@return true if one or more corners were pruned, false if nothing changed | [
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50,516 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/shapes/polyline/MinimizeEnergyPrune.java | MinimizeEnergyPrune.removeDuplicates | void removeDuplicates( GrowQueue_I32 corners ) {
// remove duplicates
for (int i = 0; i < corners.size(); i++) {
Point2D_I32 a = contour.get(corners.get(i));
// start from the top so that removing a corner doesn't mess with the for loop
for (int j = corners.size()-1; j > i; j--) {
Point2D_I32 b = cont... | java | void removeDuplicates( GrowQueue_I32 corners ) {
// remove duplicates
for (int i = 0; i < corners.size(); i++) {
Point2D_I32 a = contour.get(corners.get(i));
// start from the top so that removing a corner doesn't mess with the for loop
for (int j = corners.size()-1; j > i; j--) {
Point2D_I32 b = cont... | [
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50,517 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/shapes/polyline/MinimizeEnergyPrune.java | MinimizeEnergyPrune.computeSegmentEnergy | void computeSegmentEnergy( GrowQueue_I32 corners ) {
if( energySegment.length < corners.size() ) {
energySegment = new double[ corners.size() ];
}
for (int i = 0,j=corners.size()-1; i < corners.size(); j=i,i++) {
energySegment[j] = computeSegmentEnergy(corners, j, i);
}
} | java | void computeSegmentEnergy( GrowQueue_I32 corners ) {
if( energySegment.length < corners.size() ) {
energySegment = new double[ corners.size() ];
}
for (int i = 0,j=corners.size()-1; i < corners.size(); j=i,i++) {
energySegment[j] = computeSegmentEnergy(corners, j, i);
}
} | [
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50,518 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/shapes/polyline/MinimizeEnergyPrune.java | MinimizeEnergyPrune.energyRemoveCorner | protected double energyRemoveCorner( int removed , GrowQueue_I32 corners ) {
double total = 0;
int cornerA = CircularIndex.addOffset(removed, -1 , corners.size());
int cornerB = CircularIndex.addOffset(removed, 1 , corners.size());
total += computeSegmentEnergy(corners, cornerA, cornerB);
if( cornerA > co... | java | protected double energyRemoveCorner( int removed , GrowQueue_I32 corners ) {
double total = 0;
int cornerA = CircularIndex.addOffset(removed, -1 , corners.size());
int cornerB = CircularIndex.addOffset(removed, 1 , corners.size());
total += computeSegmentEnergy(corners, cornerA, cornerB);
if( cornerA > co... | [
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50,519 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/shapes/polyline/MinimizeEnergyPrune.java | MinimizeEnergyPrune.computeSegmentEnergy | protected double computeSegmentEnergy(GrowQueue_I32 corners, int cornerA, int cornerB) {
int indexA = corners.get(cornerA);
int indexB = corners.get(cornerB);
if( indexA == indexB ) {
return 100000.0;
}
Point2D_I32 a = contour.get(indexA);
Point2D_I32 b = contour.get(indexB);
line.p.x = a.x;
line.... | java | protected double computeSegmentEnergy(GrowQueue_I32 corners, int cornerA, int cornerB) {
int indexA = corners.get(cornerA);
int indexB = corners.get(cornerB);
if( indexA == indexB ) {
return 100000.0;
}
Point2D_I32 a = contour.get(indexA);
Point2D_I32 b = contour.get(indexB);
line.p.x = a.x;
line.... | [
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50,520 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/segmentation/ms/MergeSmallRegions.java | MergeSmallRegions.process | public void process( T image,
GrayS32 pixelToRegion ,
GrowQueue_I32 regionMemberCount,
FastQueue<float[]> regionColor ) {
stopRequested = false;
// iterate until no more regions need to be merged together
while( !stopRequested ) {
// Update the color of each region
regionColor.resize(... | java | public void process( T image,
GrayS32 pixelToRegion ,
GrowQueue_I32 regionMemberCount,
FastQueue<float[]> regionColor ) {
stopRequested = false;
// iterate until no more regions need to be merged together
while( !stopRequested ) {
// Update the color of each region
regionColor.resize(... | [
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@param pixelToRegion (input/output) Segmented image with the ID of each region. Modified.
@param regionMemberCount (input/output) Number of members ... | [
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50,521 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/segmentation/ms/MergeSmallRegions.java | MergeSmallRegions.setupPruneList | protected boolean setupPruneList(GrowQueue_I32 regionMemberCount) {
segmentPruneFlag.resize(regionMemberCount.size);
pruneGraph.reset();
segmentToPruneID.resize(regionMemberCount.size);
for( int i = 0; i < regionMemberCount.size; i++ ) {
if( regionMemberCount.get(i) < minimumSize ) {
segmentToPruneID.set... | java | protected boolean setupPruneList(GrowQueue_I32 regionMemberCount) {
segmentPruneFlag.resize(regionMemberCount.size);
pruneGraph.reset();
segmentToPruneID.resize(regionMemberCount.size);
for( int i = 0; i < regionMemberCount.size; i++ ) {
if( regionMemberCount.get(i) < minimumSize ) {
segmentToPruneID.set... | [
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50,522 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/segmentation/ms/MergeSmallRegions.java | MergeSmallRegions.findAdjacentRegions | protected void findAdjacentRegions(GrayS32 pixelToRegion) {
// -------- Do the inner pixels first
if( connect.length == 4 )
adjacentInner4(pixelToRegion);
else if( connect.length == 8 ) {
adjacentInner8(pixelToRegion);
}
adjacentBorder(pixelToRegion);
} | java | protected void findAdjacentRegions(GrayS32 pixelToRegion) {
// -------- Do the inner pixels first
if( connect.length == 4 )
adjacentInner4(pixelToRegion);
else if( connect.length == 8 ) {
adjacentInner8(pixelToRegion);
}
adjacentBorder(pixelToRegion);
} | [
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50,523 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/segmentation/ms/MergeSmallRegions.java | MergeSmallRegions.selectMerge | protected void selectMerge( int pruneId , FastQueue<float[]> regionColor ) {
// Grab information on the region which is being pruned
Node n = pruneGraph.get(pruneId);
float[] targetColor = regionColor.get(n.segment);
// segment ID and distance away from the most similar neighbor
int bestId = -1;
float best... | java | protected void selectMerge( int pruneId , FastQueue<float[]> regionColor ) {
// Grab information on the region which is being pruned
Node n = pruneGraph.get(pruneId);
float[] targetColor = regionColor.get(n.segment);
// segment ID and distance away from the most similar neighbor
int bestId = -1;
float best... | [
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50,524 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/feature/detect/interest/EasyGeneralFeatureDetector.java | EasyGeneralFeatureDetector.declareDerivativeImages | private void declareDerivativeImages(ImageGradient<T, D> gradient, ImageHessian<D> hessian, Class<D> derivType) {
if( gradient != null || hessian != null ) {
derivX = GeneralizedImageOps.createSingleBand(derivType, 1, 1);
derivY = GeneralizedImageOps.createSingleBand(derivType,1,1);
}
if( hessian != null ) ... | java | private void declareDerivativeImages(ImageGradient<T, D> gradient, ImageHessian<D> hessian, Class<D> derivType) {
if( gradient != null || hessian != null ) {
derivX = GeneralizedImageOps.createSingleBand(derivType, 1, 1);
derivY = GeneralizedImageOps.createSingleBand(derivType,1,1);
}
if( hessian != null ) ... | [
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50,525 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/feature/detect/interest/EasyGeneralFeatureDetector.java | EasyGeneralFeatureDetector.detect | public void detect(T input, QueueCorner exclude ) {
initializeDerivatives(input);
if (detector.getRequiresGradient() || detector.getRequiresHessian())
gradient.process(input, derivX, derivY);
if (detector.getRequiresHessian())
hessian.process(derivX, derivY, derivXX, derivYY, derivXY);
detector.setExcl... | java | public void detect(T input, QueueCorner exclude ) {
initializeDerivatives(input);
if (detector.getRequiresGradient() || detector.getRequiresHessian())
gradient.process(input, derivX, derivY);
if (detector.getRequiresHessian())
hessian.process(derivX, derivY, derivXX, derivYY, derivXY);
detector.setExcl... | [
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50,526 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/feature/detect/interest/EasyGeneralFeatureDetector.java | EasyGeneralFeatureDetector.initializeDerivatives | private void initializeDerivatives(T input) {
// reshape derivatives if the input image has changed size
if (detector.getRequiresGradient() || detector.getRequiresHessian()) {
derivX.reshape(input.width, input.height);
derivY.reshape(input.width, input.height);
}
if (detector.getRequiresHessian()) {
de... | java | private void initializeDerivatives(T input) {
// reshape derivatives if the input image has changed size
if (detector.getRequiresGradient() || detector.getRequiresHessian()) {
derivX.reshape(input.width, input.height);
derivY.reshape(input.width, input.height);
}
if (detector.getRequiresHessian()) {
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50,527 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/squares/SquareGridTools.java | SquareGridTools.checkFlip | public boolean checkFlip( SquareGrid grid ) {
if( grid.columns == 1 || grid.rows == 1 )
return false;
Point2D_F64 a = grid.get(0,0).center;
Point2D_F64 b = grid.get(0,grid.columns-1).center;
Point2D_F64 c = grid.get(grid.rows-1,0).center;
double x0 = b.x-a.x;
double y0 = b.y-a.y;
double x1 = c.x-a.x... | java | public boolean checkFlip( SquareGrid grid ) {
if( grid.columns == 1 || grid.rows == 1 )
return false;
Point2D_F64 a = grid.get(0,0).center;
Point2D_F64 b = grid.get(0,grid.columns-1).center;
Point2D_F64 c = grid.get(grid.rows-1,0).center;
double x0 = b.x-a.x;
double y0 = b.y-a.y;
double x1 = c.x-a.x... | [
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50,528 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/squares/SquareGridTools.java | SquareGridTools.orderNodeGrid | protected void orderNodeGrid(SquareGrid grid, int row, int col) {
SquareNode node = grid.get(row,col);
if(grid.rows==1 && grid.columns==1 ) {
for (int i = 0; i < 4; i++) {
ordered[i] = node.square.get(i);
}
} else if( grid.columns==1 ) {
if (row == grid.rows - 1) {
orderNode(node, grid.get(row -... | java | protected void orderNodeGrid(SquareGrid grid, int row, int col) {
SquareNode node = grid.get(row,col);
if(grid.rows==1 && grid.columns==1 ) {
for (int i = 0; i < 4; i++) {
ordered[i] = node.square.get(i);
}
} else if( grid.columns==1 ) {
if (row == grid.rows - 1) {
orderNode(node, grid.get(row -... | [
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50,529 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/squares/SquareGridTools.java | SquareGridTools.rotateTwiceOrdered | private void rotateTwiceOrdered() {
Point2D_F64 a = ordered[0];
Point2D_F64 b = ordered[1];
Point2D_F64 c = ordered[2];
Point2D_F64 d = ordered[3];
ordered[0] = c;
ordered[1] = d;
ordered[2] = a;
ordered[3] = b;
} | java | private void rotateTwiceOrdered() {
Point2D_F64 a = ordered[0];
Point2D_F64 b = ordered[1];
Point2D_F64 c = ordered[2];
Point2D_F64 d = ordered[3];
ordered[0] = c;
ordered[1] = d;
ordered[2] = a;
ordered[3] = b;
} | [
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50,530 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/squares/SquareGridTools.java | SquareGridTools.orderNode | protected void orderNode(SquareNode target, SquareNode node, boolean pointingX) {
int index0 = findIntersection(target,node);
int index1 = (index0+1)%4;
int index2 = (index0+2)%4;
int index3 = (index0+3)%4;
if( index0 < 0 )
throw new RuntimeException("Couldn't find intersection. Probable bug");
line... | java | protected void orderNode(SquareNode target, SquareNode node, boolean pointingX) {
int index0 = findIntersection(target,node);
int index1 = (index0+1)%4;
int index2 = (index0+2)%4;
int index3 = (index0+3)%4;
if( index0 < 0 )
throw new RuntimeException("Couldn't find intersection. Probable bug");
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50,531 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/squares/SquareGridTools.java | SquareGridTools.findIntersection | protected int findIntersection( SquareNode target , SquareNode node ) {
lineCenters.a = target.center;
lineCenters.b = node.center;
for (int i = 0; i < 4; i++) {
int j = (i+1)%4;
lineSide.a = target.square.get(i);
lineSide.b = target.square.get(j);
if(Intersection2D_F64.intersection(lineCenters,lin... | java | protected int findIntersection( SquareNode target , SquareNode node ) {
lineCenters.a = target.center;
lineCenters.b = node.center;
for (int i = 0; i < 4; i++) {
int j = (i+1)%4;
lineSide.a = target.square.get(i);
lineSide.b = target.square.get(j);
if(Intersection2D_F64.intersection(lineCenters,lin... | [
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50,532 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/squares/SquareGridTools.java | SquareGridTools.orderSquareCorners | public boolean orderSquareCorners( SquareGrid grid ) {
// the first pass interleaves every other row
for (int row = 0; row < grid.rows; row++) {
for (int col = 0; col < grid.columns; col++) {
orderNodeGrid(grid, row, col);
Polygon2D_F64 square = grid.get(row,col).square;
for (int i = 0; i < 4; i++... | java | public boolean orderSquareCorners( SquareGrid grid ) {
// the first pass interleaves every other row
for (int row = 0; row < grid.rows; row++) {
for (int col = 0; col < grid.columns; col++) {
orderNodeGrid(grid, row, col);
Polygon2D_F64 square = grid.get(row,col).square;
for (int i = 0; i < 4; i++... | [
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50,533 | lessthanoptimal/BoofCV | examples/src/main/java/boofcv/examples/features/ExampleTemplateMatching.java | ExampleTemplateMatching.findMatches | private static List<Match> findMatches(GrayF32 image, GrayF32 template, GrayF32 mask,
int expectedMatches) {
// create template matcher.
TemplateMatching<GrayF32> matcher =
FactoryTemplateMatching.createMatcher(TemplateScoreType.SUM_DIFF_SQ, GrayF32.class);
// Find the points which match the tem... | java | private static List<Match> findMatches(GrayF32 image, GrayF32 template, GrayF32 mask,
int expectedMatches) {
// create template matcher.
TemplateMatching<GrayF32> matcher =
FactoryTemplateMatching.createMatcher(TemplateScoreType.SUM_DIFF_SQ, GrayF32.class);
// Find the points which match the tem... | [
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50,534 | lessthanoptimal/BoofCV | examples/src/main/java/boofcv/examples/features/ExampleTemplateMatching.java | ExampleTemplateMatching.showMatchIntensity | public static void showMatchIntensity(GrayF32 image, GrayF32 template, GrayF32 mask) {
// create algorithm for computing intensity image
TemplateMatchingIntensity<GrayF32> matchIntensity =
FactoryTemplateMatching.createIntensity(TemplateScoreType.SUM_DIFF_SQ, GrayF32.class);
// apply the template to the ima... | java | public static void showMatchIntensity(GrayF32 image, GrayF32 template, GrayF32 mask) {
// create algorithm for computing intensity image
TemplateMatchingIntensity<GrayF32> matchIntensity =
FactoryTemplateMatching.createIntensity(TemplateScoreType.SUM_DIFF_SQ, GrayF32.class);
// apply the template to the ima... | [
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50,535 | lessthanoptimal/BoofCV | examples/src/main/java/boofcv/examples/features/ExampleTemplateMatching.java | ExampleTemplateMatching.drawRectangles | private static void drawRectangles(Graphics2D g2,
GrayF32 image, GrayF32 template, GrayF32 mask,
int expectedMatches) {
List<Match> found = findMatches(image, template, mask, expectedMatches);
int r = 2;
int w = template.width + 2 * r;
int h = template.height + 2 * r;
for (Match m : ... | java | private static void drawRectangles(Graphics2D g2,
GrayF32 image, GrayF32 template, GrayF32 mask,
int expectedMatches) {
List<Match> found = findMatches(image, template, mask, expectedMatches);
int r = 2;
int w = template.width + 2 * r;
int h = template.height + 2 * r;
for (Match m : ... | [
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50,536 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/abst/fiducial/SquareBase_to_FiducialDetector.java | SquareBase_to_FiducialDetector.getCenter | @Override
public void getCenter(int which, Point2D_F64 location) {
Quadrilateral_F64 q = alg.getFound().get(which).distortedPixels;
// compute intersection in undistorted pixels so that the intersection is the true
// geometric center of the square. Since distorted pixels are being used this will only be approx... | java | @Override
public void getCenter(int which, Point2D_F64 location) {
Quadrilateral_F64 q = alg.getFound().get(which).distortedPixels;
// compute intersection in undistorted pixels so that the intersection is the true
// geometric center of the square. Since distorted pixels are being used this will only be approx... | [
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] | f01c0243da0ec086285ee722183804d5923bc3ac | https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/abst/fiducial/SquareBase_to_FiducialDetector.java#L91-L101 |
50,537 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/squares/SquareEdge.java | SquareEdge.destination | public <T extends SquareNode>T destination(SquareNode src) {
if( a == src )
return (T)b;
else if( b == src )
return (T)a;
else
throw new IllegalArgumentException("BUG! src is not a or b");
} | java | public <T extends SquareNode>T destination(SquareNode src) {
if( a == src )
return (T)b;
else if( b == src )
return (T)a;
else
throw new IllegalArgumentException("BUG! src is not a or b");
} | [
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50,538 | lessthanoptimal/BoofCV | examples/src/main/java/boofcv/examples/sfm/ExampleVisualOdometryDepth.java | ExampleVisualOdometryDepth.inlierPercent | public static String inlierPercent(VisualOdometry alg) {
if( !(alg instanceof AccessPointTracks3D))
return "";
AccessPointTracks3D access = (AccessPointTracks3D)alg;
int count = 0;
int N = access.getAllTracks().size();
for( int i = 0; i < N; i++ ) {
if( access.isInlier(i) )
count++;
}
return ... | java | public static String inlierPercent(VisualOdometry alg) {
if( !(alg instanceof AccessPointTracks3D))
return "";
AccessPointTracks3D access = (AccessPointTracks3D)alg;
int count = 0;
int N = access.getAllTracks().size();
for( int i = 0; i < N; i++ ) {
if( access.isInlier(i) )
count++;
}
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50,539 | lessthanoptimal/BoofCV | examples/src/main/java/boofcv/examples/features/ExampleFitPolygon.java | ExampleFitPolygon.fitBinaryImage | public static void fitBinaryImage(GrayF32 input) {
GrayU8 binary = new GrayU8(input.width,input.height);
BufferedImage polygon = new BufferedImage(input.width,input.height,BufferedImage.TYPE_INT_RGB);
// the mean pixel value is often a reasonable threshold when creating a binary image
double mean = ImageStati... | java | public static void fitBinaryImage(GrayF32 input) {
GrayU8 binary = new GrayU8(input.width,input.height);
BufferedImage polygon = new BufferedImage(input.width,input.height,BufferedImage.TYPE_INT_RGB);
// the mean pixel value is often a reasonable threshold when creating a binary image
double mean = ImageStati... | [
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50,540 | lessthanoptimal/BoofCV | examples/src/main/java/boofcv/examples/features/ExampleFitPolygon.java | ExampleFitPolygon.fitCannyEdges | public static void fitCannyEdges( GrayF32 input ) {
BufferedImage displayImage = new BufferedImage(input.width,input.height,BufferedImage.TYPE_INT_RGB);
// Finds edges inside the image
CannyEdge<GrayF32,GrayF32> canny =
FactoryEdgeDetectors.canny(2, true, true, GrayF32.class, GrayF32.class);
canny.proces... | java | public static void fitCannyEdges( GrayF32 input ) {
BufferedImage displayImage = new BufferedImage(input.width,input.height,BufferedImage.TYPE_INT_RGB);
// Finds edges inside the image
CannyEdge<GrayF32,GrayF32> canny =
FactoryEdgeDetectors.canny(2, true, true, GrayF32.class, GrayF32.class);
canny.proces... | [
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50,541 | lessthanoptimal/BoofCV | examples/src/main/java/boofcv/examples/features/ExampleFitPolygon.java | ExampleFitPolygon.fitCannyBinary | public static void fitCannyBinary( GrayF32 input ) {
BufferedImage displayImage = new BufferedImage(input.width,input.height,BufferedImage.TYPE_INT_RGB);
GrayU8 binary = new GrayU8(input.width,input.height);
// Finds edges inside the image
CannyEdge<GrayF32,GrayF32> canny =
FactoryEdgeDetectors.canny(2, f... | java | public static void fitCannyBinary( GrayF32 input ) {
BufferedImage displayImage = new BufferedImage(input.width,input.height,BufferedImage.TYPE_INT_RGB);
GrayU8 binary = new GrayU8(input.width,input.height);
// Finds edges inside the image
CannyEdge<GrayF32,GrayF32> canny =
FactoryEdgeDetectors.canny(2, f... | [
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50,542 | lessthanoptimal/BoofCV | main/boofcv-learning/src/main/java/boofcv/alg/bow/LearnSceneFromFiles.java | LearnSceneFromFiles.evaluate | protected Confusion evaluate( Map<String,List<String>> set ) {
ClassificationHistogram histogram = new ClassificationHistogram(scenes.size());
int total = 0;
for (int i = 0; i < scenes.size(); i++) {
total += set.get(scenes.get(i)).size();
}
System.out.println("total images "+total);
for (int i = 0; i ... | java | protected Confusion evaluate( Map<String,List<String>> set ) {
ClassificationHistogram histogram = new ClassificationHistogram(scenes.size());
int total = 0;
for (int i = 0; i < scenes.size(); i++) {
total += set.get(scenes.get(i)).size();
}
System.out.println("total images "+total);
for (int i = 0; i ... | [
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50,543 | lessthanoptimal/BoofCV | main/boofcv-learning/src/main/java/boofcv/alg/bow/LearnSceneFromFiles.java | LearnSceneFromFiles.findImages | public static Map<String,List<String>> findImages( File rootDir ) {
File files[] = rootDir.listFiles();
if( files == null )
return null;
List<File> imageDirectories = new ArrayList<>();
for( File f : files ) {
if( f.isDirectory() ) {
imageDirectories.add(f);
}
}
Map<String,List<String>> out = ... | java | public static Map<String,List<String>> findImages( File rootDir ) {
File files[] = rootDir.listFiles();
if( files == null )
return null;
List<File> imageDirectories = new ArrayList<>();
for( File f : files ) {
if( f.isDirectory() ) {
imageDirectories.add(f);
}
}
Map<String,List<String>> out = ... | [
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50,544 | lessthanoptimal/BoofCV | integration/boofcv-swing/src/main/java/boofcv/gui/feature/CompareTwoImagePanel.java | CompareTwoImagePanel.setImages | public synchronized void setImages(BufferedImage leftImage , BufferedImage rightImage ) {
this.leftImage = leftImage;
this.rightImage = rightImage;
setPreferredSize(leftImage.getWidth(),leftImage.getHeight(),rightImage.getWidth(),rightImage.getHeight());
} | java | public synchronized void setImages(BufferedImage leftImage , BufferedImage rightImage ) {
this.leftImage = leftImage;
this.rightImage = rightImage;
setPreferredSize(leftImage.getWidth(),leftImage.getHeight(),rightImage.getWidth(),rightImage.getHeight());
} | [
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50,545 | lessthanoptimal/BoofCV | integration/boofcv-swing/src/main/java/boofcv/gui/feature/CompareTwoImagePanel.java | CompareTwoImagePanel.computeScales | private void computeScales() {
int width = getWidth();
int height = getHeight();
width = (width-borderSize)/2;
// compute the scale factor for each image
scaleLeft = scaleRight = 1;
if( leftImage.getWidth() > width || leftImage.getHeight() > height ) {
double scaleX = (double)width/(double)leftImage.ge... | java | private void computeScales() {
int width = getWidth();
int height = getHeight();
width = (width-borderSize)/2;
// compute the scale factor for each image
scaleLeft = scaleRight = 1;
if( leftImage.getWidth() > width || leftImage.getHeight() > height ) {
double scaleX = (double)width/(double)leftImage.ge... | [
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50,546 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/deepboof/DataManipulationOps.java | DataManipulationOps.normalize | public static void normalize(GrayF32 image , float mean , float stdev ) {
for (int y = 0; y < image.height; y++) {
int index = image.startIndex + y*image.stride;
int end = index + image.width;
while( index < end ) {
image.data[index] = (image.data[index]-mean)/stdev;
index++;
}
}
} | java | public static void normalize(GrayF32 image , float mean , float stdev ) {
for (int y = 0; y < image.height; y++) {
int index = image.startIndex + y*image.stride;
int end = index + image.width;
while( index < end ) {
image.data[index] = (image.data[index]-mean)/stdev;
index++;
}
}
} | [
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50,547 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/deepboof/DataManipulationOps.java | DataManipulationOps.create1D_F32 | public static Kernel1D_F32 create1D_F32( double[] kernel ) {
Kernel1D_F32 k = new Kernel1D_F32(kernel.length,kernel.length/2);
for (int i = 0; i < kernel.length; i++) {
k.data[i] = (float)kernel[i];
}
return k;
} | java | public static Kernel1D_F32 create1D_F32( double[] kernel ) {
Kernel1D_F32 k = new Kernel1D_F32(kernel.length,kernel.length/2);
for (int i = 0; i < kernel.length; i++) {
k.data[i] = (float)kernel[i];
}
return k;
} | [
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50,548 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/deepboof/DataManipulationOps.java | DataManipulationOps.imageToTensor | public static void imageToTensor(Planar<GrayF32> input , Tensor_F32 output , int miniBatch) {
if( input.isSubimage())
throw new RuntimeException("Subimages not accepted");
if( output.getDimension() != 4 )
throw new IllegalArgumentException("Output should be 4-DOF. batch + spatial (channel,height,width)");
... | java | public static void imageToTensor(Planar<GrayF32> input , Tensor_F32 output , int miniBatch) {
if( input.isSubimage())
throw new RuntimeException("Subimages not accepted");
if( output.getDimension() != 4 )
throw new IllegalArgumentException("Output should be 4-DOF. batch + spatial (channel,height,width)");
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50,549 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/alg/filter/binary/LinearExternalContours.java | LinearExternalContours.process | public void process( GrayU8 binary , int adjustX , int adjustY ) {
// Initialize data structures
this.adjustX = adjustX;
this.adjustY = adjustY;
storagePoints.reset();
ImageMiscOps.fillBorder(binary, 0, 1);
tracer.setInputs(binary);
final byte binaryData[] = binary.data;
// Scan through the image one ... | java | public void process( GrayU8 binary , int adjustX , int adjustY ) {
// Initialize data structures
this.adjustX = adjustX;
this.adjustY = adjustY;
storagePoints.reset();
ImageMiscOps.fillBorder(binary, 0, 1);
tracer.setInputs(binary);
final byte binaryData[] = binary.data;
// Scan through the image one ... | [
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50,550 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/alg/filter/binary/LinearExternalContours.java | LinearExternalContours.findNotZero | static int findNotZero( byte[] data , int index , int end ) {
while( index < end && data[index] == 0 ) {
index++;
}
return index;
} | java | static int findNotZero( byte[] data , int index , int end ) {
while( index < end && data[index] == 0 ) {
index++;
}
return index;
} | [
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50,551 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/alg/filter/binary/LinearExternalContours.java | LinearExternalContours.findZero | static int findZero( byte[] data , int index , int end ) {
while( index < end && data[index] != 0 ) {
index++;
}
return index;
} | java | static int findZero( byte[] data , int index , int end ) {
while( index < end && data[index] != 0 ) {
index++;
}
return index;
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50,552 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/abst/fiducial/SquareImage_to_FiducialDetector.java | SquareImage_to_FiducialDetector.addPatternImage | public void addPatternImage(T pattern, double threshold, double lengthSide) {
GrayU8 binary = new GrayU8(pattern.width,pattern.height);
GThresholdImageOps.threshold(pattern,binary,threshold,false);
alg.addPattern(binary, lengthSide);
} | java | public void addPatternImage(T pattern, double threshold, double lengthSide) {
GrayU8 binary = new GrayU8(pattern.width,pattern.height);
GThresholdImageOps.threshold(pattern,binary,threshold,false);
alg.addPattern(binary, lengthSide);
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50,553 | lessthanoptimal/BoofCV | integration/boofcv-android/examples/video/app/src/main/java/org/boofcv/video/MainActivity.java | MainActivity.requestCameraPermission | private void requestCameraPermission() {
int permissionCheck = ContextCompat.checkSelfPermission(this,
Manifest.permission.CAMERA);
if( permissionCheck != android.content.pm.PackageManager.PERMISSION_GRANTED) {
ActivityCompat.requestPermissions(this,
new String[]{Manifest.permission.CAMERA},
0);
... | java | private void requestCameraPermission() {
int permissionCheck = ContextCompat.checkSelfPermission(this,
Manifest.permission.CAMERA);
if( permissionCheck != android.content.pm.PackageManager.PERMISSION_GRANTED) {
ActivityCompat.requestPermissions(this,
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50,554 | lessthanoptimal/BoofCV | integration/boofcv-android/src/main/java/boofcv/android/ConvertBitmap.java | ConvertBitmap.bitmapToGray | public static <T extends ImageGray<T>>
T bitmapToGray( Bitmap input , T output , Class<T> imageType , byte[] storage) {
if( imageType == GrayF32.class )
return (T)bitmapToGray(input,(GrayF32)output,storage);
else if( imageType == GrayU8.class )
return (T)bitmapToGray(input,(GrayU8)output,storage);
else
... | java | public static <T extends ImageGray<T>>
T bitmapToGray( Bitmap input , T output , Class<T> imageType , byte[] storage) {
if( imageType == GrayF32.class )
return (T)bitmapToGray(input,(GrayF32)output,storage);
else if( imageType == GrayU8.class )
return (T)bitmapToGray(input,(GrayU8)output,storage);
else
... | [
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50,555 | lessthanoptimal/BoofCV | integration/boofcv-android/src/main/java/boofcv/android/ConvertBitmap.java | ConvertBitmap.bitmapToGray | public static GrayU8 bitmapToGray( Bitmap input , GrayU8 output , byte[] storage ) {
if( output == null ) {
output = new GrayU8( input.getWidth() , input.getHeight() );
} else {
output.reshape(input.getWidth(), input.getHeight());
}
if( storage == null )
storage = declareStorage(input,null);
inpu... | java | public static GrayU8 bitmapToGray( Bitmap input , GrayU8 output , byte[] storage ) {
if( output == null ) {
output = new GrayU8( input.getWidth() , input.getHeight() );
} else {
output.reshape(input.getWidth(), input.getHeight());
}
if( storage == null )
storage = declareStorage(input,null);
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50,556 | lessthanoptimal/BoofCV | integration/boofcv-android/src/main/java/boofcv/android/ConvertBitmap.java | ConvertBitmap.bitmapToPlanar | public static <T extends ImageGray<T>>
Planar<T> bitmapToPlanar(Bitmap input , Planar<T> output , Class<T> type , byte[] storage ) {
if( output == null ) {
output = new Planar<>(type, input.getWidth(), input.getHeight(), 3);
} else {
int numBands = Math.min(4,Math.max(3,output.getNumBands()));
output.resh... | java | public static <T extends ImageGray<T>>
Planar<T> bitmapToPlanar(Bitmap input , Planar<T> output , Class<T> type , byte[] storage ) {
if( output == null ) {
output = new Planar<>(type, input.getWidth(), input.getHeight(), 3);
} else {
int numBands = Math.min(4,Math.max(3,output.getNumBands()));
output.resh... | [
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50,557 | lessthanoptimal/BoofCV | integration/boofcv-android/src/main/java/boofcv/android/ConvertBitmap.java | ConvertBitmap.boofToBitmap | public static void boofToBitmap( ImageBase input , Bitmap output , byte[] storage) {
if( BOverrideConvertAndroid.invokeBoofToBitmap(ColorFormat.RGB,input,output,storage))
return;
if( input instanceof Planar ) {
planarToBitmap((Planar)input,output,storage);
} else if( input instanceof ImageGray ) {
grayT... | java | public static void boofToBitmap( ImageBase input , Bitmap output , byte[] storage) {
if( BOverrideConvertAndroid.invokeBoofToBitmap(ColorFormat.RGB,input,output,storage))
return;
if( input instanceof Planar ) {
planarToBitmap((Planar)input,output,storage);
} else if( input instanceof ImageGray ) {
grayT... | [
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50,558 | lessthanoptimal/BoofCV | integration/boofcv-android/src/main/java/boofcv/android/ConvertBitmap.java | ConvertBitmap.planarToBitmap | public static <T extends ImageGray<T>>
void planarToBitmap(Planar<T> input , Bitmap output , byte[] storage ) {
if( output.getWidth() != input.getWidth() || output.getHeight() != input.getHeight() ) {
throw new IllegalArgumentException("Image shapes are not the same");
}
if( storage == null )
storage = ... | java | public static <T extends ImageGray<T>>
void planarToBitmap(Planar<T> input , Bitmap output , byte[] storage ) {
if( output.getWidth() != input.getWidth() || output.getHeight() != input.getHeight() ) {
throw new IllegalArgumentException("Image shapes are not the same");
}
if( storage == null )
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50,559 | lessthanoptimal/BoofCV | integration/boofcv-android/src/main/java/boofcv/android/ConvertBitmap.java | ConvertBitmap.grayToBitmap | public static Bitmap grayToBitmap( GrayU8 input , Bitmap.Config config ) {
Bitmap output = Bitmap.createBitmap(input.width, input.height, config);
grayToBitmap(input,output,null);
return output;
} | java | public static Bitmap grayToBitmap( GrayU8 input , Bitmap.Config config ) {
Bitmap output = Bitmap.createBitmap(input.width, input.height, config);
grayToBitmap(input,output,null);
return output;
} | [
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50,560 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/feature/associate/AssociateUniqueByScoreAlg.java | AssociateUniqueByScoreAlg.process | public void process( FastQueue<AssociatedIndex> matches , int numSource , int numDestination ) {
if( checkSource ) {
if( checkDestination ) {
processSource(matches, numSource, firstPass);
processDestination(firstPass,numDestination,pruned);
} else {
processSource(matches, numSource, pruned);
}
... | java | public void process( FastQueue<AssociatedIndex> matches , int numSource , int numDestination ) {
if( checkSource ) {
if( checkDestination ) {
processSource(matches, numSource, firstPass);
processDestination(firstPass,numDestination,pruned);
} else {
processSource(matches, numSource, pruned);
}
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50,561 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/feature/associate/AssociateUniqueByScoreAlg.java | AssociateUniqueByScoreAlg.processSource | private void processSource(FastQueue<AssociatedIndex> matches, int numSource,
FastQueue<AssociatedIndex> output ) {
//set up data structures
scores.resize(numSource);
solutions.resize(numSource);
for( int i =0; i < numSource; i++ ) {
solutions.data[i] = -1;
}
// select best matches
for( int ... | java | private void processSource(FastQueue<AssociatedIndex> matches, int numSource,
FastQueue<AssociatedIndex> output ) {
//set up data structures
scores.resize(numSource);
solutions.resize(numSource);
for( int i =0; i < numSource; i++ ) {
solutions.data[i] = -1;
}
// select best matches
for( int ... | [
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50,562 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/feature/associate/AssociateUniqueByScoreAlg.java | AssociateUniqueByScoreAlg.processDestination | private void processDestination(FastQueue<AssociatedIndex> matches, int numDestination,
FastQueue<AssociatedIndex> output ) {
//set up data structures
scores.resize(numDestination);
solutions.resize(numDestination);
for( int i =0; i < numDestination; i++ ) {
solutions.data[i] = -1;
}
// select ... | java | private void processDestination(FastQueue<AssociatedIndex> matches, int numDestination,
FastQueue<AssociatedIndex> output ) {
//set up data structures
scores.resize(numDestination);
solutions.resize(numDestination);
for( int i =0; i < numDestination; i++ ) {
solutions.data[i] = -1;
}
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50,563 | lessthanoptimal/BoofCV | integration/boofcv-swing/src/main/java/boofcv/gui/d3/PointCloudViewerPanelSwing.java | PointCloudViewerPanelSwing.applyFog | private int applyFog( int rgb , float fraction ) {
// avoid floating point math
int adjustment = (int)(1000*fraction);
int r = (rgb >> 16)&0xFF;
int g = (rgb >> 8)&0xFF;
int b = rgb & 0xFF;
r = (r * adjustment + ((backgroundColor>>16)&0xFF)*(1000-adjustment)) / 1000;
g = (g * adjustment + ((backgroundCo... | java | private int applyFog( int rgb , float fraction ) {
// avoid floating point math
int adjustment = (int)(1000*fraction);
int r = (rgb >> 16)&0xFF;
int g = (rgb >> 8)&0xFF;
int b = rgb & 0xFF;
r = (r * adjustment + ((backgroundColor>>16)&0xFF)*(1000-adjustment)) / 1000;
g = (g * adjustment + ((backgroundCo... | [
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... | Fades color into background as a function of distance | [
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] | f01c0243da0ec086285ee722183804d5923bc3ac | https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/integration/boofcv-swing/src/main/java/boofcv/gui/d3/PointCloudViewerPanelSwing.java#L246-L259 |
50,564 | lessthanoptimal/BoofCV | integration/boofcv-swing/src/main/java/boofcv/gui/d3/PointCloudViewerPanelSwing.java | PointCloudViewerPanelSwing.renderDot | private void renderDot( int cx , int cy , float Z , int rgb ) {
for (int i = -dotRadius; i <= dotRadius; i++) {
int y = cy+i;
if( y < 0 || y >= imageRgb.height )
continue;
for (int j = -dotRadius; j <= dotRadius; j++) {
int x = cx+j;
if( x < 0 || x >= imageRgb.width )
continue;
int pixe... | java | private void renderDot( int cx , int cy , float Z , int rgb ) {
for (int i = -dotRadius; i <= dotRadius; i++) {
int y = cy+i;
if( y < 0 || y >= imageRgb.height )
continue;
for (int j = -dotRadius; j <= dotRadius; j++) {
int x = cx+j;
if( x < 0 || x >= imageRgb.width )
continue;
int pixe... | [
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50,565 | lessthanoptimal/BoofCV | integration/boofcv-android/src/main/java/boofcv/android/camera/VideoRenderProcessing.java | VideoRenderProcessing.imageToOutput | protected void imageToOutput( double x , double y , Point2D_F64 pt ) {
pt.x = x/scale - tranX/scale;
pt.y = y/scale - tranY/scale;
} | java | protected void imageToOutput( double x , double y , Point2D_F64 pt ) {
pt.x = x/scale - tranX/scale;
pt.y = y/scale - tranY/scale;
} | [
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50,566 | lessthanoptimal/BoofCV | integration/boofcv-android/src/main/java/boofcv/android/camera/VideoRenderProcessing.java | VideoRenderProcessing.outputToImage | protected void outputToImage( double x , double y , Point2D_F64 pt ) {
pt.x = x*scale + tranX;
pt.y = y*scale + tranY;
} | java | protected void outputToImage( double x , double y , Point2D_F64 pt ) {
pt.x = x*scale + tranX;
pt.y = y*scale + tranY;
} | [
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50,567 | lessthanoptimal/BoofCV | integration/boofcv-jcodec/src/main/java/boofcv/io/jcodec/ImplConvertJCodecPicture.java | ImplConvertJCodecPicture.RGB_to_PLU8 | public static void RGB_to_PLU8(Picture input, Planar<GrayU8> output) {
if( input.getColor() != ColorSpace.RGB )
throw new RuntimeException("Unexpected input color space!");
if( output.getNumBands() != 3 )
throw new RuntimeException("Unexpected number of bands in output image!");
output.reshape(input.getWid... | java | public static void RGB_to_PLU8(Picture input, Planar<GrayU8> output) {
if( input.getColor() != ColorSpace.RGB )
throw new RuntimeException("Unexpected input color space!");
if( output.getNumBands() != 3 )
throw new RuntimeException("Unexpected number of bands in output image!");
output.reshape(input.getWid... | [
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50,568 | lessthanoptimal/BoofCV | main/boofcv-geo/src/main/java/boofcv/alg/geo/h/HomographyTotalLeastSquares.java | HomographyTotalLeastSquares.backsubstitution0134 | static void backsubstitution0134(DMatrixRMaj P_plus, DMatrixRMaj P , DMatrixRMaj X ,
double H[] ) {
final int N = P.numRows;
DMatrixRMaj tmp = new DMatrixRMaj(N*2, 1);
double H6 = H[6];
double H7 = H[7];
double H8 = H[8];
for (int i = 0, index = 0; i < N; i++) {
double x = -X.data[index],y = ... | java | static void backsubstitution0134(DMatrixRMaj P_plus, DMatrixRMaj P , DMatrixRMaj X ,
double H[] ) {
final int N = P.numRows;
DMatrixRMaj tmp = new DMatrixRMaj(N*2, 1);
double H6 = H[6];
double H7 = H[7];
double H8 = H[8];
for (int i = 0, index = 0; i < N; i++) {
double x = -X.data[index],y = ... | [
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50,569 | lessthanoptimal/BoofCV | main/boofcv-geo/src/main/java/boofcv/alg/geo/h/HomographyTotalLeastSquares.java | HomographyTotalLeastSquares.constructA678 | void constructA678() {
final int N = X1.numRows;
// Pseudo-inverse of hat(p)
computePseudo(X1,P_plus);
DMatrixRMaj PPpXP = new DMatrixRMaj(1,1);
DMatrixRMaj PPpYP = new DMatrixRMaj(1,1);
computePPXP(X1,P_plus,X2,0,PPpXP);
computePPXP(X1,P_plus,X2,1,PPpYP);
DMatrixRMaj PPpX = new DMatrixRMaj(1,1);
D... | java | void constructA678() {
final int N = X1.numRows;
// Pseudo-inverse of hat(p)
computePseudo(X1,P_plus);
DMatrixRMaj PPpXP = new DMatrixRMaj(1,1);
DMatrixRMaj PPpYP = new DMatrixRMaj(1,1);
computePPXP(X1,P_plus,X2,0,PPpXP);
computePPXP(X1,P_plus,X2,1,PPpYP);
DMatrixRMaj PPpX = new DMatrixRMaj(1,1);
D... | [
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50,570 | lessthanoptimal/BoofCV | main/boofcv-sfm/src/main/java/boofcv/alg/sfm/structure/MetricSceneGraph.java | MetricSceneGraph.sanityCheck | public void sanityCheck() {
for( View v : nodes ) {
for( Motion m : v.connections ) {
if( m.viewDst != v && m.viewSrc != v )
throw new RuntimeException("Not member of connection");
}
}
for( Motion m : edges ) {
if( m.viewDst != m.destination(m.viewSrc) )
throw new RuntimeException("Unexpecte... | java | public void sanityCheck() {
for( View v : nodes ) {
for( Motion m : v.connections ) {
if( m.viewDst != v && m.viewSrc != v )
throw new RuntimeException("Not member of connection");
}
}
for( Motion m : edges ) {
if( m.viewDst != m.destination(m.viewSrc) )
throw new RuntimeException("Unexpecte... | [
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50,571 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/tld/TldAdjustRegion.java | TldAdjustRegion.process | public boolean process( FastQueue<AssociatedPair> pairs , Rectangle2D_F64 targetRectangle ) {
// estimate how the rectangle has changed and update it
if( !estimateMotion.process(pairs.toList()) )
return false;
ScaleTranslate2D motion = estimateMotion.getModelParameters();
adjustRectangle(targetRectangle,mo... | java | public boolean process( FastQueue<AssociatedPair> pairs , Rectangle2D_F64 targetRectangle ) {
// estimate how the rectangle has changed and update it
if( !estimateMotion.process(pairs.toList()) )
return false;
ScaleTranslate2D motion = estimateMotion.getModelParameters();
adjustRectangle(targetRectangle,mo... | [
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@param pairs List of feature location in previous and current frame.
@param targetRectangle (Input) current location of rectangle. (output) adjusted location
@return true if successful | [
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] | f01c0243da0ec086285ee722183804d5923bc3ac | https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/tracker/tld/TldAdjustRegion.java#L72-L88 |
50,572 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/tld/TldAdjustRegion.java | TldAdjustRegion.adjustRectangle | protected void adjustRectangle( Rectangle2D_F64 rect , ScaleTranslate2D motion ) {
rect.p0.x = rect.p0.x*motion.scale + motion.transX;
rect.p0.y = rect.p0.y*motion.scale + motion.transY;
rect.p1.x = rect.p1.x*motion.scale + motion.transX;
rect.p1.y = rect.p1.y*motion.scale + motion.transY;
} | java | protected void adjustRectangle( Rectangle2D_F64 rect , ScaleTranslate2D motion ) {
rect.p0.x = rect.p0.x*motion.scale + motion.transX;
rect.p0.y = rect.p0.y*motion.scale + motion.transY;
rect.p1.x = rect.p1.x*motion.scale + motion.transX;
rect.p1.y = rect.p1.y*motion.scale + motion.transY;
} | [
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50,573 | lessthanoptimal/BoofCV | examples/src/main/java/boofcv/examples/features/ExampleAssociatePoints.java | ExampleAssociatePoints.associate | public void associate( BufferedImage imageA , BufferedImage imageB )
{
T inputA = ConvertBufferedImage.convertFromSingle(imageA, null, imageType);
T inputB = ConvertBufferedImage.convertFromSingle(imageB, null, imageType);
// stores the location of detected interest points
pointsA = new ArrayList<>();
point... | java | public void associate( BufferedImage imageA , BufferedImage imageB )
{
T inputA = ConvertBufferedImage.convertFromSingle(imageA, null, imageType);
T inputB = ConvertBufferedImage.convertFromSingle(imageB, null, imageType);
// stores the location of detected interest points
pointsA = new ArrayList<>();
point... | [
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50,574 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/abst/denoise/FactoryImageDenoise.java | FactoryImageDenoise.waveletVisu | public static <T extends ImageGray<T>> WaveletDenoiseFilter<T>
waveletVisu( Class<T> imageType , int numLevels , double minPixelValue , double maxPixelValue )
{
ImageDataType info = ImageDataType.classToType(imageType);
WaveletTransform descTran = createDefaultShrinkTransform(info, numLevels,minPixelValue,maxPixe... | java | public static <T extends ImageGray<T>> WaveletDenoiseFilter<T>
waveletVisu( Class<T> imageType , int numLevels , double minPixelValue , double maxPixelValue )
{
ImageDataType info = ImageDataType.classToType(imageType);
WaveletTransform descTran = createDefaultShrinkTransform(info, numLevels,minPixelValue,maxPixe... | [
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@param imageType The type of image being transform.
@param numLevels Number of levels in the wavelet transform. If not sure, try using 3.
@param minPixelValue Minimum allowed pixel intensity value
@param maxPixelValue Maximum allowed pixel intensity value
@return ... | [
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50,575 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/abst/denoise/FactoryImageDenoise.java | FactoryImageDenoise.waveletBayes | public static <T extends ImageGray<T>> WaveletDenoiseFilter<T>
waveletBayes( Class<T> imageType , int numLevels , double minPixelValue , double maxPixelValue )
{
ImageDataType info = ImageDataType.classToType(imageType);
WaveletTransform descTran = createDefaultShrinkTransform(info, numLevels,minPixelValue,maxPix... | java | public static <T extends ImageGray<T>> WaveletDenoiseFilter<T>
waveletBayes( Class<T> imageType , int numLevels , double minPixelValue , double maxPixelValue )
{
ImageDataType info = ImageDataType.classToType(imageType);
WaveletTransform descTran = createDefaultShrinkTransform(info, numLevels,minPixelValue,maxPix... | [
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@param minPixelValue Minimum allowed pixel intensity value
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50,576 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/abst/denoise/FactoryImageDenoise.java | FactoryImageDenoise.createDefaultShrinkTransform | private static WaveletTransform createDefaultShrinkTransform(ImageDataType imageType, int numLevels,
double minPixelValue , double maxPixelValue ) {
WaveletTransform descTran;
if( !imageType.isInteger()) {
WaveletDescription<WlCoef_F32> waveletDesc_F32 = FactoryWaveletDaub.daubJ_F32(4);
des... | java | private static WaveletTransform createDefaultShrinkTransform(ImageDataType imageType, int numLevels,
double minPixelValue , double maxPixelValue ) {
WaveletTransform descTran;
if( !imageType.isInteger()) {
WaveletDescription<WlCoef_F32> waveletDesc_F32 = FactoryWaveletDaub.daubJ_F32(4);
des... | [
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] | f01c0243da0ec086285ee722183804d5923bc3ac | https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-ip/src/main/java/boofcv/abst/denoise/FactoryImageDenoise.java#L106-L122 |
50,577 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/misc/CircularIndex.java | CircularIndex.minusPOffset | public static int minusPOffset(int index, int offset, int size) {
index -= offset;
if( index < 0 ) {
return size + index;
} else {
return index;
}
} | java | public static int minusPOffset(int index, int offset, int size) {
index -= offset;
if( index < 0 ) {
return size + index;
} else {
return index;
}
} | [
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50,578 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/misc/CircularIndex.java | CircularIndex.distanceP | public static int distanceP(int index0, int index1, int size) {
int difference = index1-index0;
if( difference < 0 ) {
difference = size+difference;
}
return difference;
} | java | public static int distanceP(int index0, int index1, int size) {
int difference = index1-index0;
if( difference < 0 ) {
difference = size+difference;
}
return difference;
} | [
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50,579 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/misc/CircularIndex.java | CircularIndex.subtract | public static int subtract(int index0, int index1, int size) {
int distance = distanceP(index0, index1, size);
if( distance >= size/2+size%2 ) {
return distance-size;
} else {
return distance;
}
} | java | public static int subtract(int index0, int index1, int size) {
int distance = distanceP(index0, index1, size);
if( distance >= size/2+size%2 ) {
return distance-size;
} else {
return distance;
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50,580 | lessthanoptimal/BoofCV | integration/boofcv-swing/src/main/java/boofcv/gui/StandardAlgConfigPanel.java | StandardAlgConfigPanel.removeChildInsidePanel | protected static void removeChildInsidePanel( JComponent root , JComponent target ) {
int N = root.getComponentCount();
for (int i = 0; i < N; i++) {
try {
JPanel p = (JPanel)root.getComponent(i);
Component[] children = p.getComponents();
for (int j = 0; j < children.length; j++) {
if( children... | java | protected static void removeChildInsidePanel( JComponent root , JComponent target ) {
int N = root.getComponentCount();
for (int i = 0; i < N; i++) {
try {
JPanel p = (JPanel)root.getComponent(i);
Component[] children = p.getComponents();
for (int j = 0; j < children.length; j++) {
if( children... | [
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50,581 | lessthanoptimal/BoofCV | integration/boofcv-swing/src/main/java/boofcv/gui/StandardAlgConfigPanel.java | StandardAlgConfigPanel.removeChildAndPrevious | protected static void removeChildAndPrevious( JComponent root , JComponent target ) {
int N = root.getComponentCount();
for (int i = 0; i < N; i++) {
if( root.getComponent(i) == target ) {
root.remove(i);
root.remove(i-1);
return;
}
}
throw new RuntimeException("Can't find component");
} | java | protected static void removeChildAndPrevious( JComponent root , JComponent target ) {
int N = root.getComponentCount();
for (int i = 0; i < N; i++) {
if( root.getComponent(i) == target ) {
root.remove(i);
root.remove(i-1);
return;
}
}
throw new RuntimeException("Can't find component");
} | [
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50,582 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/segmentation/ms/SegmentMeanShiftSearch.java | SegmentMeanShiftSearch.distanceSq | public static float distanceSq( float[] a , float[]b ) {
float ret = 0;
for( int i = 0; i < a.length; i++ ) {
float d = a[i] - b[i];
ret += d*d;
}
return ret;
} | java | public static float distanceSq( float[] a , float[]b ) {
float ret = 0;
for( int i = 0; i < a.length; i++ ) {
float d = a[i] - b[i];
ret += d*d;
}
return ret;
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50,583 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/segmentation/ms/SegmentMeanShiftSearch.java | SegmentMeanShiftSearch.weight | protected float weight( float distance ) {
float findex = distance*100f;
int index = (int)findex;
if( index >= 99 )
return weightTable[99];
float sample0 = weightTable[index];
float sample1 = weightTable[index+1];
float w = findex-index;
return sample0*(1f-w) + sample1*w;
} | java | protected float weight( float distance ) {
float findex = distance*100f;
int index = (int)findex;
if( index >= 99 )
return weightTable[99];
float sample0 = weightTable[index];
float sample1 = weightTable[index+1];
float w = findex-index;
return sample0*(1f-w) + sample1*w;
} | [
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50,584 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/scene/FeatureToWordHistogram_F64.java | FeatureToWordHistogram_F64.process | @Override
public void process() {
processed = true;
for (int i = 0; i < histogram.length; i++) {
histogram[i] /= total;
}
} | java | @Override
public void process() {
processed = true;
for (int i = 0; i < histogram.length; i++) {
histogram[i] /= total;
}
} | [
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50,585 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/feature/detect/line/HoughTransformLinePolar.java | HoughTransformLinePolar.transform | public void transform( GrayU8 binary )
{
ImageMiscOps.fill(transform, 0);
originX = binary.width/2;
originY = binary.height/2;
r_max = Math.sqrt(originX*originX+originY*originY);
for( int y = 0; y < binary.height; y++ ) {
int start = binary.startIndex + y*binary.stride;
int stop = start + binary.widt... | java | public void transform( GrayU8 binary )
{
ImageMiscOps.fill(transform, 0);
originX = binary.width/2;
originY = binary.height/2;
r_max = Math.sqrt(originX*originX+originY*originY);
for( int y = 0; y < binary.height; y++ ) {
int start = binary.startIndex + y*binary.stride;
int stop = start + binary.widt... | [
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50,586 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/feature/detect/line/HoughTransformLinePolar.java | HoughTransformLinePolar.lineToCoordinate | public void lineToCoordinate(LineParametric2D_F32 line , Point2D_F64 coordinate ) {
line = line.copy();
line.p.x -= originX;
line.p.y -= originY;
LinePolar2D_F32 polar = new LinePolar2D_F32();
UtilLine2D_F32.convert(line,polar);
if( polar.angle < 0 ) {
polar.distance = -polar.distance;
polar.angle = ... | java | public void lineToCoordinate(LineParametric2D_F32 line , Point2D_F64 coordinate ) {
line = line.copy();
line.p.x -= originX;
line.p.y -= originY;
LinePolar2D_F32 polar = new LinePolar2D_F32();
UtilLine2D_F32.convert(line,polar);
if( polar.angle < 0 ) {
polar.distance = -polar.distance;
polar.angle = ... | [
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50,587 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/feature/detect/line/HoughTransformLinePolar.java | HoughTransformLinePolar.parameterize | public void parameterize( int x , int y )
{
// put the point in a new coordinate system centered at the image's origin
x -= originX;
y -= originY;
int w2 = transform.width/2;
// The line's slope is encoded using the tangent angle. Those bins are along the image's y-axis
for( int i = 0; i < transform.hei... | java | public void parameterize( int x , int y )
{
// put the point in a new coordinate system centered at the image's origin
x -= originX;
y -= originY;
int w2 = transform.width/2;
// The line's slope is encoded using the tangent angle. Those bins are along the image's y-axis
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50,588 | lessthanoptimal/BoofCV | main/boofcv-geo/src/main/java/boofcv/struct/geo/PairLineNorm.java | PairLineNorm.set | public void set( Vector3D_F64 l1 , Vector3D_F64 l2 ) {
this.l1.set(l1);
this.l2.set(l2);
} | java | public void set( Vector3D_F64 l1 , Vector3D_F64 l2 ) {
this.l1.set(l1);
this.l2.set(l2);
} | [
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50,589 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/scene/ClassifierKNearestNeighborsBow.java | ClassifierKNearestNeighborsBow.setClassificationData | public void setClassificationData(List<HistogramScene> memory , int numScenes ) {
nn.setPoints(memory, false);
scenes = new double[ numScenes ];
} | java | public void setClassificationData(List<HistogramScene> memory , int numScenes ) {
nn.setPoints(memory, false);
scenes = new double[ numScenes ];
} | [
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50,590 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/scene/ClassifierKNearestNeighborsBow.java | ClassifierKNearestNeighborsBow.classify | public int classify(T image) {
if( numNeighbors == 0 )
throw new IllegalArgumentException("Must specify number of neighbors!");
// compute all the features inside the image
describe.process(image);
// find which word the feature matches and construct a frequency histogram
featureToHistogram.reset();
Li... | java | public int classify(T image) {
if( numNeighbors == 0 )
throw new IllegalArgumentException("Must specify number of neighbors!");
// compute all the features inside the image
describe.process(image);
// find which word the feature matches and construct a frequency histogram
featureToHistogram.reset();
Li... | [
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@param image Image that's to be classified
@return The index of the scene it most resembles | [
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] | f01c0243da0ec086285ee722183804d5923bc3ac | https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/scene/ClassifierKNearestNeighborsBow.java#L110-L154 |
50,591 | lessthanoptimal/BoofCV | examples/src/main/java/boofcv/examples/imageprocessing/ExamplePyramidDiscrete.java | ExamplePyramidDiscrete.unusual | public void unusual() {
// Note that the first level does not have to be one
pyramid = FactoryPyramid.discreteGaussian(new int[]{2,6},-1,2,true, ImageType.single(imageType));
// Other kernels can also be used besides Gaussian
Kernel1D kernel;
if(GeneralizedImageOps.isFloatingPoint(imageType) ) {
kernel = ... | java | public void unusual() {
// Note that the first level does not have to be one
pyramid = FactoryPyramid.discreteGaussian(new int[]{2,6},-1,2,true, ImageType.single(imageType));
// Other kernels can also be used besides Gaussian
Kernel1D kernel;
if(GeneralizedImageOps.isFloatingPoint(imageType) ) {
kernel = ... | [
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50,592 | lessthanoptimal/BoofCV | examples/src/main/java/boofcv/examples/imageprocessing/ExamplePyramidDiscrete.java | ExamplePyramidDiscrete.process | public void process( BufferedImage image ) {
T input = ConvertBufferedImage.convertFromSingle(image, null, imageType);
pyramid.process(input);
DiscretePyramidPanel gui = new DiscretePyramidPanel();
gui.setPyramid(pyramid);
gui.render();
ShowImages.showWindow(gui,"Image Pyramid");
// To get an image at ... | java | public void process( BufferedImage image ) {
T input = ConvertBufferedImage.convertFromSingle(image, null, imageType);
pyramid.process(input);
DiscretePyramidPanel gui = new DiscretePyramidPanel();
gui.setPyramid(pyramid);
gui.render();
ShowImages.showWindow(gui,"Image Pyramid");
// To get an image at ... | [
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50,593 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/factory/filter/derivative/FactoryDerivativeSparse.java | FactoryDerivativeSparse.createLaplacian | public static <T extends ImageGray<T>>
ImageFunctionSparse<T> createLaplacian( Class<T> imageType , ImageBorder<T> border )
{
if( border == null ) {
border = FactoryImageBorder.single(imageType, BorderType.EXTENDED);
}
if( GeneralizedImageOps.isFloatingPoint(imageType)) {
ImageConvolveSparse<GrayF32, Ker... | java | public static <T extends ImageGray<T>>
ImageFunctionSparse<T> createLaplacian( Class<T> imageType , ImageBorder<T> border )
{
if( border == null ) {
border = FactoryImageBorder.single(imageType, BorderType.EXTENDED);
}
if( GeneralizedImageOps.isFloatingPoint(imageType)) {
ImageConvolveSparse<GrayF32, Ker... | [
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@see DerivativeLaplacian
@param imageType The type of image which is to be processed.
@param border How the border should be handled. If null {@link BorderType#EXTENDED} will be used.
@return Filter for performing a sparse laplacian. | [
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] | f01c0243da0ec086285ee722183804d5923bc3ac | https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-ip/src/main/java/boofcv/factory/filter/derivative/FactoryDerivativeSparse.java#L58-L78 |
50,594 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/factory/filter/derivative/FactoryDerivativeSparse.java | FactoryDerivativeSparse.createSobel | public static <T extends ImageGray<T>, G extends GradientValue>
SparseImageGradient<T,G> createSobel( Class<T> imageType , ImageBorder<T> border )
{
if( imageType == GrayF32.class) {
return (SparseImageGradient)new GradientSparseSobel_F32((ImageBorder_F32)border);
} else if( imageType == GrayU8.class ){
ret... | java | public static <T extends ImageGray<T>, G extends GradientValue>
SparseImageGradient<T,G> createSobel( Class<T> imageType , ImageBorder<T> border )
{
if( imageType == GrayF32.class) {
return (SparseImageGradient)new GradientSparseSobel_F32((ImageBorder_F32)border);
} else if( imageType == GrayU8.class ){
ret... | [
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... | Creates a sparse sobel gradient operator.
@see GradientSobel
@param imageType The type of image which is to be processed.
@param border How the border should be handled. If null then the borders can't be processed.
@return Sparse gradient | [
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] | f01c0243da0ec086285ee722183804d5923bc3ac | https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-ip/src/main/java/boofcv/factory/filter/derivative/FactoryDerivativeSparse.java#L89-L99 |
50,595 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/factory/filter/derivative/FactoryDerivativeSparse.java | FactoryDerivativeSparse.createPrewitt | public static <T extends ImageGray<T>, G extends GradientValue>
SparseImageGradient<T,G> createPrewitt( Class<T> imageType , ImageBorder<T> border )
{
if( imageType == GrayF32.class) {
return (SparseImageGradient)new GradientSparsePrewitt_F32((ImageBorder_F32)border);
} else if( imageType == GrayU8.class ){
... | java | public static <T extends ImageGray<T>, G extends GradientValue>
SparseImageGradient<T,G> createPrewitt( Class<T> imageType , ImageBorder<T> border )
{
if( imageType == GrayF32.class) {
return (SparseImageGradient)new GradientSparsePrewitt_F32((ImageBorder_F32)border);
} else if( imageType == GrayU8.class ){
... | [
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... | Creates a sparse prewitt gradient operator.
@see boofcv.alg.filter.derivative.GradientPrewitt
@param imageType The type of image which is to be processed.
@param border How the border should be handled. If null then the borders can't be processed.
@return Sparse gradient. | [
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] | f01c0243da0ec086285ee722183804d5923bc3ac | https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-ip/src/main/java/boofcv/factory/filter/derivative/FactoryDerivativeSparse.java#L110-L120 |
50,596 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/factory/filter/derivative/FactoryDerivativeSparse.java | FactoryDerivativeSparse.createThree | public static <T extends ImageGray<T>, G extends GradientValue>
SparseImageGradient<T,G> createThree( Class<T> imageType , ImageBorder<T> border )
{
if( imageType == GrayF32.class) {
return (SparseImageGradient)new GradientSparseThree_F32((ImageBorder_F32)border);
} else if( imageType == GrayU8.class ){
ret... | java | public static <T extends ImageGray<T>, G extends GradientValue>
SparseImageGradient<T,G> createThree( Class<T> imageType , ImageBorder<T> border )
{
if( imageType == GrayF32.class) {
return (SparseImageGradient)new GradientSparseThree_F32((ImageBorder_F32)border);
} else if( imageType == GrayU8.class ){
ret... | [
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... | Creates a sparse three gradient operator.
@see boofcv.alg.filter.derivative.GradientThree
@param imageType The type of image which is to be processed.
@param border How the border should be handled. If null then the borders can't be processed.
@return Sparse gradient. | [
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] | f01c0243da0ec086285ee722183804d5923bc3ac | https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-ip/src/main/java/boofcv/factory/filter/derivative/FactoryDerivativeSparse.java#L131-L141 |
50,597 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/factory/filter/derivative/FactoryDerivativeSparse.java | FactoryDerivativeSparse.createTwo0 | public static <T extends ImageGray<T>, G extends GradientValue>
SparseImageGradient<T,G> createTwo0( Class<T> imageType , ImageBorder<T> border )
{
if( imageType == GrayF32.class) {
return (SparseImageGradient)new GradientSparseTwo0_F32((ImageBorder_F32)border);
} else if( imageType == GrayU8.class ){
retur... | java | public static <T extends ImageGray<T>, G extends GradientValue>
SparseImageGradient<T,G> createTwo0( Class<T> imageType , ImageBorder<T> border )
{
if( imageType == GrayF32.class) {
return (SparseImageGradient)new GradientSparseTwo0_F32((ImageBorder_F32)border);
} else if( imageType == GrayU8.class ){
retur... | [
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@see boofcv.alg.filter.derivative.GradientTwo0
@param imageType The type of image which is to be processed.
@param border How the border should be handled. If null then the borders can't be processed.
@return Sparse gradient. | [
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] | f01c0243da0ec086285ee722183804d5923bc3ac | https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-ip/src/main/java/boofcv/factory/filter/derivative/FactoryDerivativeSparse.java#L152-L162 |
50,598 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/factory/filter/derivative/FactoryDerivativeSparse.java | FactoryDerivativeSparse.createTwo1 | public static <T extends ImageGray<T>, G extends GradientValue>
SparseImageGradient<T,G> createTwo1( Class<T> imageType , ImageBorder<T> border )
{
if( imageType == GrayF32.class) {
return (SparseImageGradient)new GradientSparseTwo1_F32((ImageBorder_F32)border);
} else if( imageType == GrayU8.class ){
retur... | java | public static <T extends ImageGray<T>, G extends GradientValue>
SparseImageGradient<T,G> createTwo1( Class<T> imageType , ImageBorder<T> border )
{
if( imageType == GrayF32.class) {
return (SparseImageGradient)new GradientSparseTwo1_F32((ImageBorder_F32)border);
} else if( imageType == GrayU8.class ){
retur... | [
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@see boofcv.alg.filter.derivative.GradientTwo1
@param imageType The type of image which is to be processed.
@param border How the border should be handled. If null then the borders can't be processed.
@return Sparse gradient. | [
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] | f01c0243da0ec086285ee722183804d5923bc3ac | https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-ip/src/main/java/boofcv/factory/filter/derivative/FactoryDerivativeSparse.java#L173-L183 |
50,599 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/flow/DenseFlowPyramidBase.java | DenseFlowPyramidBase.process | public void process( T image1 , T image2 )
{
// declare image data structures
if( pyr1 == null || pyr1.getInputWidth() != image1.width || pyr1.getInputHeight() != image1.height ) {
pyr1 = UtilDenseOpticalFlow.standardPyramid(image1.width, image1.height, scale, sigma, 5, maxLayers, GrayF32.class);
pyr2 = Util... | java | public void process( T image1 , T image2 )
{
// declare image data structures
if( pyr1 == null || pyr1.getInputWidth() != image1.width || pyr1.getInputHeight() != image1.height ) {
pyr1 = UtilDenseOpticalFlow.standardPyramid(image1.width, image1.height, scale, sigma, 5, maxLayers, GrayF32.class);
pyr2 = Util... | [
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"getInputHeig... | Processes the raw input images. Normalizes them and creates image pyramids from them. | [
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] | f01c0243da0ec086285ee722183804d5923bc3ac | https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-feature/src/main/java/boofcv/alg/flow/DenseFlowPyramidBase.java#L67-L90 |
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