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value | code stringlengths 73 34.1k | code_tokens list | docstring stringlengths 3 16k | docstring_tokens list | sha stringlengths 40 40 | url stringlengths 105 339 | partition stringclasses 1
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lessthanoptimal/BoofCV | main/boofcv-geo/src/main/java/boofcv/alg/geo/bundle/jacobians/JacobianSo3Numerical.java | JacobianSo3Numerical.init | public void init() {
N = getParameterLength();
jacR = new DMatrixRMaj[N];
for (int i = 0; i < N; i++) {
jacR[i] = new DMatrixRMaj(3,3);
}
jacobian = new DMatrixRMaj(N,9);
paramInternal = new double[N];
numericalJac = createNumericalAlgorithm(function);
} | java | public void init() {
N = getParameterLength();
jacR = new DMatrixRMaj[N];
for (int i = 0; i < N; i++) {
jacR[i] = new DMatrixRMaj(3,3);
}
jacobian = new DMatrixRMaj(N,9);
paramInternal = new double[N];
numericalJac = createNumericalAlgorithm(function);
} | [
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lessthanoptimal/BoofCV | main/boofcv-geo/src/main/java/boofcv/abst/geo/bundle/SceneObservations.java | SceneObservations.checkOneObservationPerView | public void checkOneObservationPerView() {
for (int viewIdx = 0; viewIdx < views.length; viewIdx++) {
SceneObservations.View v = views[viewIdx];
for (int obsIdx = 0; obsIdx < v.size(); obsIdx++) {
int a = v.point.get(obsIdx);
for (int i = obsIdx+1; i < v.size(); i++) {
if( a == v.point.get(i)) {
... | java | public void checkOneObservationPerView() {
for (int viewIdx = 0; viewIdx < views.length; viewIdx++) {
SceneObservations.View v = views[viewIdx];
for (int obsIdx = 0; obsIdx < v.size(); obsIdx++) {
int a = v.point.get(obsIdx);
for (int i = obsIdx+1; i < v.size(); i++) {
if( a == v.point.get(i)) {
... | [
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lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/misc/ProfileOperation.java | ProfileOperation.profile | public static void profile( Performer performer , int num ) {
long deltaTime = measureTime(performer,num);
System.out.printf("%30s time = %8d ms per frame = %8.3f\n",
performer.getName(),deltaTime,(deltaTime/(double)num));
// System.out.println(performer.getClass().getSimpleName... | java | public static void profile( Performer performer , int num ) {
long deltaTime = measureTime(performer,num);
System.out.printf("%30s time = %8d ms per frame = %8.3f\n",
performer.getName(),deltaTime,(deltaTime/(double)num));
// System.out.println(performer.getClass().getSimpleName... | [
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/segmentation/fh04/SegmentFelzenszwalbHuttenlocher04.java | SegmentFelzenszwalbHuttenlocher04.initialize | protected void initialize(T input , GrayS32 output ) {
this.graph = output;
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regionSize.resize(N);
threshold.resize(N);
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regionSize.data[i] = 1;
threshold.data[i] = K;
graph.data[i] = i; // assign a unique label to each pixel since... | java | protected void initialize(T input , GrayS32 output ) {
this.graph = output;
final int N = input.width*input.height;
regionSize.resize(N);
threshold.resize(N);
for( int i = 0; i < N; i++ ) {
regionSize.data[i] = 1;
threshold.data[i] = K;
graph.data[i] = i; // assign a unique label to each pixel since... | [
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/segmentation/fh04/SegmentFelzenszwalbHuttenlocher04.java | SegmentFelzenszwalbHuttenlocher04.mergeSmallRegions | protected void mergeSmallRegions() {
for( int i = 0; i < edgesNotMatched.size(); i++ ) {
Edge e = edgesNotMatched.get(i);
int rootA = find(e.indexA);
int rootB = find(e.indexB);
// see if they are already part of the same segment
if( rootA == rootB )
continue;
int sizeA = regionSize.get(rootA... | java | protected void mergeSmallRegions() {
for( int i = 0; i < edgesNotMatched.size(); i++ ) {
Edge e = edgesNotMatched.get(i);
int rootA = find(e.indexA);
int rootB = find(e.indexB);
// see if they are already part of the same segment
if( rootA == rootB )
continue;
int sizeA = regionSize.get(rootA... | [
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/segmentation/fh04/SegmentFelzenszwalbHuttenlocher04.java | SegmentFelzenszwalbHuttenlocher04.find | protected int find( int child ) {
int root = graph.data[child];
if( root == graph.data[root] )
return root;
int inputChild = child;
while( root != child ) {
child = root;
root = graph.data[child];
}
graph.data[inputChild] = root;
return root;
} | java | protected int find( int child ) {
int root = graph.data[child];
if( root == graph.data[root] )
return root;
int inputChild = child;
while( root != child ) {
child = root;
root = graph.data[child];
}
graph.data[inputChild] = root;
return root;
} | [
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/segmentation/fh04/SegmentFelzenszwalbHuttenlocher04.java | SegmentFelzenszwalbHuttenlocher04.computeOutput | protected void computeOutput() {
outputRegionId.reset();
outputRegionSizes.reset();
for( int y = 0; y < graph.height; y++ ) {
int indexGraph = graph.startIndex + y*graph.stride;
for( int x = 0; x < graph.width; x++ , indexGraph++) {
int parent = graph.data[indexGraph];
if( parent == indexGraph ) {
... | java | protected void computeOutput() {
outputRegionId.reset();
outputRegionSizes.reset();
for( int y = 0; y < graph.height; y++ ) {
int indexGraph = graph.startIndex + y*graph.stride;
for( int x = 0; x < graph.width; x++ , indexGraph++) {
int parent = graph.data[indexGraph];
if( parent == indexGraph ) {
... | [
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lessthanoptimal/BoofCV | main/boofcv-geo/src/main/java/boofcv/alg/geo/NormalizationPoint2D.java | NormalizationPoint2D.apply | public void apply( DMatrixRMaj H , DMatrixRMaj output ) {
output.reshape(3,H.numCols);
int stride = H.numCols;
for (int col = 0; col < H.numCols; col++) {
// This column in H
double h1 = H.data[col], h2 = H.data[col+stride], h3 = H.data[col+2*stride];
output.data[col] = h1/stdX - meanX*h3/stdX;
outpu... | java | public void apply( DMatrixRMaj H , DMatrixRMaj output ) {
output.reshape(3,H.numCols);
int stride = H.numCols;
for (int col = 0; col < H.numCols; col++) {
// This column in H
double h1 = H.data[col], h2 = H.data[col+stride], h3 = H.data[col+2*stride];
output.data[col] = h1/stdX - meanX*h3/stdX;
outpu... | [
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lessthanoptimal/BoofCV | main/boofcv-geo/src/main/java/boofcv/alg/geo/NormalizationPoint2D.java | NormalizationPoint2D.apply | public void apply(DMatrix3x3 C, DMatrix3x3 output) {
DMatrix3x3 Hinv = matrixInv3(work);
PerspectiveOps.multTranA(Hinv,C,Hinv,output);
} | java | public void apply(DMatrix3x3 C, DMatrix3x3 output) {
DMatrix3x3 Hinv = matrixInv3(work);
PerspectiveOps.multTranA(Hinv,C,Hinv,output);
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lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/factory/transform/wavelet/FactoryWaveletHaar.java | FactoryWaveletHaar.generateInv_I32 | private static WlCoef_I32 generateInv_I32() {
WlCoef_I32 ret = new WlCoef_I32();
ret.scaling = new int[]{1,1};
ret.wavelet = new int[]{ret.scaling[0],-ret.scaling[0]};
ret.denominatorScaling = 2;
ret.denominatorWavelet = 2;
return ret;
} | java | private static WlCoef_I32 generateInv_I32() {
WlCoef_I32 ret = new WlCoef_I32();
ret.scaling = new int[]{1,1};
ret.wavelet = new int[]{ret.scaling[0],-ret.scaling[0]};
ret.denominatorScaling = 2;
ret.denominatorWavelet = 2;
return ret;
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/tracker/combined/CombinedTrackerScalePoint.java | CombinedTrackerScalePoint.updateTracks | public void updateTracks( I input ,
PyramidDiscrete<I> pyramid ,
D[] derivX,
D[] derivY ) {
// forget recently dropped or spawned tracks
tracksSpawned.clear();
// save references
this.input = input;
trackerKlt.setInputs(pyramid, derivX, derivY);
trackUsingKlt(tracksPureKlt);
... | java | public void updateTracks( I input ,
PyramidDiscrete<I> pyramid ,
D[] derivX,
D[] derivY ) {
// forget recently dropped or spawned tracks
tracksSpawned.clear();
// save references
this.input = input;
trackerKlt.setInputs(pyramid, derivX, derivY);
trackUsingKlt(tracksPureKlt);
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/tracker/combined/CombinedTrackerScalePoint.java | CombinedTrackerScalePoint.trackUsingKlt | private void trackUsingKlt(List<CombinedTrack<TD>> tracks) {
for( int i = 0; i < tracks.size(); ) {
CombinedTrack<TD> track = tracks.get(i);
if( !trackerKlt.performTracking(track.track) ) {
// handle the dropped track
tracks.remove(i);
tracksDormant.add(track);
} else {
track.set(track.trac... | java | private void trackUsingKlt(List<CombinedTrack<TD>> tracks) {
for( int i = 0; i < tracks.size(); ) {
CombinedTrack<TD> track = tracks.get(i);
if( !trackerKlt.performTracking(track.track) ) {
// handle the dropped track
tracks.remove(i);
tracksDormant.add(track);
} else {
track.set(track.trac... | [
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/tracker/combined/CombinedTrackerScalePoint.java | CombinedTrackerScalePoint.spawnTracksFromDetected | public void spawnTracksFromDetected() {
// mark detected features with no matches as available
FastQueue<AssociatedIndex> matches = associate.getMatches();
int N = detector.getNumberOfFeatures();
for( int i = 0; i < N; i++ )
associated[i] = false;
for( AssociatedIndex i : matches.toList() ) {
associat... | java | public void spawnTracksFromDetected() {
// mark detected features with no matches as available
FastQueue<AssociatedIndex> matches = associate.getMatches();
int N = detector.getNumberOfFeatures();
for( int i = 0; i < N; i++ )
associated[i] = false;
for( AssociatedIndex i : matches.toList() ) {
associat... | [
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/tracker/combined/CombinedTrackerScalePoint.java | CombinedTrackerScalePoint.associateToDetected | private void associateToDetected( List<CombinedTrack<TD>> known ) {
// initialize data structures
detectedDesc.reset();
knownDesc.reset();
// create a list of detected feature descriptions
int N = detector.getNumberOfFeatures();
for( int i = 0; i < N; i++ ) {
detectedDesc.add(detector.getDescription(i))... | java | private void associateToDetected( List<CombinedTrack<TD>> known ) {
// initialize data structures
detectedDesc.reset();
knownDesc.reset();
// create a list of detected feature descriptions
int N = detector.getNumberOfFeatures();
for( int i = 0; i < N; i++ ) {
detectedDesc.add(detector.getDescription(i))... | [
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/tracker/combined/CombinedTrackerScalePoint.java | CombinedTrackerScalePoint.associateAllToDetected | public void associateAllToDetected() {
// initialize data structures
List<CombinedTrack<TD>> all = new ArrayList<>();
all.addAll(tracksReactivated);
all.addAll(tracksDormant);
all.addAll(tracksPureKlt);
int numTainted = tracksReactivated.size() + tracksDormant.size();
tracksReactivated.clear();
tracks... | java | public void associateAllToDetected() {
// initialize data structures
List<CombinedTrack<TD>> all = new ArrayList<>();
all.addAll(tracksReactivated);
all.addAll(tracksDormant);
all.addAll(tracksPureKlt);
int numTainted = tracksReactivated.size() + tracksDormant.size();
tracksReactivated.clear();
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/tracker/combined/CombinedTrackerScalePoint.java | CombinedTrackerScalePoint.dropTrack | public boolean dropTrack( CombinedTrack<TD> track ) {
if( !tracksPureKlt.remove(track) )
if( !tracksReactivated.remove(track) )
if( !tracksDormant.remove(track) )
return false;
tracksUnused.add(track);
return true;
} | java | public boolean dropTrack( CombinedTrack<TD> track ) {
if( !tracksPureKlt.remove(track) )
if( !tracksReactivated.remove(track) )
if( !tracksDormant.remove(track) )
return false;
tracksUnused.add(track);
return true;
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/tracker/combined/CombinedTrackerScalePoint.java | CombinedTrackerScalePoint.dropAllTracks | public void dropAllTracks() {
tracksUnused.addAll(tracksDormant);
tracksUnused.addAll(tracksPureKlt);
tracksUnused.addAll(tracksReactivated);
tracksSpawned.clear();
tracksPureKlt.clear();
tracksReactivated.clear();
tracksSpawned.clear();
tracksDormant.clear();
} | java | public void dropAllTracks() {
tracksUnused.addAll(tracksDormant);
tracksUnused.addAll(tracksPureKlt);
tracksUnused.addAll(tracksReactivated);
tracksSpawned.clear();
tracksPureKlt.clear();
tracksReactivated.clear();
tracksSpawned.clear();
tracksDormant.clear();
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lessthanoptimal/BoofCV | demonstrations/src/main/java/boofcv/demonstrations/feature/associate/VisualizeAssociationScoreApp.java | VisualizeAssociationScoreApp.processImage | private void processImage() {
final List<Point2D_F64> leftPts = new ArrayList<>();
final List<Point2D_F64> rightPts = new ArrayList<>();
final List<TupleDesc> leftDesc = new ArrayList<>();
final List<TupleDesc> rightDesc = new ArrayList<>();
final ProgressMonitor progressMonitor = new ProgressMonitor(this,
... | java | private void processImage() {
final List<Point2D_F64> leftPts = new ArrayList<>();
final List<Point2D_F64> rightPts = new ArrayList<>();
final List<TupleDesc> leftDesc = new ArrayList<>();
final List<TupleDesc> rightDesc = new ArrayList<>();
final ProgressMonitor progressMonitor = new ProgressMonitor(this,
... | [
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lessthanoptimal/BoofCV | demonstrations/src/main/java/boofcv/demonstrations/feature/associate/VisualizeAssociationScoreApp.java | VisualizeAssociationScoreApp.extractImageFeatures | private void extractImageFeatures(final ProgressMonitor progressMonitor, final int progress,
T image,
List<TupleDesc> descs, List<Point2D_F64> locs) {
SwingUtilities.invokeLater(new Runnable() {
public void run() {
progressMonitor.setNote("Detecting");
}
});
detector.detect(image);... | java | private void extractImageFeatures(final ProgressMonitor progressMonitor, final int progress,
T image,
List<TupleDesc> descs, List<Point2D_F64> locs) {
SwingUtilities.invokeLater(new Runnable() {
public void run() {
progressMonitor.setNote("Detecting");
}
});
detector.detect(image);... | [
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/flow/BroxWarpingSpacial.java | BroxWarpingSpacial.resizeForLayer | protected void resizeForLayer( int width , int height ) {
deriv1X.reshape(width,height);
deriv1Y.reshape(width,height);
deriv2X.reshape(width,height);
deriv2Y.reshape(width,height);
deriv2XX.reshape(width,height);
deriv2YY.reshape(width,height);
deriv2XY.reshape(width,height);
warpImage2.reshape(width,... | java | protected void resizeForLayer( int width , int height ) {
deriv1X.reshape(width,height);
deriv1Y.reshape(width,height);
deriv2X.reshape(width,height);
deriv2Y.reshape(width,height);
deriv2XX.reshape(width,height);
deriv2YY.reshape(width,height);
deriv2XY.reshape(width,height);
warpImage2.reshape(width,... | [
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/flow/BroxWarpingSpacial.java | BroxWarpingSpacial.computePsiSmooth | private void computePsiSmooth(GrayF32 ux , GrayF32 uy , GrayF32 vx , GrayF32 vy ,
GrayF32 psiSmooth ) {
int N = derivFlowUX.width * derivFlowUX.height;
for( int i = 0; i < N; i++ ) {
float vux = ux.data[i];
float vuy = uy.data[i];
float vvx = vx.data[i];
float vvy = vy.data[i];
float mu =... | java | private void computePsiSmooth(GrayF32 ux , GrayF32 uy , GrayF32 vx , GrayF32 vy ,
GrayF32 psiSmooth ) {
int N = derivFlowUX.width * derivFlowUX.height;
for( int i = 0; i < N; i++ ) {
float vux = ux.data[i];
float vuy = uy.data[i];
float vvx = vx.data[i];
float vvy = vy.data[i];
float mu =... | [
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/flow/BroxWarpingSpacial.java | BroxWarpingSpacial.computePsiDataPsiGradient | protected void computePsiDataPsiGradient(GrayF32 image1, GrayF32 image2,
GrayF32 deriv1x, GrayF32 deriv1y,
GrayF32 deriv2x, GrayF32 deriv2y,
GrayF32 deriv2xx, GrayF32 deriv2yy, GrayF32 deriv2xy,
GrayF32 du, GrayF32 dv,
GrayF32 psiData, GrayF32 psiGradient ) {
... | java | protected void computePsiDataPsiGradient(GrayF32 image1, GrayF32 image2,
GrayF32 deriv1x, GrayF32 deriv1y,
GrayF32 deriv2x, GrayF32 deriv2y,
GrayF32 deriv2xx, GrayF32 deriv2yy, GrayF32 deriv2xy,
GrayF32 du, GrayF32 dv,
GrayF32 psiData, GrayF32 psiGradient ) {
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/flow/BroxWarpingSpacial.java | BroxWarpingSpacial.computeDivUVD | private void computeDivUVD(GrayF32 u , GrayF32 v , GrayF32 psi ,
GrayF32 divU , GrayF32 divV , GrayF32 divD ) {
final int stride = psi.stride;
// compute the inside pixel
for (int y = 1; y < psi.height-1; y++) {
// index of the current pixel
int index = y*stride + 1;
for (int x = 1; x < psi... | java | private void computeDivUVD(GrayF32 u , GrayF32 v , GrayF32 psi ,
GrayF32 divU , GrayF32 divV , GrayF32 divD ) {
final int stride = psi.stride;
// compute the inside pixel
for (int y = 1; y < psi.height-1; y++) {
// index of the current pixel
int index = y*stride + 1;
for (int x = 1; x < psi... | [
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/tld/TldTemplateMatching.java | TldTemplateMatching.reset | public void reset() {
unused.addAll(templateNegative);
unused.addAll(templatePositive);
templateNegative.clear();
templatePositive.clear();
} | java | public void reset() {
unused.addAll(templateNegative);
unused.addAll(templatePositive);
templateNegative.clear();
templatePositive.clear();
} | [
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/tld/TldTemplateMatching.java | TldTemplateMatching.addDescriptor | public void addDescriptor( boolean positive , ImageRectangle rect ) {
addDescriptor(positive, rect.x0, rect.y0, rect.x1, rect.y1);
} | java | public void addDescriptor( boolean positive , ImageRectangle rect ) {
addDescriptor(positive, rect.x0, rect.y0, rect.x1, rect.y1);
} | [
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/tld/TldTemplateMatching.java | TldTemplateMatching.addDescriptor | private void addDescriptor(boolean positive, NccFeature f) {
// avoid adding the same descriptor twice or adding contradicting results
if( positive)
if( distance(f,templatePositive) < 0.05 ) {
return;
}
if( !positive) {
if( distance(f,templateNegative) < 0.05 ) {
return;
}
// a positive pos... | java | private void addDescriptor(boolean positive, NccFeature f) {
// avoid adding the same descriptor twice or adding contradicting results
if( positive)
if( distance(f,templatePositive) < 0.05 ) {
return;
}
if( !positive) {
if( distance(f,templateNegative) < 0.05 ) {
return;
}
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/tld/TldTemplateMatching.java | TldTemplateMatching.computeNccDescriptor | public void computeNccDescriptor( NccFeature f , float x0 , float y0 , float x1 , float y1 ) {
double mean = 0;
float widthStep = (x1-x0)/15.0f;
float heightStep = (y1-y0)/15.0f;
// compute the mean value
int index = 0;
for( int y = 0; y < 15; y++ ) {
float sampleY = y0 + y*heightStep;
for( int x = 0... | java | public void computeNccDescriptor( NccFeature f , float x0 , float y0 , float x1 , float y1 ) {
double mean = 0;
float widthStep = (x1-x0)/15.0f;
float heightStep = (y1-y0)/15.0f;
// compute the mean value
int index = 0;
for( int y = 0; y < 15; y++ ) {
float sampleY = y0 + y*heightStep;
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/tld/TldTemplateMatching.java | TldTemplateMatching.createDescriptor | public NccFeature createDescriptor() {
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/tld/TldTemplateMatching.java | TldTemplateMatching.computeConfidence | public double computeConfidence( int x0 , int y0 , int x1 , int y1 ) {
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// distance from each set of templates
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double distancePositive = distance(observed,templatePositive);
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computeNccDescriptor(observed,x0,y0,x1,y1);
// distance from each set of templates
if( templateNegative.size() > 0 && templatePositive.size() > 0 ) {
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/tld/TldTemplateMatching.java | TldTemplateMatching.computeConfidence | public double computeConfidence( ImageRectangle r ) {
return computeConfidence(r.x0,r.y0,r.x1,r.y1);
} | java | public double computeConfidence( ImageRectangle r ) {
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/tld/TldTemplateMatching.java | TldTemplateMatching.distance | public double distance( NccFeature observed , List<NccFeature> candidates ) {
double maximum = -Double.MAX_VALUE;
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for( NccFeature f : candidates ) {
double score = DescriptorDistance.ncc(observed, f);
if( score > maximum )
maximum = score;
... | java | public double distance( NccFeature observed , List<NccFeature> candidates ) {
double maximum = -Double.MAX_VALUE;
// The feature which has the best fit will maximize the score
for( NccFeature f : candidates ) {
double score = DescriptorDistance.ncc(observed, f);
if( score > maximum )
maximum = score;
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/feature/detect/chess/DetectChessboardCornersPyramid.java | DetectChessboardCornersPyramid.process | public void process(GrayF32 input ) {
constructPyramid(input);
corners.reset();
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// for visualiztion purposes
double scale = Math.pow(2.0,pyramid.size()-1);
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constructPyramid(input);
corners.reset();
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// for visualiztion purposes
double scale = Math.pow(2.0,pyramid.size()-1);
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/feature/detect/chess/DetectChessboardCornersPyramid.java | DetectChessboardCornersPyramid.markSeenAsFalse | void markSeenAsFalse(FastQueue<ChessboardCorner> corners0 , FastQueue<ChessboardCorner> corners1 ) {
nn.setPoints(corners1.toList(),false);
// radius of the blob in the intensity image is 2*kernelRadius
int radius = detector.shiRadius *2+1;
for (int i = 0; i < corners0.size; i++) {
ChessboardCorner c0 = corn... | java | void markSeenAsFalse(FastQueue<ChessboardCorner> corners0 , FastQueue<ChessboardCorner> corners1 ) {
nn.setPoints(corners1.toList(),false);
// radius of the blob in the intensity image is 2*kernelRadius
int radius = detector.shiRadius *2+1;
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lessthanoptimal/BoofCV | demonstrations/src/main/java/boofcv/demonstrations/fiducial/DetectQrCodeApp.java | DetectQrCodeApp.processImage | @Override
public void processImage(int sourceID, long frameID, final BufferedImage buffered, ImageBase input) {
System.out.flush();
synchronized (bufferedImageLock) {
original = ConvertBufferedImage.checkCopy(buffered, original);
work = ConvertBufferedImage.checkDeclare(buffered, work);
}
if( saveReque... | java | @Override
public void processImage(int sourceID, long frameID, final BufferedImage buffered, ImageBase input) {
System.out.flush();
synchronized (bufferedImageLock) {
original = ConvertBufferedImage.checkCopy(buffered, original);
work = ConvertBufferedImage.checkDeclare(buffered, work);
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lessthanoptimal/BoofCV | main/boofcv-calibration/src/main/java/boofcv/alg/geo/calibration/Zhang99ComputeTargetHomography.java | Zhang99ComputeTargetHomography.computeHomography | public boolean computeHomography( CalibrationObservation observedPoints )
{
if( observedPoints.size() < 4)
throw new IllegalArgumentException("At least 4 points needed in each set of observations. " +
" Filter these first please");
List<AssociatedPair> pairs = new ArrayList<>();
for( int i = 0; i < obse... | java | public boolean computeHomography( CalibrationObservation observedPoints )
{
if( observedPoints.size() < 4)
throw new IllegalArgumentException("At least 4 points needed in each set of observations. " +
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List<AssociatedPair> pairs = new ArrayList<>();
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lessthanoptimal/BoofCV | main/boofcv-types/src/main/java/boofcv/concurrency/FWorkArrays.java | FWorkArrays.recycle | public synchronized void recycle( float[] array ) {
if( array.length != length ) {
throw new IllegalArgumentException("Unexpected array length. Expected "+length+" found "+array.length);
}
storage.add(array);
} | java | public synchronized void recycle( float[] array ) {
if( array.length != length ) {
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lessthanoptimal/BoofCV | examples/src/main/java/boofcv/examples/sfm/ExampleMultiviewSceneReconstruction.java | ExampleMultiviewSceneReconstruction.visualizeResults | private void visualizeResults( SceneStructureMetric structure,
List<BufferedImage> colorImages ) {
List<Point3D_F64> cloudXyz = new ArrayList<>();
GrowQueue_I32 cloudRgb = new GrowQueue_I32();
Point3D_F64 world = new Point3D_F64();
Point3D_F64 camera = new Point3D_F64();
Point2D_F64 pixel = new Po... | java | private void visualizeResults( SceneStructureMetric structure,
List<BufferedImage> colorImages ) {
List<Point3D_F64> cloudXyz = new ArrayList<>();
GrowQueue_I32 cloudRgb = new GrowQueue_I32();
Point3D_F64 world = new Point3D_F64();
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/qrcode/QrCodePolynomialMath.java | QrCodePolynomialMath.decodeFormatMessage | public static void decodeFormatMessage(int message , QrCode qr ) {
int error = message >> 3;
qr.error = QrCode.ErrorLevel.lookup(error);
qr.mask = QrCodeMaskPattern.lookupMask(message&0x07);
} | java | public static void decodeFormatMessage(int message , QrCode qr ) {
int error = message >> 3;
qr.error = QrCode.ErrorLevel.lookup(error);
qr.mask = QrCodeMaskPattern.lookupMask(message&0x07);
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/qrcode/QrCodePolynomialMath.java | QrCodePolynomialMath.correctDCH | public static int correctDCH( int N , int messageNoMask , int generator , int totalBits, int dataBits) {
int bestHamming = 255;
int bestMessage = -1;
int errorBits = totalBits-dataBits;
// exhaustively check all possibilities
for (int i = 0; i < N; i++) {
int test = i << errorBits;
test = test ^ bitPo... | java | public static int correctDCH( int N , int messageNoMask , int generator , int totalBits, int dataBits) {
int bestHamming = 255;
int bestMessage = -1;
int errorBits = totalBits-dataBits;
// exhaustively check all possibilities
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lessthanoptimal/BoofCV | examples/src/main/java/boofcv/examples/calibration/ExampleRemoveLensDistortion.java | ExampleRemoveLensDistortion.displayResults | private static void displayResults(BufferedImage orig,
Planar<GrayF32> distortedImg,
ImageDistort allInside, ImageDistort fullView ) {
// render the results
Planar<GrayF32> undistortedImg = new Planar<>(GrayF32.class,
distortedImg.getWidth(),distortedImg.getHeight(),distortedImg.getNumBa... | java | private static void displayResults(BufferedImage orig,
Planar<GrayF32> distortedImg,
ImageDistort allInside, ImageDistort fullView ) {
// render the results
Planar<GrayF32> undistortedImg = new Planar<>(GrayF32.class,
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/square/StabilitySquareFiducialEstimate.java | StabilitySquareFiducialEstimate.process | public boolean process( double sampleRadius , Quadrilateral_F64 input ) {
work.set(input);
samples.reset();
estimator.process(work,false);
estimator.getWorldToCamera().invert(referenceCameraToWorld);
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work.set(input);
samples.reset();
estimator.process(work,false);
estimator.getWorldToCamera().invert(referenceCameraToWorld);
samples.reset();
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/square/StabilitySquareFiducialEstimate.java | StabilitySquareFiducialEstimate.createSamples | private void createSamples( double sampleRadius , Point2D_F64 workPoint , Point2D_F64 originalPoint ) {
workPoint.x = originalPoint.x + sampleRadius;
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workPoint.x = originalPoint.x - sampleRadius;
if( estimator.proc... | java | private void createSamples( double sampleRadius , Point2D_F64 workPoint , Point2D_F64 originalPoint ) {
workPoint.x = originalPoint.x + sampleRadius;
if( estimator.process(work,false) ) {
samples.grow().set( estimator.getWorldToCamera() );
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/tld/TldLearning.java | TldLearning.initialLearning | public void initialLearning( Rectangle2D_F64 targetRegion ,
FastQueue<ImageRectangle> cascadeRegions ) {
storageMetric.reset();
fernNegative.clear();
// learn the initial descriptor
TldHelperFunctions.convertRegion(targetRegion, targetRegion_I32);
// select the variance the first time using user s... | java | public void initialLearning( Rectangle2D_F64 targetRegion ,
FastQueue<ImageRectangle> cascadeRegions ) {
storageMetric.reset();
fernNegative.clear();
// learn the initial descriptor
TldHelperFunctions.convertRegion(targetRegion, targetRegion_I32);
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/tld/TldLearning.java | TldLearning.updateLearning | public void updateLearning( Rectangle2D_F64 targetRegion ) {
storageMetric.reset();
// learn the initial descriptor
TldHelperFunctions.convertRegion(targetRegion, targetRegion_I32);
template.addDescriptor(true, targetRegion_I32);
fern.learnFernNoise(true, targetRegion_I32);
// mark only a few of the far... | java | public void updateLearning( Rectangle2D_F64 targetRegion ) {
storageMetric.reset();
// learn the initial descriptor
TldHelperFunctions.convertRegion(targetRegion, targetRegion_I32);
template.addDescriptor(true, targetRegion_I32);
fern.learnFernNoise(true, targetRegion_I32);
// mark only a few of the far... | [
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/tld/TldLearning.java | TldLearning.learnAmbiguousNegative | protected void learnAmbiguousNegative(Rectangle2D_F64 targetRegion) {
TldHelperFunctions.convertRegion(targetRegion, targetRegion_I32);
if( detection.isSuccess() ) {
TldRegion best = detection.getBest();
// see if it found the correct solution
double overlap = helper.computeOverlap(best.rect,targetRegio... | java | protected void learnAmbiguousNegative(Rectangle2D_F64 targetRegion) {
TldHelperFunctions.convertRegion(targetRegion, targetRegion_I32);
if( detection.isSuccess() ) {
TldRegion best = detection.getBest();
// see if it found the correct solution
double overlap = helper.computeOverlap(best.rect,targetRegio... | [
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lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/factory/filter/binary/FactoryThresholdBinary.java | FactoryThresholdBinary.localOtsu | public static <T extends ImageGray<T>>
InputToBinary<T> localOtsu(ConfigLength regionWidth, double scale, boolean down, boolean otsu2, double tuning, Class<T> inputType) {
if( BOverrideFactoryThresholdBinary.localOtsu != null )
return BOverrideFactoryThresholdBinary.localOtsu.handle(otsu2,regionWidth, tuning, sca... | java | public static <T extends ImageGray<T>>
InputToBinary<T> localOtsu(ConfigLength regionWidth, double scale, boolean down, boolean otsu2, double tuning, Class<T> inputType) {
if( BOverrideFactoryThresholdBinary.localOtsu != null )
return BOverrideFactoryThresholdBinary.localOtsu.handle(otsu2,regionWidth, tuning, sca... | [
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lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/factory/filter/binary/FactoryThresholdBinary.java | FactoryThresholdBinary.blockMean | public static <T extends ImageGray<T>>
InputToBinary<T> blockMean(ConfigLength regionWidth, double scale , boolean down, boolean thresholdFromLocalBlocks,
Class<T> inputType) {
if( BOverrideFactoryThresholdBinary.blockMean != null )
return BOverrideFactoryThresholdBinary.blockMean.handle(regionWidth, sc... | java | public static <T extends ImageGray<T>>
InputToBinary<T> blockMean(ConfigLength regionWidth, double scale , boolean down, boolean thresholdFromLocalBlocks,
Class<T> inputType) {
if( BOverrideFactoryThresholdBinary.blockMean != null )
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lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/factory/filter/binary/FactoryThresholdBinary.java | FactoryThresholdBinary.blockOtsu | public static <T extends ImageGray<T>>
InputToBinary<T> blockOtsu(ConfigLength regionWidth, double scale, boolean down, boolean thresholdFromLocalBlocks,
boolean otsu2, double tuning,Class<T> inputType) {
if( BOverrideFactoryThresholdBinary.blockOtsu != null )
return BOverrideFactoryThresholdBinary.bloc... | java | public static <T extends ImageGray<T>>
InputToBinary<T> blockOtsu(ConfigLength regionWidth, double scale, boolean down, boolean thresholdFromLocalBlocks,
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if( BOverrideFactoryThresholdBinary.blockOtsu != null )
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lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/factory/filter/binary/FactoryThresholdBinary.java | FactoryThresholdBinary.threshold | public static <T extends ImageGray<T>>
InputToBinary<T> threshold( ConfigThreshold config, Class<T> inputType) {
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case FIXED:
return globalFixed(config.fixedThreshold, config.down, inputType);
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return globalOtsu(config.minPixelValue, config.maxPixelValue, confi... | java | public static <T extends ImageGray<T>>
InputToBinary<T> threshold( ConfigThreshold config, Class<T> inputType) {
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lessthanoptimal/BoofCV | integration/boofcv-swing/src/main/java/boofcv/gui/dialogs/JSpringPanel.java | JSpringPanel.constraintSouth | public void constraintSouth(JComponent target, JComponent top, JComponent bottom, int padV ) {
if( bottom == null ) {
layout.putConstraint(SpringLayout.SOUTH, target, -padV, SpringLayout.SOUTH, this);
} else {
Spring a = Spring.sum(Spring.constant(-padV),layout.getConstraint(Spri... | java | public void constraintSouth(JComponent target, JComponent top, JComponent bottom, int padV ) {
if( bottom == null ) {
layout.putConstraint(SpringLayout.SOUTH, target, -padV, SpringLayout.SOUTH, this);
} else {
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/square/QuadPoseEstimator.java | QuadPoseEstimator.setLensDistoriton | public void setLensDistoriton(LensDistortionNarrowFOV distortion ) {
pixelToNorm = distortion.undistort_F64(true,false);
normToPixel = distortion.distort_F64(false, true);
} | java | public void setLensDistoriton(LensDistortionNarrowFOV distortion ) {
pixelToNorm = distortion.undistort_F64(true,false);
normToPixel = distortion.distort_F64(false, true);
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/square/QuadPoseEstimator.java | QuadPoseEstimator.setFiducial | public void setFiducial( double x0 , double y0 , double x1 , double y1 ,
double x2 , double y2 , double x3 , double y3 ) {
points.get(0).location.set(x0,y0,0);
points.get(1).location.set(x1,y1,0);
points.get(2).location.set(x2,y2,0);
points.get(3).location.set(x3,y3,0);
} | java | public void setFiducial( double x0 , double y0 , double x1 , double y1 ,
double x2 , double y2 , double x3 , double y3 ) {
points.get(0).location.set(x0,y0,0);
points.get(1).location.set(x1,y1,0);
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] | f01c0243da0ec086285ee722183804d5923bc3ac | https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/square/QuadPoseEstimator.java#L141-L147 | train |
lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/square/QuadPoseEstimator.java | QuadPoseEstimator.pixelToMarker | public void pixelToMarker( double pixelX , double pixelY , Point2D_F64 marker ) {
// find pointing vector in camera reference frame
pixelToNorm.compute(pixelX,pixelY,marker);
cameraP3.set(marker.x,marker.y,1);
// rotate into marker reference frame
GeometryMath_F64.multTran(outputFiducialToCamera.R,cameraP3,... | java | public void pixelToMarker( double pixelX , double pixelY , Point2D_F64 marker ) {
// find pointing vector in camera reference frame
pixelToNorm.compute(pixelX,pixelY,marker);
cameraP3.set(marker.x,marker.y,1);
// rotate into marker reference frame
GeometryMath_F64.multTran(outputFiducialToCamera.R,cameraP3,... | [
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/square/QuadPoseEstimator.java | QuadPoseEstimator.estimate | protected boolean estimate( Quadrilateral_F64 cornersPixels ,
Quadrilateral_F64 cornersNorm ,
Se3_F64 foundFiducialToCamera ) {
// put it into a list to simplify algorithms
listObs.clear();
listObs.add( cornersPixels.a );
listObs.add( cornersPixels.b );
listObs.add( cornersPixels.c );
listOb... | java | protected boolean estimate( Quadrilateral_F64 cornersPixels ,
Quadrilateral_F64 cornersNorm ,
Se3_F64 foundFiducialToCamera ) {
// put it into a list to simplify algorithms
listObs.clear();
listObs.add( cornersPixels.a );
listObs.add( cornersPixels.b );
listObs.add( cornersPixels.c );
listOb... | [
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/square/QuadPoseEstimator.java | QuadPoseEstimator.estimateP3P | protected void estimateP3P(int excluded) {
// the point used to check the solutions is the last one
inputP3P.clear();
for( int i = 0; i < 4; i++ ) {
if( i != excluded ) {
inputP3P.add( points.get(i) );
}
}
// initial estimate for the pose
solutions.reset();
if( !p3p.process(inputP3P,solutions)... | java | protected void estimateP3P(int excluded) {
// the point used to check the solutions is the last one
inputP3P.clear();
for( int i = 0; i < 4; i++ ) {
if( i != excluded ) {
inputP3P.add( points.get(i) );
}
}
// initial estimate for the pose
solutions.reset();
if( !p3p.process(inputP3P,solutions)... | [
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/square/QuadPoseEstimator.java | QuadPoseEstimator.enlarge | protected void enlarge( Quadrilateral_F64 corners, double scale ) {
UtilPolygons2D_F64.center(corners, center);
extend(center,corners.a,scale);
extend(center,corners.b,scale);
extend(center,corners.c,scale);
extend(center,corners.d,scale);
} | java | protected void enlarge( Quadrilateral_F64 corners, double scale ) {
UtilPolygons2D_F64.center(corners, center);
extend(center,corners.a,scale);
extend(center,corners.b,scale);
extend(center,corners.c,scale);
extend(center,corners.d,scale);
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/square/QuadPoseEstimator.java | QuadPoseEstimator.computeErrors | protected double computeErrors(Se3_F64 fiducialToCamera ) {
if( fiducialToCamera.T.z < 0 ) {
// the low level algorithm should already filter this code, but just incase
return Double.MAX_VALUE;
}
double maxError = 0;
for( int i = 0; i < 4; i++ ) {
maxError = Math.max(maxError,computePixelError(fiduci... | java | protected double computeErrors(Se3_F64 fiducialToCamera ) {
if( fiducialToCamera.T.z < 0 ) {
// the low level algorithm should already filter this code, but just incase
return Double.MAX_VALUE;
}
double maxError = 0;
for( int i = 0; i < 4; i++ ) {
maxError = Math.max(maxError,computePixelError(fiduci... | [
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lessthanoptimal/BoofCV | main/boofcv-geo/src/main/java/boofcv/alg/geo/f/ParamFundamentalEpipolar.java | ParamFundamentalEpipolar.encode | @Override
public void encode(DMatrixRMaj F, double[] param) {
// see if which columns are to be used
selectColumns(F);
// set the largest element in the first two columns and normalize
// using that value
double v[] = new double[]{F.get(0,col0),F.get(1,col0),F.get(2,col0),
F.get(0,col1),F.get(1,col1),... | java | @Override
public void encode(DMatrixRMaj F, double[] param) {
// see if which columns are to be used
selectColumns(F);
// set the largest element in the first two columns and normalize
// using that value
double v[] = new double[]{F.get(0,col0),F.get(1,col0),F.get(2,col0),
F.get(0,col1),F.get(1,col1),... | [
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lessthanoptimal/BoofCV | main/boofcv-geo/src/main/java/boofcv/alg/geo/f/ParamFundamentalEpipolar.java | ParamFundamentalEpipolar.selectDivisor | private double selectDivisor( double v[] , double param[] ) {
double maxValue = 0;
int maxIndex = 0;
for( int i = 0; i < v.length; i++ ) {
if( Math.abs(v[i]) > maxValue ) {
maxValue = Math.abs(v[i]);
maxIndex = i;
}
}
double divisor = v[maxIndex];
int index = 0;
for( int i = 0; i < v.leng... | java | private double selectDivisor( double v[] , double param[] ) {
double maxValue = 0;
int maxIndex = 0;
for( int i = 0; i < v.length; i++ ) {
if( Math.abs(v[i]) > maxValue ) {
maxValue = Math.abs(v[i]);
maxIndex = i;
}
}
double divisor = v[maxIndex];
int index = 0;
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lessthanoptimal/BoofCV | main/boofcv-sfm/src/main/java/boofcv/alg/sfm/structure2/GeneratePairwiseImageGraph.java | GeneratePairwiseImageGraph.createEdge | protected void createEdge( String src , String dst ,
FastQueue<AssociatedPair> pairs , FastQueue<AssociatedIndex> matches ) {
// Fitting Essential/Fundamental works when the scene is not planar and not pure rotation
int countF = 0;
if( ransac3D.process(pairs.toList()) ) {
countF = ransac3D.getMatchSe... | java | protected void createEdge( String src , String dst ,
FastQueue<AssociatedPair> pairs , FastQueue<AssociatedIndex> matches ) {
// Fitting Essential/Fundamental works when the scene is not planar and not pure rotation
int countF = 0;
if( ransac3D.process(pairs.toList()) ) {
countF = ransac3D.getMatchSe... | [
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lessthanoptimal/BoofCV | main/boofcv-sfm/src/main/java/boofcv/alg/sfm/structure2/GeneratePairwiseImageGraph.java | GeneratePairwiseImageGraph.saveInlierMatches | private void saveInlierMatches(ModelMatcher<?, ?> ransac,
FastQueue<AssociatedIndex> matches, PairwiseImageGraph2.Motion edge) {
int N = ransac.getMatchSet().size();
edge.inliers.reset();
for (int i = 0; i < N; i++) {
int idx = ransac.getInputIndex(i);
edge.inliers.grow().set(matches.get(idx));
... | java | private void saveInlierMatches(ModelMatcher<?, ?> ransac,
FastQueue<AssociatedIndex> matches, PairwiseImageGraph2.Motion edge) {
int N = ransac.getMatchSet().size();
edge.inliers.reset();
for (int i = 0; i < N; i++) {
int idx = ransac.getInputIndex(i);
edge.inliers.grow().set(matches.get(idx));
... | [
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/squares/SquaresIntoClusters.java | SquaresIntoClusters.recycleData | protected void recycleData() {
for (int i = 0; i < nodes.size(); i++) {
SquareNode n = nodes.get(i);
for (int j = 0; j < n.edges.length; j++) {
if( n.edges[j] != null ) {
graph.detachEdge(n.edges[j]);
}
}
}
for (int i = 0; i < nodes.size(); i++) {
SquareNode n = nodes.get(i);
for (int ... | java | protected void recycleData() {
for (int i = 0; i < nodes.size(); i++) {
SquareNode n = nodes.get(i);
for (int j = 0; j < n.edges.length; j++) {
if( n.edges[j] != null ) {
graph.detachEdge(n.edges[j]);
}
}
}
for (int i = 0; i < nodes.size(); i++) {
SquareNode n = nodes.get(i);
for (int ... | [
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/squares/SquaresIntoClusters.java | SquaresIntoClusters.findClusters | protected void findClusters() {
for (int i = 0; i < nodes.size(); i++) {
SquareNode n = nodes.get(i);
if( n.graph < 0 ) {
n.graph = clusters.size();
List<SquareNode> graph = clusters.grow();
graph.add(n);
addToCluster(n, graph);
}
}
} | java | protected void findClusters() {
for (int i = 0; i < nodes.size(); i++) {
SquareNode n = nodes.get(i);
if( n.graph < 0 ) {
n.graph = clusters.size();
List<SquareNode> graph = clusters.grow();
graph.add(n);
addToCluster(n, graph);
}
}
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/squares/SquaresIntoClusters.java | SquaresIntoClusters.addToCluster | void addToCluster(SquareNode seed, List<SquareNode> graph) {
open.clear();
open.add(seed);
while( !open.isEmpty() ) {
SquareNode n = open.remove( open.size() - 1 );
for (int i = 0; i < n.square.size(); i++) {
SquareEdge edge = n.edges[i];
if( edge == null )
continue;
SquareNode other;
... | java | void addToCluster(SquareNode seed, List<SquareNode> graph) {
open.clear();
open.add(seed);
while( !open.isEmpty() ) {
SquareNode n = open.remove( open.size() - 1 );
for (int i = 0; i < n.square.size(); i++) {
SquareEdge edge = n.edges[i];
if( edge == null )
continue;
SquareNode other;
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lessthanoptimal/BoofCV | examples/src/main/java/boofcv/examples/segmentation/ExampleSegmentColor.java | ExampleSegmentColor.printClickedColor | public static void printClickedColor( final BufferedImage image ) {
ImagePanel gui = new ImagePanel(image);
gui.addMouseListener(new MouseAdapter() {
@Override
public void mouseClicked(MouseEvent e) {
float[] color = new float[3];
int rgb = image.getRGB(e.getX(),e.getY());
ColorHsv.rgbToHsv((rgb >... | java | public static void printClickedColor( final BufferedImage image ) {
ImagePanel gui = new ImagePanel(image);
gui.addMouseListener(new MouseAdapter() {
@Override
public void mouseClicked(MouseEvent e) {
float[] color = new float[3];
int rgb = image.getRGB(e.getX(),e.getY());
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lessthanoptimal/BoofCV | examples/src/main/java/boofcv/examples/segmentation/ExampleSegmentColor.java | ExampleSegmentColor.showSelectedColor | public static void showSelectedColor( String name , BufferedImage image , float hue , float saturation ) {
Planar<GrayF32> input = ConvertBufferedImage.convertFromPlanar(image,null,true,GrayF32.class);
Planar<GrayF32> hsv = input.createSameShape();
// Convert into HSV
ColorHsv.rgbToHsv(input,hsv);
// Euclid... | java | public static void showSelectedColor( String name , BufferedImage image , float hue , float saturation ) {
Planar<GrayF32> input = ConvertBufferedImage.convertFromPlanar(image,null,true,GrayF32.class);
Planar<GrayF32> hsv = input.createSameShape();
// Convert into HSV
ColorHsv.rgbToHsv(input,hsv);
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lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/alg/transform/wavelet/UtilWavelet.java | UtilWavelet.transformDimension | public static ImageDimension transformDimension( ImageBase orig , int level )
{
return transformDimension(orig.width,orig.height,level);
} | java | public static ImageDimension transformDimension( ImageBase orig , int level )
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return transformDimension(orig.width,orig.height,level);
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lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/alg/transform/wavelet/UtilWavelet.java | UtilWavelet.borderForwardLower | public static int borderForwardLower( WlCoef desc ) {
int ret = -Math.min(desc.offsetScaling,desc.offsetWavelet);
return ret + (ret % 2);
} | java | public static int borderForwardLower( WlCoef desc ) {
int ret = -Math.min(desc.offsetScaling,desc.offsetWavelet);
return ret + (ret % 2);
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lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/alg/transform/wavelet/UtilWavelet.java | UtilWavelet.borderInverseLower | public static int borderInverseLower( WlBorderCoef<?> desc, BorderIndex1D border ) {
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int borderSize = borderForwardLower(inner);
WlCoef ll = borderSize > 0 ? inner : null;
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int indexLU = 0;
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WlCoef inner = desc.getInnerCoefficients();
int borderSize = borderForwardLower(inner);
WlCoef ll = borderSize > 0 ? inner : null;
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WlCoef uu = inner;
int indexLU = 0;
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lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/alg/transform/wavelet/UtilWavelet.java | UtilWavelet.round | public static int round( int top , int div2 , int divisor ) {
if( top > 0 )
return (top + div2)/divisor;
else
return (top - div2)/divisor;
} | java | public static int round( int top , int div2 , int divisor ) {
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lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/alg/transform/wavelet/UtilWavelet.java | UtilWavelet.adjustForDisplay | public static void adjustForDisplay(ImageGray transform , int numLevels , double valueRange ) {
if( transform instanceof GrayF32)
adjustForDisplay((GrayF32)transform,numLevels,(float)valueRange);
else
adjustForDisplay((GrayI)transform,numLevels,(int)valueRange);
} | java | public static void adjustForDisplay(ImageGray transform , int numLevels , double valueRange ) {
if( transform instanceof GrayF32)
adjustForDisplay((GrayF32)transform,numLevels,(float)valueRange);
else
adjustForDisplay((GrayI)transform,numLevels,(int)valueRange);
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lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/alg/enhance/impl/ImplEnhanceHistogram.java | ImplEnhanceHistogram.equalizeLocalNaive | public static void equalizeLocalNaive( GrayU8 input , int radius , GrayU8 output ,
IWorkArrays workArrays )
{
int width = 2*radius+1;
int maxValue = workArrays.length()-1;
//CONCURRENT_BELOW BoofConcurrency.loopBlocks(0,input.height,(idx0,idx1)->{
int idx0 = 0, idx1 = input.height;
int[] histog... | java | public static void equalizeLocalNaive( GrayU8 input , int radius , GrayU8 output ,
IWorkArrays workArrays )
{
int width = 2*radius+1;
int maxValue = workArrays.length()-1;
//CONCURRENT_BELOW BoofConcurrency.loopBlocks(0,input.height,(idx0,idx1)->{
int idx0 = 0, idx1 = input.height;
int[] histog... | [
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lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/alg/enhance/impl/ImplEnhanceHistogram.java | ImplEnhanceHistogram.equalizeLocalInner | public static void equalizeLocalInner( GrayU8 input , int radius , GrayU8 output ,
IWorkArrays workArrays ) {
int width = 2*radius+1;
int area = width*width;
int maxValue = workArrays.length()-1;
//CONCURRENT_BELOW BoofConcurrency.loopBlocks(radius,input.height-radius,(y0,y1)->{
int y0 = radius, ... | java | public static void equalizeLocalInner( GrayU8 input , int radius , GrayU8 output ,
IWorkArrays workArrays ) {
int width = 2*radius+1;
int area = width*width;
int maxValue = workArrays.length()-1;
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lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/alg/enhance/impl/ImplEnhanceHistogram.java | ImplEnhanceHistogram.localHistogram | public static void localHistogram( GrayU16 input , int x0 , int y0 , int x1, int y1 , int histogram[] ) {
for( int i = 0; i < histogram.length; i++ )
histogram[i] = 0;
for( int i = y0; i < y1; i++ ) {
int index = input.startIndex + i*input.stride + x0;
int end = index + x1-x0;
for( ; index < end; index... | java | public static void localHistogram( GrayU16 input , int x0 , int y0 , int x1, int y1 , int histogram[] ) {
for( int i = 0; i < histogram.length; i++ )
histogram[i] = 0;
for( int i = y0; i < y1; i++ ) {
int index = input.startIndex + i*input.stride + x0;
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lessthanoptimal/BoofCV | integration/boofcv-swing/src/main/java/boofcv/gui/image/ImageZoomPanel.java | ImageZoomPanel.setBufferedImage | public synchronized void setBufferedImage(BufferedImage image) {
// assume the image was initially set before the GUI was invoked
if( checkEventDispatch && this.img != null ) {
if( !SwingUtilities.isEventDispatchThread() )
throw new RuntimeException("Changed image when not in GUI thread?");
}
this.img =... | java | public synchronized void setBufferedImage(BufferedImage image) {
// assume the image was initially set before the GUI was invoked
if( checkEventDispatch && this.img != null ) {
if( !SwingUtilities.isEventDispatchThread() )
throw new RuntimeException("Changed image when not in GUI thread?");
}
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/meanshift/TrackerMeanShiftLikelihood.java | TrackerMeanShiftLikelihood.initialize | public void initialize( T image , RectangleLength2D_I32 initial ) {
if( !image.isInBounds(initial.x0,initial.y0) )
throw new IllegalArgumentException("Initial rectangle is out of bounds!");
if( !image.isInBounds(initial.x0+initial.width,initial.y0+initial.height) )
throw new IllegalArgumentException("Initial ... | java | public void initialize( T image , RectangleLength2D_I32 initial ) {
if( !image.isInBounds(initial.x0,initial.y0) )
throw new IllegalArgumentException("Initial rectangle is out of bounds!");
if( !image.isInBounds(initial.x0+initial.width,initial.y0+initial.height) )
throw new IllegalArgumentException("Initial ... | [
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/meanshift/TrackerMeanShiftLikelihood.java | TrackerMeanShiftLikelihood.process | public boolean process( T image ) {
if( failed )
return false;
targetModel.setImage(image);
// mark the region where the pdf has been modified as dirty
dirty.set(location.x0, location.y0, location.x0 + location.width, location.y0 + location.height);
// compute the pdf inside the initial rectangle
upda... | java | public boolean process( T image ) {
if( failed )
return false;
targetModel.setImage(image);
// mark the region where the pdf has been modified as dirty
dirty.set(location.x0, location.y0, location.x0 + location.width, location.y0 + location.height);
// compute the pdf inside the initial rectangle
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/meanshift/TrackerMeanShiftLikelihood.java | TrackerMeanShiftLikelihood.updatePdfImage | protected void updatePdfImage( int x0 , int y0 , int x1 , int y1 ) {
for( int y = y0; y < y1; y++ ) {
int indexOut = pdf.startIndex + pdf.stride*y + x0;
for( int x = x0; x < x1; x++ , indexOut++ ) {
if( pdf.data[indexOut] < 0 )
pdf.data[indexOut] = targetModel.compute(x, y);
}
}
// update th... | java | protected void updatePdfImage( int x0 , int y0 , int x1 , int y1 ) {
for( int y = y0; y < y1; y++ ) {
int indexOut = pdf.startIndex + pdf.stride*y + x0;
for( int x = x0; x < x1; x++ , indexOut++ ) {
if( pdf.data[indexOut] < 0 )
pdf.data[indexOut] = targetModel.compute(x, y);
}
}
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/segmentation/ms/SegmentMeanShiftSearchGray.java | SegmentMeanShiftSearchGray.process | @Override
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// initialize data structures
this.image = image;
this.stopRequested = false;
modeLocation.reset();
modeColor.reset();
modeMemberCount.reset();
interpolate.setImage(image);
pixelToMode.reshape(image.width, image.height);
quickMode.reshape(image.width, ima... | java | @Override
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// initialize data structures
this.image = image;
this.stopRequested = false;
modeLocation.reset();
modeColor.reset();
modeMemberCount.reset();
interpolate.setImage(image);
pixelToMode.reshape(image.width, image.height);
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lessthanoptimal/BoofCV | main/boofcv-geo/src/main/java/boofcv/struct/geo/Point2D3D.java | Point2D3D.set | public void set( Point2D3D src ) {
observation.set(src.observation);
location.set(src.location);
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observation.set(src.observation);
location.set(src.location);
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/shapes/polygon/DetectPolygonBinaryGrayRefine.java | DetectPolygonBinaryGrayRefine.clearLensDistortion | public void clearLensDistortion() {
detector.clearLensDistortion();
if( refineGray != null )
refineGray.clearLensDistortion();
edgeIntensity.setTransform(null);
} | java | public void clearLensDistortion() {
detector.clearLensDistortion();
if( refineGray != null )
refineGray.clearLensDistortion();
edgeIntensity.setTransform(null);
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/shapes/polygon/DetectPolygonBinaryGrayRefine.java | DetectPolygonBinaryGrayRefine.process | public void process(T gray , GrayU8 binary ) {
detector.process(gray,binary);
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refineGray.setImage(gray);
edgeIntensity.setImage(gray);
long time0 = System.nanoTime();
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int... | java | public void process(T gray , GrayU8 binary ) {
detector.process(gray,binary);
if( refineGray != null )
refineGray.setImage(gray);
edgeIntensity.setImage(gray);
long time0 = System.nanoTime();
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/shapes/polygon/DetectPolygonBinaryGrayRefine.java | DetectPolygonBinaryGrayRefine.refine | public boolean refine( DetectPolygonFromContour.Info info ) {
double before,after;
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before = edgeIntensity.getAverageOutside() - edgeIntensity.getAverageInside();
} else {
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}
boolean success = false;
if( refine... | java | public boolean refine( DetectPolygonFromContour.Info info ) {
double before,after;
if( edgeIntensity.computeEdge(info.polygon,!detector.isOutputClockwise()) ) {
before = edgeIntensity.getAverageOutside() - edgeIntensity.getAverageInside();
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boolean success = false;
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/shapes/polygon/DetectPolygonBinaryGrayRefine.java | DetectPolygonBinaryGrayRefine.refineAll | public void refineAll() {
List<DetectPolygonFromContour.Info> detections = detector.getFound().toList();
for (int i = 0; i < detections.size(); i++) {
refine(detections.get(i));
}
} | java | public void refineAll() {
List<DetectPolygonFromContour.Info> detections = detector.getFound().toList();
for (int i = 0; i < detections.size(); i++) {
refine(detections.get(i));
}
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lessthanoptimal/BoofCV | main/boofcv-types/src/main/java/boofcv/alg/InputSanityCheck.java | InputSanityCheck.checkReshape | public static <T extends ImageGray<T>> T checkReshape(T target , ImageGray testImage , Class<T> targetType )
{
if( target == null ) {
return GeneralizedImageOps.createSingleBand(targetType, testImage.width, testImage.height);
} else if( target.width != testImage.width || target.height != testImage.height ) {
... | java | public static <T extends ImageGray<T>> T checkReshape(T target , ImageGray testImage , Class<T> targetType )
{
if( target == null ) {
return GeneralizedImageOps.createSingleBand(targetType, testImage.width, testImage.height);
} else if( target.width != testImage.width || target.height != testImage.height ) {
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/feature/detect/interest/FeaturePyramid.java | FeaturePyramid.findLocalScaleSpaceMax | protected void findLocalScaleSpaceMax(PyramidFloat<T> ss, int layerID) {
int index0 = spaceIndex;
int index1 = (spaceIndex + 1) % 3;
int index2 = (spaceIndex + 2) % 3;
List<Point2D_I16> candidates = maximums[index1];
ImageBorder_F32 inten0 = (ImageBorder_F32) FactoryImageBorderAlgs.value(intensities[index0],... | java | protected void findLocalScaleSpaceMax(PyramidFloat<T> ss, int layerID) {
int index0 = spaceIndex;
int index1 = (spaceIndex + 1) % 3;
int index2 = (spaceIndex + 2) % 3;
List<Point2D_I16> candidates = maximums[index1];
ImageBorder_F32 inten0 = (ImageBorder_F32) FactoryImageBorderAlgs.value(intensities[index0],... | [
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/squares/SquaresIntoCrossClusters.java | SquaresIntoCrossClusters.getCornerIndex | int getCornerIndex( SquareNode node , double x , double y ) {
for (int i = 0; i < node.square.size(); i++) {
Point2D_F64 c = node.square.get(i);
if( c.x == x && c.y == y )
return i;
}
throw new RuntimeException("BUG!");
} | java | int getCornerIndex( SquareNode node , double x , double y ) {
for (int i = 0; i < node.square.size(); i++) {
Point2D_F64 c = node.square.get(i);
if( c.x == x && c.y == y )
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}
throw new RuntimeException("BUG!");
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lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/squares/SquaresIntoCrossClusters.java | SquaresIntoCrossClusters.candidateIsMuchCloser | boolean candidateIsMuchCloser( SquareNode node0 ,
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{
double length = Math.max(node0.largestSide,node1.largestSide)*tooFarFraction;
length *= length;
if( distance2 > length)
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return distance2 <= length;
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double distance2 )
{
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lessthanoptimal/BoofCV | integration/boofcv-swing/src/main/java/boofcv/gui/ApplicationLauncherApp.java | ApplicationLauncherApp.handleContextMenu | private void handleContextMenu(JTree tree, int x, int y) {
TreePath path = tree.getPathForLocation(x, y);
tree.setSelectionPath(path);
DefaultMutableTreeNode node = (DefaultMutableTreeNode) tree.getLastSelectedPathComponent();
if (node == null)
return;
if (!node.isLeaf()) {
tree.setSelectionPath(null);... | java | private void handleContextMenu(JTree tree, int x, int y) {
TreePath path = tree.getPathForLocation(x, y);
tree.setSelectionPath(path);
DefaultMutableTreeNode node = (DefaultMutableTreeNode) tree.getLastSelectedPathComponent();
if (node == null)
return;
if (!node.isLeaf()) {
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lessthanoptimal/BoofCV | integration/boofcv-swing/src/main/java/boofcv/gui/ApplicationLauncherApp.java | ApplicationLauncherApp.openInGitHub | private void openInGitHub( AppInfo info ) {
if (Desktop.isDesktopSupported()) {
try {
URI uri = new URI(UtilIO.getGithubURL(info.app.getPackage().getName(), info.app.getSimpleName()));
if (!uri.getPath().isEmpty())
Desktop.getDesktop().browse(uri);
else
System.err.println("Bad URL received")... | java | private void openInGitHub( AppInfo info ) {
if (Desktop.isDesktopSupported()) {
try {
URI uri = new URI(UtilIO.getGithubURL(info.app.getPackage().getName(), info.app.getSimpleName()));
if (!uri.getPath().isEmpty())
Desktop.getDesktop().browse(uri);
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System.err.println("Bad URL received")... | [
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lessthanoptimal/BoofCV | integration/boofcv-swing/src/main/java/boofcv/gui/ApplicationLauncherApp.java | ApplicationLauncherApp.killAllProcesses | public void killAllProcesses( long blockTimeMS ) {
// remove already dead processes from the GUI
SwingUtilities.invokeLater(new Runnable() {
@Override
public void run() {
DefaultListModel model = (DefaultListModel)processList.getModel();
for (int i = model.size()-1; i >= 0; i--) {
ActiveProcess p... | java | public void killAllProcesses( long blockTimeMS ) {
// remove already dead processes from the GUI
SwingUtilities.invokeLater(new Runnable() {
@Override
public void run() {
DefaultListModel model = (DefaultListModel)processList.getModel();
for (int i = model.size()-1; i >= 0; i--) {
ActiveProcess p... | [
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@param blockTimeMS If > 0 then it will block until all processes are killed for the specified number
of milliseconds | [
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] | f01c0243da0ec086285ee722183804d5923bc3ac | https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/integration/boofcv-swing/src/main/java/boofcv/gui/ApplicationLauncherApp.java#L415-L452 | train |
lessthanoptimal/BoofCV | integration/boofcv-swing/src/main/java/boofcv/gui/ApplicationLauncherApp.java | ApplicationLauncherApp.intervalAdded | @Override
public void intervalAdded(ListDataEvent e) {
//retrieve the most recently added process and display it
DefaultListModel listModel = (DefaultListModel) e.getSource();
ActiveProcess process = (ActiveProcess) listModel.get(listModel.getSize() - 1);
addProcessTab(process, outputPanel);
} | java | @Override
public void intervalAdded(ListDataEvent e) {
//retrieve the most recently added process and display it
DefaultListModel listModel = (DefaultListModel) e.getSource();
ActiveProcess process = (ActiveProcess) listModel.get(listModel.getSize() - 1);
addProcessTab(process, outputPanel);
} | [
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/segmentation/ms/ClusterLabeledImage.java | ClusterLabeledImage.setUpEdges | protected void setUpEdges(GrayS32 input , GrayS32 output ) {
if( connectRule == ConnectRule.EIGHT ) {
setUpEdges8(input,edgesIn);
setUpEdges8(output,edgesOut);
edges[0].set( 1, 0);
edges[1].set( 1, 1);
edges[2].set( 0, 1);
edges[3].set(-1, 0);
} else {
setUpEdges4(input,edgesIn);
setUpEdge... | java | protected void setUpEdges(GrayS32 input , GrayS32 output ) {
if( connectRule == ConnectRule.EIGHT ) {
setUpEdges8(input,edgesIn);
setUpEdges8(output,edgesOut);
edges[0].set( 1, 0);
edges[1].set( 1, 1);
edges[2].set( 0, 1);
edges[3].set(-1, 0);
} else {
setUpEdges4(input,edgesIn);
setUpEdge... | [
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/segmentation/ms/ClusterLabeledImage.java | ClusterLabeledImage.process | public void process(GrayS32 input , GrayS32 output , GrowQueue_I32 regionMemberCount ) {
// initialize data structures
this.regionMemberCount = regionMemberCount;
regionMemberCount.reset();
setUpEdges(input,output);
ImageMiscOps.fill(output,-1);
// this is a bit of a hack here. Normally you call the pare... | java | public void process(GrayS32 input , GrayS32 output , GrowQueue_I32 regionMemberCount ) {
// initialize data structures
this.regionMemberCount = regionMemberCount;
regionMemberCount.reset();
setUpEdges(input,output);
ImageMiscOps.fill(output,-1);
// this is a bit of a hack here. Normally you call the pare... | [
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"(... | Relabels the image such that all pixels with the same label are a member of the same graph.
@param input Labeled input image.
@param output Labeled output image.
@param regionMemberCount (Input/Output) Number of pixels which belong to each group. | [
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] | f01c0243da0ec086285ee722183804d5923bc3ac | https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-feature/src/main/java/boofcv/alg/segmentation/ms/ClusterLabeledImage.java#L125-L143 | train |
lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/segmentation/ms/ClusterLabeledImage.java | ClusterLabeledImage.connectInner | protected void connectInner(GrayS32 input, GrayS32 output) {
int startX = connectRule == ConnectRule.EIGHT ? 1 : 0;
for( int y = 0; y < input.height-1; y++ ) {
int indexIn = input.startIndex + y*input.stride + startX;
int indexOut = output.startIndex + y*output.stride + startX;
for( int x = startX; x < ... | java | protected void connectInner(GrayS32 input, GrayS32 output) {
int startX = connectRule == ConnectRule.EIGHT ? 1 : 0;
for( int y = 0; y < input.height-1; y++ ) {
int indexIn = input.startIndex + y*input.stride + startX;
int indexOut = output.startIndex + y*output.stride + startX;
for( int x = startX; x < ... | [
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"input... | Examines pixels inside the image without the need for bounds checking | [
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] | f01c0243da0ec086285ee722183804d5923bc3ac | https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-feature/src/main/java/boofcv/alg/segmentation/ms/ClusterLabeledImage.java#L148-L178 | train |
lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/segmentation/ms/ClusterLabeledImage.java | ClusterLabeledImage.connectLeftRight | protected void connectLeftRight(GrayS32 input, GrayS32 output) {
for( int y = 0; y < input.height; y++ ) {
int x = input.width-1;
int inputLabel = input.unsafe_get(x, y);
int outputLabel = output.unsafe_get(x, y);
if( outputLabel == -1 ) { // see if it needs to create a new output segment
outputLabe... | java | protected void connectLeftRight(GrayS32 input, GrayS32 output) {
for( int y = 0; y < input.height; y++ ) {
int x = input.width-1;
int inputLabel = input.unsafe_get(x, y);
int outputLabel = output.unsafe_get(x, y);
if( outputLabel == -1 ) { // see if it needs to create a new output segment
outputLabe... | [
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... | Examines pixels along the left and right border | [
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"and",
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"border"
] | f01c0243da0ec086285ee722183804d5923bc3ac | https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-feature/src/main/java/boofcv/alg/segmentation/ms/ClusterLabeledImage.java#L183-L251 | train |
lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/segmentation/ms/ClusterLabeledImage.java | ClusterLabeledImage.connectBottom | protected void connectBottom(GrayS32 input, GrayS32 output) {
for( int x = 0; x < input.width-1; x++ ) {
int y = input.height-1;
int inputLabel = input.unsafe_get(x,y);
int outputLabel = output.unsafe_get(x,y);
if( outputLabel == -1 ) { // see if it needs to create a new output segment
outputLabel =... | java | protected void connectBottom(GrayS32 input, GrayS32 output) {
for( int x = 0; x < input.width-1; x++ ) {
int y = input.height-1;
int inputLabel = input.unsafe_get(x,y);
int outputLabel = output.unsafe_get(x,y);
if( outputLabel == -1 ) { // see if it needs to create a new output segment
outputLabel =... | [
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"height"... | Examines pixels along the bottom border | [
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] | f01c0243da0ec086285ee722183804d5923bc3ac | https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-feature/src/main/java/boofcv/alg/segmentation/ms/ClusterLabeledImage.java#L256-L281 | train |
lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/tracker/klt/KltTracker.java | KltTracker.setImage | public void setImage(I image, D derivX, D derivY) {
InputSanityCheck.checkSameShape(image, derivX, derivY);
this.image = image;
this.interpInput.setImage(image);
this.derivX = derivX;
this.derivY = derivY;
} | java | public void setImage(I image, D derivX, D derivY) {
InputSanityCheck.checkSameShape(image, derivX, derivY);
this.image = image;
this.interpInput.setImage(image);
this.derivX = derivX;
this.derivY = derivY;
} | [
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... | Sets the current image it should be tracking with.
@param image Original input image.
@param derivX Image derivative along the x-axis
@param derivY Image derivative along the y-axis | [
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] | f01c0243da0ec086285ee722183804d5923bc3ac | https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-feature/src/main/java/boofcv/alg/tracker/klt/KltTracker.java#L119-L127 | train |
lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/tracker/klt/KltTracker.java | KltTracker.setDescription | @SuppressWarnings({"SuspiciousNameCombination"})
public boolean setDescription(KltFeature feature) {
setAllowedBounds(feature);
if (!isFullyInside(feature.x, feature.y)) {
if( isFullyOutside(feature.x,feature.y))
return false;
else
return internalSetDescriptionBorder(feature);
}
return internal... | java | @SuppressWarnings({"SuspiciousNameCombination"})
public boolean setDescription(KltFeature feature) {
setAllowedBounds(feature);
if (!isFullyInside(feature.x, feature.y)) {
if( isFullyOutside(feature.x,feature.y))
return false;
else
return internalSetDescriptionBorder(feature);
}
return internal... | [
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... | Sets the features description using the current image and the location of the feature stored in the feature.
If the feature is an illegal location and cannot be set then false is returned.
@param feature Feature description which is to be set. Location must be specified.
@return true if the feature's description was m... | [
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lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/tracker/klt/KltTracker.java | KltTracker.internalSetDescriptionBorder | protected boolean internalSetDescriptionBorder(KltFeature feature) {
computeSubImageBounds(feature, feature.x, feature.y);
ImageMiscOps.fill(feature.desc, Float.NaN);
feature.desc.subimage(dstX0, dstY0, dstX1, dstY1, subimage);
interpInput.setImage(image);
interpInput.region(srcX0, srcY0, subimage);
feat... | java | protected boolean internalSetDescriptionBorder(KltFeature feature) {
computeSubImageBounds(feature, feature.x, feature.y);
ImageMiscOps.fill(feature.desc, Float.NaN);
feature.desc.subimage(dstX0, dstY0, dstX1, dstY1, subimage);
interpInput.setImage(image);
interpInput.region(srcX0, srcY0, subimage);
feat... | [
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is save the pixel value, but derivative information is also computed
so that it can reject bad features immediately. | [
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