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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
49,800 | lessthanoptimal/BoofCV | main/boofcv-sfm/src/main/java/boofcv/alg/sfm/d3/direct/VisOdomDirectColorDepth.java | VisOdomDirectColorDepth.setInterpolation | public void setInterpolation( double inputMin , double inputMax, double derivMin , double derivMax ,
InterpolationType type) {
interpI = FactoryInterpolation.createPixelS(inputMin,inputMax,type, BorderType.EXTENDED, imageType.getImageClass());
interpDX = FactoryInterpolation.createPixelS(derivMin,derivMax... | java | public void setInterpolation( double inputMin , double inputMax, double derivMin , double derivMax ,
InterpolationType type) {
interpI = FactoryInterpolation.createPixelS(inputMin,inputMax,type, BorderType.EXTENDED, imageType.getImageClass());
interpDX = FactoryInterpolation.createPixelS(derivMin,derivMax... | [
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@param inputMin min value for input pixels. 0 is typical
@param inputMax max value for input pixels. 255 is typical
@param derivMin min value for the derivative of input pixels
@param derivMax max value for the derivative of input pixels
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49,801 | lessthanoptimal/BoofCV | main/boofcv-sfm/src/main/java/boofcv/alg/sfm/d3/direct/VisOdomDirectColorDepth.java | VisOdomDirectColorDepth.setKeyFrame | void setKeyFrame(Planar<I> input, ImagePixelTo3D pixelTo3D) {
InputSanityCheck.checkSameShape(derivX,input);
wrapI.wrap(input);
keypixels.reset();
for (int y = 0; y < input.height; y++) {
for (int x = 0; x < input.width; x++) {
// See if there's a valid 3D point at this location
if( !pixelTo3D.proce... | java | void setKeyFrame(Planar<I> input, ImagePixelTo3D pixelTo3D) {
InputSanityCheck.checkSameShape(derivX,input);
wrapI.wrap(input);
keypixels.reset();
for (int y = 0; y < input.height; y++) {
for (int x = 0; x < input.width; x++) {
// See if there's a valid 3D point at this location
if( !pixelTo3D.proce... | [
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@param input Image which is to be used as the key frame
@param pixelTo3D Used to compute 3D points from pixels in key frame | [
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49,802 | lessthanoptimal/BoofCV | main/boofcv-sfm/src/main/java/boofcv/alg/sfm/d3/direct/VisOdomDirectColorDepth.java | VisOdomDirectColorDepth.computeFeatureDiversity | public double computeFeatureDiversity(Se3_F32 keyToCurrent ) {
diversity.reset();
for (int i = 0; i < keypixels.size(); i++) {
Pixel p = keypixels.data[i];
if( !p.valid )
continue;
SePointOps_F32.transform(keyToCurrent, p.p3, S);
diversity.addPoint(S.x, S.y, S.z);
}
diversity.process();
re... | java | public double computeFeatureDiversity(Se3_F32 keyToCurrent ) {
diversity.reset();
for (int i = 0; i < keypixels.size(); i++) {
Pixel p = keypixels.data[i];
if( !p.valid )
continue;
SePointOps_F32.transform(keyToCurrent, p.p3, S);
diversity.addPoint(S.x, S.y, S.z);
}
diversity.process();
re... | [
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49,803 | lessthanoptimal/BoofCV | main/boofcv-sfm/src/main/java/boofcv/alg/sfm/d3/direct/VisOdomDirectColorDepth.java | VisOdomDirectColorDepth.estimateMotion | public boolean estimateMotion(Planar<I> input , Se3_F32 hintKeyToInput ) {
InputSanityCheck.checkSameShape(derivX,input);
initMotion(input);
keyToCurrent.set(hintKeyToInput);
boolean foundSolution = false;
float previousError = Float.MAX_VALUE;
for (int i = 0; i < maxIterations; i++) {
constructLinearS... | java | public boolean estimateMotion(Planar<I> input , Se3_F32 hintKeyToInput ) {
InputSanityCheck.checkSameShape(derivX,input);
initMotion(input);
keyToCurrent.set(hintKeyToInput);
boolean foundSolution = false;
float previousError = Float.MAX_VALUE;
for (int i = 0; i < maxIterations; i++) {
constructLinearS... | [
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@param input Next image in the sequence
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49,804 | lessthanoptimal/BoofCV | main/boofcv-sfm/src/main/java/boofcv/alg/sfm/d3/direct/VisOdomDirectColorDepth.java | VisOdomDirectColorDepth.initMotion | void initMotion(Planar<I> input) {
if( solver == null ) {
solver = LinearSolverFactory_DDRM.qr(input.width*input.height*input.getNumBands(),6);
}
// compute image derivative and setup interpolation functions
computeD.process(input,derivX,derivY);
} | java | void initMotion(Planar<I> input) {
if( solver == null ) {
solver = LinearSolverFactory_DDRM.qr(input.width*input.height*input.getNumBands(),6);
}
// compute image derivative and setup interpolation functions
computeD.process(input,derivX,derivY);
} | [
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49,805 | lessthanoptimal/BoofCV | main/boofcv-geo/src/main/java/boofcv/alg/geo/f/EssentialNister5.java | EssentialNister5.process | public boolean process( List<AssociatedPair> points , FastQueue<DMatrixRMaj> solutions ) {
if( points.size() != 5 )
throw new IllegalArgumentException("Exactly 5 points are required, not "+points.size());
solutions.reset();
// Computes the 4-vector span which contains E. See equations 7-9
computeSpan(point... | java | public boolean process( List<AssociatedPair> points , FastQueue<DMatrixRMaj> solutions ) {
if( points.size() != 5 )
throw new IllegalArgumentException("Exactly 5 points are required, not "+points.size());
solutions.reset();
// Computes the 4-vector span which contains E. See equations 7-9
computeSpan(point... | [
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@param points Input: List of points correspondences in normalized image coordinates
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49,806 | lessthanoptimal/BoofCV | main/boofcv-geo/src/main/java/boofcv/alg/geo/f/EssentialNister5.java | EssentialNister5.solveForXandY | private void solveForXandY( double z ) {
this.z = z;
// solve for x and y using the first two rows of B
tmpA.data[0] = ((helper.K00*z + helper.K01)*z + helper.K02)*z + helper.K03;
tmpA.data[1] = ((helper.K04*z + helper.K05)*z + helper.K06)*z + helper.K07;
tmpY.data[0] = (((helper.K08*z + helper.K09)*z + help... | java | private void solveForXandY( double z ) {
this.z = z;
// solve for x and y using the first two rows of B
tmpA.data[0] = ((helper.K00*z + helper.K01)*z + helper.K02)*z + helper.K03;
tmpA.data[1] = ((helper.K04*z + helper.K05)*z + helper.K06)*z + helper.K07;
tmpY.data[0] = (((helper.K08*z + helper.K09)*z + help... | [
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49,807 | lessthanoptimal/BoofCV | main/boofcv-sfm/src/main/java/boofcv/alg/feature/associate/StereoConsistencyCheck.java | StereoConsistencyCheck.checkPixel | public boolean checkPixel( Point2D_F64 left , Point2D_F64 right ) {
leftImageToRect.compute(left.x,left.y,rectLeft);
rightImageToRect.compute(right.x, right.y, rectRight);
return checkRectified(rectLeft,rectRight);
} | java | public boolean checkPixel( Point2D_F64 left , Point2D_F64 right ) {
leftImageToRect.compute(left.x,left.y,rectLeft);
rightImageToRect.compute(right.x, right.y, rectRight);
return checkRectified(rectLeft,rectRight);
} | [
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49,808 | lessthanoptimal/BoofCV | main/boofcv-sfm/src/main/java/boofcv/alg/feature/associate/StereoConsistencyCheck.java | StereoConsistencyCheck.checkRectified | public boolean checkRectified( Point2D_F64 left , Point2D_F64 right ) {
// rectifications should make them appear along the same y-coordinate/epipolar line
if( Math.abs(left.y - right.y) > toleranceY )
return false;
// features in the right camera should appear left of features in the image image
return rig... | java | public boolean checkRectified( Point2D_F64 left , Point2D_F64 right ) {
// rectifications should make them appear along the same y-coordinate/epipolar line
if( Math.abs(left.y - right.y) > toleranceY )
return false;
// features in the right camera should appear left of features in the image image
return rig... | [
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49,809 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/factory/feature/describe/FactoryDescribePointAlgs.java | FactoryDescribePointAlgs.briefso | public static <T extends ImageGray<T>>
DescribePointBriefSO<T> briefso(BinaryCompareDefinition_I32 definition, BlurFilter<T> filterBlur) {
Class<T> imageType = filterBlur.getInputType().getImageClass();
InterpolatePixelS<T> interp = FactoryInterpolation.bilinearPixelS(imageType, BorderType.EXTENDED);
return ne... | java | public static <T extends ImageGray<T>>
DescribePointBriefSO<T> briefso(BinaryCompareDefinition_I32 definition, BlurFilter<T> filterBlur) {
Class<T> imageType = filterBlur.getInputType().getImageClass();
InterpolatePixelS<T> interp = FactoryInterpolation.bilinearPixelS(imageType, BorderType.EXTENDED);
return ne... | [
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49,810 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/tld/TldVarianceFilter.java | TldVarianceFilter.checkVariance | public boolean checkVariance( ImageRectangle r ) {
double sigma2 = computeVariance(r.x0,r.y0,r.x1,r.y1);
return sigma2 >= thresholdLower;
} | java | public boolean checkVariance( ImageRectangle r ) {
double sigma2 = computeVariance(r.x0,r.y0,r.x1,r.y1);
return sigma2 >= thresholdLower;
} | [
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49,811 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/tld/TldVarianceFilter.java | TldVarianceFilter.computeVariance | protected double computeVariance(int x0, int y0, int x1, int y1) {
// can use unsafe operations here since x0 > 0 and y0 > 0
double square = GIntegralImageOps.block_unsafe(integralSq, x0 - 1, y0 - 1, x1 - 1, y1 - 1);
double area = (x1-x0)*(y1-y0);
double mean = GIntegralImageOps.block_unsafe(integral, x0 - 1, ... | java | protected double computeVariance(int x0, int y0, int x1, int y1) {
// can use unsafe operations here since x0 > 0 and y0 > 0
double square = GIntegralImageOps.block_unsafe(integralSq, x0 - 1, y0 - 1, x1 - 1, y1 - 1);
double area = (x1-x0)*(y1-y0);
double mean = GIntegralImageOps.block_unsafe(integral, x0 - 1, ... | [
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49,812 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/tld/TldVarianceFilter.java | TldVarianceFilter.computeVarianceSafe | protected double computeVarianceSafe(int x0, int y0, int x1, int y1) {
// can use unsafe operations here since x0 > 0 and y0 > 0
double square = GIntegralImageOps.block_zero(integralSq, x0 - 1, y0 - 1, x1 - 1, y1 - 1);
double area = (x1-x0)*(y1-y0);
double mean = GIntegralImageOps.block_zero(integral, x0 - 1, ... | java | protected double computeVarianceSafe(int x0, int y0, int x1, int y1) {
// can use unsafe operations here since x0 > 0 and y0 > 0
double square = GIntegralImageOps.block_zero(integralSq, x0 - 1, y0 - 1, x1 - 1, y1 - 1);
double area = (x1-x0)*(y1-y0);
double mean = GIntegralImageOps.block_zero(integral, x0 - 1, ... | [
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49,813 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/tld/TldVarianceFilter.java | TldVarianceFilter.transformSq | public static void transformSq(final GrayU8 input , final GrayS64 transformed )
{
int indexSrc = input.startIndex;
int indexDst = transformed.startIndex;
int end = indexSrc + input.width;
long total = 0;
for( ; indexSrc < end; indexSrc++ ) {
int value = input.data[indexSrc]& 0xFF;
transformed.data[ind... | java | public static void transformSq(final GrayU8 input , final GrayS64 transformed )
{
int indexSrc = input.startIndex;
int indexDst = transformed.startIndex;
int end = indexSrc + input.width;
long total = 0;
for( ; indexSrc < end; indexSrc++ ) {
int value = input.data[indexSrc]& 0xFF;
transformed.data[ind... | [
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49,814 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/tld/TldVarianceFilter.java | TldVarianceFilter.transformSq | public static void transformSq(final GrayF32 input , final GrayF64 transformed )
{
int indexSrc = input.startIndex;
int indexDst = transformed.startIndex;
int end = indexSrc + input.width;
double total = 0;
for( ; indexSrc < end; indexSrc++ ) {
float value = input.data[indexSrc];
transformed.data[inde... | java | public static void transformSq(final GrayF32 input , final GrayF64 transformed )
{
int indexSrc = input.startIndex;
int indexDst = transformed.startIndex;
int end = indexSrc + input.width;
double total = 0;
for( ; indexSrc < end; indexSrc++ ) {
float value = input.data[indexSrc];
transformed.data[inde... | [
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49,815 | lessthanoptimal/BoofCV | main/boofcv-geo/src/main/java/boofcv/alg/geo/triangulate/TriangulateProjectiveLinearDLT.java | TriangulateProjectiveLinearDLT.addView | private int addView( DMatrixRMaj P , Point2D_F64 a , int index ) {
final double sx = stats.stdX, sy = stats.stdY;
// final double cx = stats.meanX, cy = stats.meanY;
// Easier to read the code when P is broken up this way
double r11 = P.data[0], r12 = P.data[1], r13 = P.data[2], r14=P.data[3];
double r21 =... | java | private int addView( DMatrixRMaj P , Point2D_F64 a , int index ) {
final double sx = stats.stdX, sy = stats.stdY;
// final double cx = stats.meanX, cy = stats.meanY;
// Easier to read the code when P is broken up this way
double r11 = P.data[0], r12 = P.data[1], r13 = P.data[2], r14=P.data[3];
double r21 =... | [
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49,816 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/tld/TldDetection.java | TldDetection.detectionCascade | protected void detectionCascade( FastQueue<ImageRectangle> cascadeRegions ) {
// initialize data structures
success = false;
ambiguous = false;
best = null;
candidateDetections.reset();
localMaximums.reset();
ambiguousRegions.clear();
storageMetric.reset();
storageIndexes.reset();
storageRect.clea... | java | protected void detectionCascade( FastQueue<ImageRectangle> cascadeRegions ) {
// initialize data structures
success = false;
ambiguous = false;
best = null;
candidateDetections.reset();
localMaximums.reset();
ambiguousRegions.clear();
storageMetric.reset();
storageIndexes.reset();
storageRect.clea... | [
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49,817 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/tld/TldDetection.java | TldDetection.computeTemplateConfidence | protected void computeTemplateConfidence() {
double max = 0;
for( int i = 0; i < fernRegions.size(); i++ ) {
ImageRectangle region = fernRegions.get(i);
double confidence = template.computeConfidence(region);
max = Math.max(max,confidence);
if( confidence < config.confidenceThresholdUpper)
contin... | java | protected void computeTemplateConfidence() {
double max = 0;
for( int i = 0; i < fernRegions.size(); i++ ) {
ImageRectangle region = fernRegions.get(i);
double confidence = template.computeConfidence(region);
max = Math.max(max,confidence);
if( confidence < config.confidenceThresholdUpper)
contin... | [
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49,818 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/tld/TldDetection.java | TldDetection.selectBestRegionsFern | protected void selectBestRegionsFern(double totalP, double totalN) {
for( int i = 0; i < fernInfo.size; i++ ) {
TldRegionFernInfo info = fernInfo.get(i);
double probP = info.sumP/totalP;
double probN = info.sumN/totalN;
// only consider regions with a higher P likelihood
if( probP > probN ) {
//... | java | protected void selectBestRegionsFern(double totalP, double totalN) {
for( int i = 0; i < fernInfo.size; i++ ) {
TldRegionFernInfo info = fernInfo.get(i);
double probP = info.sumP/totalP;
double probN = info.sumN/totalN;
// only consider regions with a higher P likelihood
if( probP > probN ) {
//... | [
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the sumP and sumN are needed for image conditional probability
NOTE: This is a big change from the original paper | [
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49,819 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/tracker/klt/PyramidKltTracker.java | PyramidKltTracker.setImage | public void setImage(ImagePyramid<InputImage> image,
DerivativeImage[] derivX, DerivativeImage[] derivY) {
if( image.getNumLayers() != derivX.length || image.getNumLayers() != derivY.length )
throw new IllegalArgumentException("Number of layers does not match.");
this.image = image;
this.derivX = deriv... | java | public void setImage(ImagePyramid<InputImage> image,
DerivativeImage[] derivX, DerivativeImage[] derivY) {
if( image.getNumLayers() != derivX.length || image.getNumLayers() != derivY.length )
throw new IllegalArgumentException("Number of layers does not match.");
this.image = image;
this.derivX = deriv... | [
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@param image Original image pyramid.
@param derivX Derivative along x-axis.
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49,820 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/tracker/klt/PyramidKltTracker.java | PyramidKltTracker.setImage | public void setImage(ImagePyramid<InputImage> image ) {
this.image = image;
this.derivX = null;
this.derivY = null;
} | java | public void setImage(ImagePyramid<InputImage> image ) {
this.image = image;
this.derivX = null;
this.derivY = null;
} | [
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@param image Image pyramid | [
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49,821 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/alg/enhance/EnhanceImageOps.java | EnhanceImageOps.equalize | public static void equalize( int histogram[] , int transform[] ) {
int sum = 0;
for( int i = 0; i < histogram.length; i++ ) {
transform[i] = sum += histogram[i];
}
int maxValue = histogram.length-1;
for( int i = 0; i < histogram.length; i++ ) {
transform[i] = (transform[i]*maxValue)/sum;
}
} | java | public static void equalize( int histogram[] , int transform[] ) {
int sum = 0;
for( int i = 0; i < histogram.length; i++ ) {
transform[i] = sum += histogram[i];
}
int maxValue = histogram.length-1;
for( int i = 0; i < histogram.length; i++ ) {
transform[i] = (transform[i]*maxValue)/sum;
}
} | [
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49,822 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/alg/enhance/EnhanceImageOps.java | EnhanceImageOps.sharpen8 | public static void sharpen8(GrayU8 input , GrayU8 output ) {
InputSanityCheck.checkSameShape(input, output);
if( BoofConcurrency.USE_CONCURRENT ) {
ImplEnhanceFilter_MT.sharpenInner8(input,output,0,255);
ImplEnhanceFilter_MT.sharpenBorder8(input,output,0,255);
} else {
ImplEnhanceFilter.sharpenInner8(in... | java | public static void sharpen8(GrayU8 input , GrayU8 output ) {
InputSanityCheck.checkSameShape(input, output);
if( BoofConcurrency.USE_CONCURRENT ) {
ImplEnhanceFilter_MT.sharpenInner8(input,output,0,255);
ImplEnhanceFilter_MT.sharpenBorder8(input,output,0,255);
} else {
ImplEnhanceFilter.sharpenInner8(in... | [
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49,823 | lessthanoptimal/BoofCV | main/boofcv-geo/src/main/java/boofcv/abst/feature/tracker/DetectDescribeAssociateTwoPass.java | DetectDescribeAssociateTwoPass.updateTrackLocation | protected void updateTrackLocation( SetTrackInfo<Desc> info, FastQueue<AssociatedIndex> matches) {
info.matches.resize(matches.size);
for (int i = 0; i < matches.size; i++) {
info.matches.get(i).set(matches.get(i));
}
tracksActive.clear();
for( int i = 0; i < info.matches.size; i++ ) {
AssociatedIndex ... | java | protected void updateTrackLocation( SetTrackInfo<Desc> info, FastQueue<AssociatedIndex> matches) {
info.matches.resize(matches.size);
for (int i = 0; i < matches.size; i++) {
info.matches.get(i).set(matches.get(i));
}
tracksActive.clear();
for( int i = 0; i < info.matches.size; i++ ) {
AssociatedIndex ... | [
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49,824 | lessthanoptimal/BoofCV | main/boofcv-feature/src/experimental/java/boofcv/alg/descriptor/ExperimentalDescriptorDistance.java | ExperimentalDescriptorDistance.hamming | public static int hamming(TupleDesc_B a, TupleDesc_B b ) {
int score = 0;
final int N = a.data.length;
for( int i = 0; i < N; i++ ) {
score += hamming(a.data[i] ^ b.data[i]);
}
return score;
} | java | public static int hamming(TupleDesc_B a, TupleDesc_B b ) {
int score = 0;
final int N = a.data.length;
for( int i = 0; i < N; i++ ) {
score += hamming(a.data[i] ^ b.data[i]);
}
return score;
} | [
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49,825 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/alg/filter/derivative/impl/GradientThree_Share.java | GradientThree_Share.derivX_F32 | public static void derivX_F32(GrayF32 orig,
GrayF32 derivX) {
final float[] data = orig.data;
final float[] imgX = derivX.data;
final int width = orig.getWidth();
final int height = orig.getHeight();
for (int y = 0; y < height; y++) {
int index = width * y + 1;
int endX = index + width - 2;
... | java | public static void derivX_F32(GrayF32 orig,
GrayF32 derivX) {
final float[] data = orig.data;
final float[] imgX = derivX.data;
final int width = orig.getWidth();
final int height = orig.getHeight();
for (int y = 0; y < height; y++) {
int index = width * y + 1;
int endX = index + width - 2;
... | [
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49,826 | lessthanoptimal/BoofCV | main/boofcv-geo/src/main/java/boofcv/abst/feature/tracker/DetectDescribeAssociate.java | DetectDescribeAssociate.pruneTracks | private void pruneTracks(SetTrackInfo<Desc> info, GrowQueue_I32 unassociated) {
if( unassociated.size > maxInactiveTracks ) {
// make the first N elements the ones which will be dropped
int numDrop = unassociated.size-maxInactiveTracks;
for (int i = 0; i < numDrop; i++) {
int selected = rand.nextInt(unas... | java | private void pruneTracks(SetTrackInfo<Desc> info, GrowQueue_I32 unassociated) {
if( unassociated.size > maxInactiveTracks ) {
// make the first N elements the ones which will be dropped
int numDrop = unassociated.size-maxInactiveTracks;
for (int i = 0; i < numDrop; i++) {
int selected = rand.nextInt(unas... | [
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49,827 | lessthanoptimal/BoofCV | main/boofcv-geo/src/main/java/boofcv/abst/feature/tracker/DetectDescribeAssociate.java | DetectDescribeAssociate.putIntoSrcList | protected void putIntoSrcList( SetTrackInfo<Desc> info ) {
// make sure isAssociated is large enough
if( info.isAssociated.length < info.tracks.size() ) {
info.isAssociated = new boolean[ info.tracks.size() ];
}
info.featSrc.reset();
info.locSrc.reset();
for( int i = 0; i < info.tracks.size(); i++ ) {
... | java | protected void putIntoSrcList( SetTrackInfo<Desc> info ) {
// make sure isAssociated is large enough
if( info.isAssociated.length < info.tracks.size() ) {
info.isAssociated = new boolean[ info.tracks.size() ];
}
info.featSrc.reset();
info.locSrc.reset();
for( int i = 0; i < info.tracks.size(); i++ ) {
... | [
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49,828 | lessthanoptimal/BoofCV | main/boofcv-geo/src/main/java/boofcv/abst/feature/tracker/DetectDescribeAssociate.java | DetectDescribeAssociate.spawnTracks | @Override
public void spawnTracks() {
for (int setIndex = 0; setIndex < sets.length; setIndex++) {
SetTrackInfo<Desc> info = sets[setIndex];
// setup data structures
if( info.isAssociated.length < info.featDst.size ) {
info.isAssociated = new boolean[ info.featDst.size ];
}
// see which features... | java | @Override
public void spawnTracks() {
for (int setIndex = 0; setIndex < sets.length; setIndex++) {
SetTrackInfo<Desc> info = sets[setIndex];
// setup data structures
if( info.isAssociated.length < info.featDst.size ) {
info.isAssociated = new boolean[ info.featDst.size ];
}
// see which features... | [
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49,829 | lessthanoptimal/BoofCV | main/boofcv-geo/src/main/java/boofcv/abst/feature/tracker/DetectDescribeAssociate.java | DetectDescribeAssociate.addNewTrack | protected PointTrack addNewTrack( int setIndex, double x , double y , Desc desc ) {
PointTrack p = getUnused();
p.set(x, y);
((Desc)p.getDescription()).setTo(desc);
if( checkValidSpawn(setIndex,p) ) {
p.setId = setIndex;
p.featureId = featureID++;
sets[setIndex].tracks.add(p);
tracksNew.add(p);
... | java | protected PointTrack addNewTrack( int setIndex, double x , double y , Desc desc ) {
PointTrack p = getUnused();
p.set(x, y);
((Desc)p.getDescription()).setTo(desc);
if( checkValidSpawn(setIndex,p) ) {
p.setId = setIndex;
p.featureId = featureID++;
sets[setIndex].tracks.add(p);
tracksNew.add(p);
... | [
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49,830 | lessthanoptimal/BoofCV | main/boofcv-geo/src/main/java/boofcv/abst/feature/tracker/DetectDescribeAssociate.java | DetectDescribeAssociate.getUnused | protected PointTrack getUnused() {
PointTrack p;
if( unused.size() > 0 ) {
p = unused.remove( unused.size()-1 );
} else {
p = new PointTrack();
p.setDescription(manager.createDescription());
}
return p;
} | java | protected PointTrack getUnused() {
PointTrack p;
if( unused.size() > 0 ) {
p = unused.remove( unused.size()-1 );
} else {
p = new PointTrack();
p.setDescription(manager.createDescription());
}
return p;
} | [
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49,831 | lessthanoptimal/BoofCV | main/boofcv-geo/src/main/java/boofcv/abst/feature/tracker/DetectDescribeAssociate.java | DetectDescribeAssociate.dropTrack | @Override
public boolean dropTrack(PointTrack track) {
if( !tracksAll.remove(track) )
return false;
if( !sets[track.setId].tracks.remove(track) ) {
return false;
}
// the track may or may not be in the active list
tracksActive.remove(track);
tracksInactive.remove(track);
// it must be in the all l... | java | @Override
public boolean dropTrack(PointTrack track) {
if( !tracksAll.remove(track) )
return false;
if( !sets[track.setId].tracks.remove(track) ) {
return false;
}
// the track may or may not be in the active list
tracksActive.remove(track);
tracksInactive.remove(track);
// it must be in the all l... | [
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49,832 | lessthanoptimal/BoofCV | main/boofcv-sfm/src/main/java/boofcv/alg/geo/pose/PnPStereoJacobianRodrigues.java | PnPStereoJacobianRodrigues.addRodriguesJacobian | private void addRodriguesJacobian( DMatrixRMaj Rj , Point3D_F64 worldPt , Point3D_F64 cameraPt )
{
// (1/z)*dot(R)*X
double Rx = (Rj.data[0]*worldPt.x + Rj.data[1]*worldPt.y + Rj.data[2]*worldPt.z)/cameraPt.z;
double Ry = (Rj.data[3]*worldPt.x + Rj.data[4]*worldPt.y + Rj.data[5]*worldPt.z)/cameraPt.z;
// dot(... | java | private void addRodriguesJacobian( DMatrixRMaj Rj , Point3D_F64 worldPt , Point3D_F64 cameraPt )
{
// (1/z)*dot(R)*X
double Rx = (Rj.data[0]*worldPt.x + Rj.data[1]*worldPt.y + Rj.data[2]*worldPt.z)/cameraPt.z;
double Ry = (Rj.data[3]*worldPt.x + Rj.data[4]*worldPt.y + Rj.data[5]*worldPt.z)/cameraPt.z;
// dot(... | [
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where R is rotation matrix, T is translation, z = z-coordinate of point in camera frame
@param Rj Jacobian for Rodrigues
@param worldPt Location of point in world coordinates
@param camer... | [
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49,833 | lessthanoptimal/BoofCV | main/boofcv-sfm/src/main/java/boofcv/alg/geo/pose/PnPStereoJacobianRodrigues.java | PnPStereoJacobianRodrigues.addTranslationJacobian | private void addTranslationJacobian( Point3D_F64 cameraPt )
{
double divZ = 1.0/cameraPt.z;
double divZ2 = 1.0/(cameraPt.z*cameraPt.z);
// partial T.x
output[indexX++] = divZ;
output[indexY++] = 0;
// partial T.y
output[indexX++] = 0;
output[indexY++] = divZ;
// partial T.z
output[indexX++] = -cam... | java | private void addTranslationJacobian( Point3D_F64 cameraPt )
{
double divZ = 1.0/cameraPt.z;
double divZ2 = 1.0/(cameraPt.z*cameraPt.z);
// partial T.x
output[indexX++] = divZ;
output[indexY++] = 0;
// partial T.y
output[indexX++] = 0;
output[indexY++] = divZ;
// partial T.z
output[indexX++] = -cam... | [
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49,834 | lessthanoptimal/BoofCV | main/boofcv-sfm/src/main/java/boofcv/alg/geo/pose/PnPStereoJacobianRodrigues.java | PnPStereoJacobianRodrigues.addTranslationJacobian | private void addTranslationJacobian( DMatrixRMaj R ,
Point3D_F64 cameraPt )
{
double z = cameraPt.z;
double z2 = z*z;
// partial T.x
output[indexX++] = R.get(0,0)/cameraPt.z - R.get(2,0)/z2*cameraPt.x;
output[indexY++] = R.get(1,0)/cameraPt.z - R.get(2,0)/z2*cameraPt.y;
// partial T.y
output[... | java | private void addTranslationJacobian( DMatrixRMaj R ,
Point3D_F64 cameraPt )
{
double z = cameraPt.z;
double z2 = z*z;
// partial T.x
output[indexX++] = R.get(0,0)/cameraPt.z - R.get(2,0)/z2*cameraPt.x;
output[indexY++] = R.get(1,0)/cameraPt.z - R.get(2,0)/z2*cameraPt.y;
// partial T.y
output[... | [
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49,835 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/alg/denoise/wavelet/UtilDenoiseWavelet.java | UtilDenoiseWavelet.subbandAbsVal | public static float[] subbandAbsVal(GrayF32 subband, float[] coef ) {
if( coef == null ) {
coef = new float[subband.width*subband.height];
}
int i = 0;
for( int y = 0; y < subband.height; y++ ) {
int index = subband.startIndex + subband.stride*y;
int end = index + subband.width;
for( ;index < end;... | java | public static float[] subbandAbsVal(GrayF32 subband, float[] coef ) {
if( coef == null ) {
coef = new float[subband.width*subband.height];
}
int i = 0;
for( int y = 0; y < subband.height; y++ ) {
int index = subband.startIndex + subband.stride*y;
int end = index + subband.width;
for( ;index < end;... | [
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49,836 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/factory/filter/blur/FactoryBlurFilter.java | FactoryBlurFilter.median | public static <T extends ImageBase<T>> BlurStorageFilter<T> median(ImageType<T> type , int radius ) {
return new BlurStorageFilter<>("median", type, radius);
} | java | public static <T extends ImageBase<T>> BlurStorageFilter<T> median(ImageType<T> type , int radius ) {
return new BlurStorageFilter<>("median", type, radius);
} | [
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@param type Image type.
@param radius Size of the filter.
@return Median image filter. | [
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49,837 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/factory/filter/blur/FactoryBlurFilter.java | FactoryBlurFilter.mean | public static <T extends ImageBase<T>> BlurStorageFilter<T> mean(ImageType<T> type , int radius ) {
return new BlurStorageFilter<>("mean", type, radius);
} | java | public static <T extends ImageBase<T>> BlurStorageFilter<T> mean(ImageType<T> type , int radius ) {
return new BlurStorageFilter<>("mean", type, radius);
} | [
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49,838 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/factory/filter/blur/FactoryBlurFilter.java | FactoryBlurFilter.gaussian | public static <T extends ImageBase<T>> BlurStorageFilter<T> gaussian(ImageType<T> type , double sigma , int radius ) {
return new BlurStorageFilter<>("gaussian", type, sigma, radius);
} | java | public static <T extends ImageBase<T>> BlurStorageFilter<T> gaussian(ImageType<T> type , double sigma , int radius ) {
return new BlurStorageFilter<>("gaussian", type, sigma, radius);
} | [
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49,839 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/circulant/CirculantTracker.java | CirculantTracker.initialize | public void initialize( T image , int x0 , int y0 , int regionWidth , int regionHeight ) {
this.imageWidth = image.width;
this.imageHeight = image.height;
setTrackLocation(x0,y0,regionWidth,regionHeight);
initialLearning(image);
} | java | public void initialize( T image , int x0 , int y0 , int regionWidth , int regionHeight ) {
this.imageWidth = image.width;
this.imageHeight = image.height;
setTrackLocation(x0,y0,regionWidth,regionHeight);
initialLearning(image);
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@param image Image to start tracking from
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49,840 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/circulant/CirculantTracker.java | CirculantTracker.setTrackLocation | public void setTrackLocation( int x0 , int y0 , int regionWidth , int regionHeight ) {
if( imageWidth < regionWidth || imageHeight < regionHeight)
throw new IllegalArgumentException("Track region is larger than input image: "+regionWidth+" "+regionHeight);
regionOut.width = regionWidth;
regionOut.height = reg... | java | public void setTrackLocation( int x0 , int y0 , int regionWidth , int regionHeight ) {
if( imageWidth < regionWidth || imageHeight < regionHeight)
throw new IllegalArgumentException("Track region is larger than input image: "+regionWidth+" "+regionHeight);
regionOut.width = regionWidth;
regionOut.height = reg... | [
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@param x0 top-left corner of region
@param y0 top-left corner of region
@param regionWidth region's width
@param regionHeight region's height | [
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49,841 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/circulant/CirculantTracker.java | CirculantTracker.initialLearning | protected void initialLearning( T image ) {
// get subwindow at current estimated target position, to train classifier
get_subwindow(image, template);
// Kernel Regularized Least-Squares, calculate alphas (in Fourier domain)
// k = dense_gauss_kernel(sigma, x);
dense_gauss_kernel(sigma, template, template,k)... | java | protected void initialLearning( T image ) {
// get subwindow at current estimated target position, to train classifier
get_subwindow(image, template);
// Kernel Regularized Least-Squares, calculate alphas (in Fourier domain)
// k = dense_gauss_kernel(sigma, x);
dense_gauss_kernel(sigma, template, template,k)... | [
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49,842 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/circulant/CirculantTracker.java | CirculantTracker.computeCosineWindow | protected static void computeCosineWindow( GrayF64 cosine ) {
double cosX[] = new double[ cosine.width ];
for( int x = 0; x < cosine.width; x++ ) {
cosX[x] = 0.5*(1 - Math.cos( 2.0*Math.PI*x/(cosine.width-1) ));
}
for( int y = 0; y < cosine.height; y++ ) {
int index = cosine.startIndex + y*cosine.stride;
... | java | protected static void computeCosineWindow( GrayF64 cosine ) {
double cosX[] = new double[ cosine.width ];
for( int x = 0; x < cosine.width; x++ ) {
cosX[x] = 0.5*(1 - Math.cos( 2.0*Math.PI*x/(cosine.width-1) ));
}
for( int y = 0; y < cosine.height; y++ ) {
int index = cosine.startIndex + y*cosine.stride;
... | [
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49,843 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/circulant/CirculantTracker.java | CirculantTracker.computeGaussianWeights | protected void computeGaussianWeights( int width ) {
// desired output (gaussian shaped), bandwidth proportional to target size
double output_sigma = Math.sqrt(width*width) * output_sigma_factor;
double left = -0.5/(output_sigma*output_sigma);
int radius = width/2;
for( int y = 0; y < gaussianWeight.height... | java | protected void computeGaussianWeights( int width ) {
// desired output (gaussian shaped), bandwidth proportional to target size
double output_sigma = Math.sqrt(width*width) * output_sigma_factor;
double left = -0.5/(output_sigma*output_sigma);
int radius = width/2;
for( int y = 0; y < gaussianWeight.height... | [
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This isn't actually symmetric for even widths. These weights are used has label in the learning phase. Closer
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it will learn an incorrect model. | [
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49,844 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/circulant/CirculantTracker.java | CirculantTracker.performTracking | public void performTracking( T image ) {
if( image.width != imageWidth || image.height != imageHeight )
throw new IllegalArgumentException("Tracking image size is not the same as " +
"input image. Expected "+imageWidth+" x "+imageHeight);
updateTrackLocation(image);
if( interp_factor != 0 )
performLear... | java | public void performTracking( T image ) {
if( image.width != imageWidth || image.height != imageHeight )
throw new IllegalArgumentException("Tracking image size is not the same as " +
"input image. Expected "+imageWidth+" x "+imageHeight);
updateTrackLocation(image);
if( interp_factor != 0 )
performLear... | [
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49,845 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/circulant/CirculantTracker.java | CirculantTracker.updateTrackLocation | protected void updateTrackLocation(T image) {
get_subwindow(image, templateNew);
// calculate response of the classifier at all locations
// matlab: k = dense_gauss_kernel(sigma, x, z);
dense_gauss_kernel(sigma, templateNew, template,k);
fft.forward(k,kf);
// response = real(ifft2(alphaf .* fft2(k))); ... | java | protected void updateTrackLocation(T image) {
get_subwindow(image, templateNew);
// calculate response of the classifier at all locations
// matlab: k = dense_gauss_kernel(sigma, x, z);
dense_gauss_kernel(sigma, templateNew, template,k);
fft.forward(k,kf);
// response = real(ifft2(alphaf .* fft2(k))); ... | [
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49,846 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/circulant/CirculantTracker.java | CirculantTracker.subpixelPeak | protected void subpixelPeak(int peakX, int peakY) {
// this function for r was determined empirically by using work regions of 32,64,128
int r = Math.min(2,response.width/25);
if( r < 0 )
return;
localPeak.setSearchRadius(r);
localPeak.search(peakX,peakY);
offX = localPeak.getPeakX() - peakX;
offY = ... | java | protected void subpixelPeak(int peakX, int peakY) {
// this function for r was determined empirically by using work regions of 32,64,128
int r = Math.min(2,response.width/25);
if( r < 0 )
return;
localPeak.setSearchRadius(r);
localPeak.search(peakX,peakY);
offX = localPeak.getPeakX() - peakX;
offY = ... | [
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49,847 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/circulant/CirculantTracker.java | CirculantTracker.performLearning | public void performLearning(T image) {
// use the update track location
get_subwindow(image, templateNew);
// Kernel Regularized Least-Squares, calculate alphas (in Fourier domain)
// k = dense_gauss_kernel(sigma, x);
dense_gauss_kernel(sigma, templateNew, templateNew, k);
fft.forward(k,kf);
// new_alph... | java | public void performLearning(T image) {
// use the update track location
get_subwindow(image, templateNew);
// Kernel Regularized Least-Squares, calculate alphas (in Fourier domain)
// k = dense_gauss_kernel(sigma, x);
dense_gauss_kernel(sigma, templateNew, templateNew, k);
fft.forward(k,kf);
// new_alph... | [
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49,848 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/circulant/CirculantTracker.java | CirculantTracker.imageDotProduct | public static double imageDotProduct(GrayF64 a) {
double total = 0;
int N = a.width*a.height;
for( int index = 0; index < N; index++ ) {
double value = a.data[index];
total += value*value;
}
return total;
} | java | public static double imageDotProduct(GrayF64 a) {
double total = 0;
int N = a.width*a.height;
for( int index = 0; index < N; index++ ) {
double value = a.data[index];
total += value*value;
}
return total;
} | [
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49,849 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/circulant/CirculantTracker.java | CirculantTracker.elementMultConjB | public static void elementMultConjB( InterleavedF64 a , InterleavedF64 b , InterleavedF64 output ) {
for( int y = 0; y < a.height; y++ ) {
int index = a.startIndex + y*a.stride;
for( int x = 0; x < a.width; x++, index += 2 ) {
double realA = a.data[index];
double imgA = a.data[index+1];
double re... | java | public static void elementMultConjB( InterleavedF64 a , InterleavedF64 b , InterleavedF64 output ) {
for( int y = 0; y < a.height; y++ ) {
int index = a.startIndex + y*a.stride;
for( int x = 0; x < a.width; x++, index += 2 ) {
double realA = a.data[index];
double imgA = a.data[index+1];
double re... | [
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49,850 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/circulant/CirculantTracker.java | CirculantTracker.gaussianKernel | protected static void gaussianKernel(double xx , double yy , GrayF64 xy , double sigma , GrayF64 output ) {
double sigma2 = sigma*sigma;
double N = xy.width*xy.height;
for( int y = 0; y < xy.height; y++ ) {
int index = xy.startIndex + y*xy.stride;
for( int x = 0; x < xy.width; x++ , index++ ) {
// (... | java | protected static void gaussianKernel(double xx , double yy , GrayF64 xy , double sigma , GrayF64 output ) {
double sigma2 = sigma*sigma;
double N = xy.width*xy.height;
for( int y = 0; y < xy.height; y++ ) {
int index = xy.startIndex + y*xy.stride;
for( int x = 0; x < xy.width; x++ , index++ ) {
// (... | [
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k = exp(-1 / sigma^2 * max(0, (xx + yy - 2 * xy) / numel(x)));
@param xx ||x||^2
@param yy ||y||^2 | [
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49,851 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/tracker/circulant/CirculantTracker.java | CirculantTracker.get_subwindow | protected void get_subwindow( T image , GrayF64 output ) {
// copy the target region
interp.setImage(image);
int index = 0;
for( int y = 0; y < workRegionSize; y++ ) {
float yy = regionTrack.y0 + y*stepY;
for( int x = 0; x < workRegionSize; x++ ) {
float xx = regionTrack.x0 + x*stepX;
if( inte... | java | protected void get_subwindow( T image , GrayF64 output ) {
// copy the target region
interp.setImage(image);
int index = 0;
for( int y = 0; y < workRegionSize; y++ ) {
float yy = regionTrack.y0 + y*stepY;
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49,852 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/alg/filter/binary/ThresholdBlock.java | ThresholdBlock.selectBlockSize | void selectBlockSize( int width , int height , int requestedBlockWidth) {
if( height < requestedBlockWidth ) {
blockHeight = height;
} else {
int rows = height/requestedBlockWidth;
blockHeight = height/rows;
}
if( width < requestedBlockWidth ) {
blockWidth = width;
} else {
int cols = width/r... | java | void selectBlockSize( int width , int height , int requestedBlockWidth) {
if( height < requestedBlockWidth ) {
blockHeight = height;
} else {
int rows = height/requestedBlockWidth;
blockHeight = height/rows;
}
if( width < requestedBlockWidth ) {
blockWidth = width;
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49,853 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/alg/filter/binary/ThresholdBlock.java | ThresholdBlock.applyThreshold | protected void applyThreshold( T input, GrayU8 output ) {
for (int blockY = 0; blockY < stats.height; blockY++) {
for (int blockX = 0; blockX < stats.width; blockX++) {
original.thresholdBlock(blockX,blockY,input,stats,output);
}
}
} | java | protected void applyThreshold( T input, GrayU8 output ) {
for (int blockY = 0; blockY < stats.height; blockY++) {
for (int blockX = 0; blockX < stats.width; blockX++) {
original.thresholdBlock(blockX,blockY,input,stats,output);
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49,854 | lessthanoptimal/BoofCV | main/boofcv-sfm/src/main/java/boofcv/alg/sfm/structure/PairwiseImageMatching.java | PairwiseImageMatching.addImage | public void addImage(T image , String cameraName ) {
PairwiseImageGraph.View view = new PairwiseImageGraph.View(graph.nodes.size(),
new FastQueue<TupleDesc>(TupleDesc.class,true) {
@Override
protected TupleDesc createInstance() {
return detDesc.createDescription();
}
});
view.camera =... | java | public void addImage(T image , String cameraName ) {
PairwiseImageGraph.View view = new PairwiseImageGraph.View(graph.nodes.size(),
new FastQueue<TupleDesc>(TupleDesc.class,true) {
@Override
protected TupleDesc createInstance() {
return detDesc.createDescription();
}
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49,855 | lessthanoptimal/BoofCV | main/boofcv-sfm/src/main/java/boofcv/alg/sfm/structure/PairwiseImageMatching.java | PairwiseImageMatching.connectViews | protected boolean connectViews(PairwiseImageGraph.View viewA , PairwiseImageGraph.View viewB ,
FastQueue<AssociatedIndex> matches) {
// Estimate fundamental/essential with RANSAC
PairwiseImageGraph.Motion edge = new PairwiseImageGraph.Motion();
int inliersEpipolar;
CameraPinhole pinhole0 = viewA.ca... | java | protected boolean connectViews(PairwiseImageGraph.View viewA , PairwiseImageGraph.View viewB ,
FastQueue<AssociatedIndex> matches) {
// Estimate fundamental/essential with RANSAC
PairwiseImageGraph.Motion edge = new PairwiseImageGraph.Motion();
int inliersEpipolar;
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49,856 | lessthanoptimal/BoofCV | main/boofcv-sfm/src/main/java/boofcv/alg/sfm/structure/PairwiseImageMatching.java | PairwiseImageMatching.fitEpipolar | boolean fitEpipolar(FastQueue<AssociatedIndex> matches ,
List<Point2D_F64> pointsA , List<Point2D_F64> pointsB ,
ModelMatcher<?,AssociatedPair> ransac ,
PairwiseImageGraph.Motion edge )
{
pairs.resize(matches.size);
for (int i = 0; i < matches.size; i++) {
AssociatedIndex a = matches.get(i);
... | java | boolean fitEpipolar(FastQueue<AssociatedIndex> matches ,
List<Point2D_F64> pointsA , List<Point2D_F64> pointsB ,
ModelMatcher<?,AssociatedPair> ransac ,
PairwiseImageGraph.Motion edge )
{
pairs.resize(matches.size);
for (int i = 0; i < matches.size; i++) {
AssociatedIndex a = matches.get(i);
... | [
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49,857 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/shapes/polygon/DetectPolygonFromContour.java | DetectPolygonFromContour.process | public void process(T gray, GrayU8 binary) {
if( verbose ) System.out.println("ENTER DetectPolygonFromContour.process()");
if( contourPadded != null && !contourPadded.isCreatePaddedCopy() ) {
int padding = 2;
if( gray.width+padding != binary.width || gray.height+padding != binary.height ) {
throw new Il... | java | public void process(T gray, GrayU8 binary) {
if( verbose ) System.out.println("ENTER DetectPolygonFromContour.process()");
if( contourPadded != null && !contourPadded.isCreatePaddedCopy() ) {
int padding = 2;
if( gray.width+padding != binary.width || gray.height+padding != binary.height ) {
throw new Il... | [
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49,858 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/shapes/polygon/DetectPolygonFromContour.java | DetectPolygonFromContour.determineCornersOnBorder | void determineCornersOnBorder( Polygon2D_F64 polygon , GrowQueue_B onImageBorder ) {
onImageBorder.reset();
for (int i = 0; i < polygon.size(); i++) {
Point2D_F64 p = polygon.get(i);
onImageBorder.add( p.x <= 1 || p.y <= 1 || p.x >= imageWidth-2 || p.y >= imageHeight-2);
}
} | java | void determineCornersOnBorder( Polygon2D_F64 polygon , GrowQueue_B onImageBorder ) {
onImageBorder.reset();
for (int i = 0; i < polygon.size(); i++) {
Point2D_F64 p = polygon.get(i);
onImageBorder.add( p.x <= 1 || p.y <= 1 || p.x >= imageWidth-2 || p.y >= imageHeight-2);
}
} | [
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49,859 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/shapes/polygon/DetectPolygonFromContour.java | DetectPolygonFromContour.getContour | public List<Point2D_I32> getContour( Info info ) {
contourTmp.reset();
contourFinder.loadContour(info.contour.externalIndex,contourTmp);
return contourTmp.toList();
} | java | public List<Point2D_I32> getContour( Info info ) {
contourTmp.reset();
contourFinder.loadContour(info.contour.externalIndex,contourTmp);
return contourTmp.toList();
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49,860 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/shapes/polygon/DetectPolygonFromContour.java | DetectPolygonFromContour.removeDistortionFromContour | private void removeDistortionFromContour(List<Point2D_I32> distorted , FastQueue<Point2D_I32> undistorted ) {
undistorted.reset();
for (int j = 0; j < distorted.size(); j++) {
// remove distortion
Point2D_I32 p = distorted.get(j);
Point2D_I32 q = undistorted.grow();
distToUndist.compute(p.x,p.y,disto... | java | private void removeDistortionFromContour(List<Point2D_I32> distorted , FastQueue<Point2D_I32> undistorted ) {
undistorted.reset();
for (int j = 0; j < distorted.size(); j++) {
// remove distortion
Point2D_I32 p = distorted.get(j);
Point2D_I32 q = undistorted.grow();
distToUndist.compute(p.x,p.y,disto... | [
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49,861 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/shapes/polygon/DetectPolygonFromContour.java | DetectPolygonFromContour.touchesBorder | protected final boolean touchesBorder( List<Point2D_I32> contour ) {
int endX = imageWidth-1;
int endY = imageHeight-1;
for (int j = 0; j < contour.size(); j++) {
Point2D_I32 p = contour.get(j);
if( p.x == 0 || p.y == 0 || p.x == endX || p.y == endY )
{
return true;
}
}
return false;
} | java | protected final boolean touchesBorder( List<Point2D_I32> contour ) {
int endX = imageWidth-1;
int endY = imageHeight-1;
for (int j = 0; j < contour.size(); j++) {
Point2D_I32 p = contour.get(j);
if( p.x == 0 || p.y == 0 || p.x == endX || p.y == endY )
{
return true;
}
}
return false;
} | [
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49,862 | lessthanoptimal/BoofCV | main/boofcv-geo/src/main/java/boofcv/alg/geo/NormalizedToPixelError.java | NormalizedToPixelError.set | public void set(double fx, double fy, double skew) {
this.fx = fx;
this.fy = fy;
this.skew = skew;
} | java | public void set(double fx, double fy, double skew) {
this.fx = fx;
this.fy = fy;
this.skew = skew;
} | [
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@param fy focal length y
@param skew camera skew | [
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49,863 | lessthanoptimal/BoofCV | examples/src/main/java/boofcv/examples/geometry/ExampleImageStitching.java | ExampleImageStitching.computeTransform | public static<T extends ImageGray<T>, FD extends TupleDesc> Homography2D_F64
computeTransform( T imageA , T imageB ,
DetectDescribePoint<T,FD> detDesc ,
AssociateDescription<FD> associate ,
ModelMatcher<Homography2D_F64,AssociatedPair> modelMatcher )
{
// get the length of the description
Lis... | java | public static<T extends ImageGray<T>, FD extends TupleDesc> Homography2D_F64
computeTransform( T imageA , T imageB ,
DetectDescribePoint<T,FD> detDesc ,
AssociateDescription<FD> associate ,
ModelMatcher<Homography2D_F64,AssociatedPair> modelMatcher )
{
// get the length of the description
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49,864 | lessthanoptimal/BoofCV | examples/src/main/java/boofcv/examples/geometry/ExampleImageStitching.java | ExampleImageStitching.stitch | public static <T extends ImageGray<T>>
void stitch( BufferedImage imageA , BufferedImage imageB , Class<T> imageType )
{
T inputA = ConvertBufferedImage.convertFromSingle(imageA, null, imageType);
T inputB = ConvertBufferedImage.convertFromSingle(imageB, null, imageType);
// Detect using the standard SURF feat... | java | public static <T extends ImageGray<T>>
void stitch( BufferedImage imageA , BufferedImage imageB , Class<T> imageType )
{
T inputA = ConvertBufferedImage.convertFromSingle(imageA, null, imageType);
T inputB = ConvertBufferedImage.convertFromSingle(imageB, null, imageType);
// Detect using the standard SURF feat... | [
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49,865 | lessthanoptimal/BoofCV | integration/boofcv-swing/src/main/java/boofcv/gui/d3/DisparityToColorPointCloud.java | DisparityToColorPointCloud.configure | public void configure(double baseline,
DMatrixRMaj K, DMatrixRMaj rectifiedR,
Point2Transform2_F64 rectifiedToColor,
int minDisparity, int maxDisparity) {
this.K = K;
ConvertMatrixData.convert(rectifiedR,this.rectifiedR);
this.rectifiedToColor = rectifiedToColor;
this.baseline = (float)b... | java | public void configure(double baseline,
DMatrixRMaj K, DMatrixRMaj rectifiedR,
Point2Transform2_F64 rectifiedToColor,
int minDisparity, int maxDisparity) {
this.K = K;
ConvertMatrixData.convert(rectifiedR,this.rectifiedR);
this.rectifiedToColor = rectifiedToColor;
this.baseline = (float)b... | [
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@param K Intrinsic camera calibration matrix of rectified camera
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49,866 | lessthanoptimal/BoofCV | integration/boofcv-swing/src/main/java/boofcv/gui/d3/DisparityToColorPointCloud.java | DisparityToColorPointCloud.process | public void process(ImageGray disparity , BufferedImage color ) {
cloudRgb.setMaxSize(disparity.width*disparity.height);
cloudXyz.setMaxSize(disparity.width*disparity.height*3);
cloudRgb.reset();
cloudXyz.reset();
if( disparity instanceof GrayU8)
process((GrayU8)disparity,color);
else
process((GrayF3... | java | public void process(ImageGray disparity , BufferedImage color ) {
cloudRgb.setMaxSize(disparity.width*disparity.height);
cloudXyz.setMaxSize(disparity.width*disparity.height*3);
cloudRgb.reset();
cloudXyz.reset();
if( disparity instanceof GrayU8)
process((GrayU8)disparity,color);
else
process((GrayF3... | [
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49,867 | lessthanoptimal/BoofCV | demonstrations/src/main/java/boofcv/demonstrations/feature/detect/ImageCorruptPanel.java | ImageCorruptPanel.corruptImage | public <T extends ImageGray<T>> void corruptImage(T original , T corrupted )
{
GGrayImageOps.stretch(original, valueScale, valueOffset, 255.0, corrupted);
GImageMiscOps.addGaussian(corrupted, rand, valueNoise, 0, 255);
GPixelMath.boundImage(corrupted,0,255);
} | java | public <T extends ImageGray<T>> void corruptImage(T original , T corrupted )
{
GGrayImageOps.stretch(original, valueScale, valueOffset, 255.0, corrupted);
GImageMiscOps.addGaussian(corrupted, rand, valueNoise, 0, 255);
GPixelMath.boundImage(corrupted,0,255);
} | [
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49,868 | lessthanoptimal/BoofCV | main/boofcv-geo/src/main/java/boofcv/alg/geo/h/AdjustHomographyMatrix.java | AdjustHomographyMatrix.findScaleH | protected boolean findScaleH( DMatrixRMaj H ) {
if( !svd.decompose(H) )
return false;
Arrays.sort(svd.getSingularValues(), 0, 3);
double scale = svd.getSingularValues()[1];
CommonOps_DDRM.divide(H,scale);
return true;
} | java | protected boolean findScaleH( DMatrixRMaj H ) {
if( !svd.decompose(H) )
return false;
Arrays.sort(svd.getSingularValues(), 0, 3);
double scale = svd.getSingularValues()[1];
CommonOps_DDRM.divide(H,scale);
return true;
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49,869 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/alg/transform/wavelet/impl/ImplWaveletTransformNaive.java | ImplWaveletTransformNaive.vertical | public static void vertical(BorderIndex1D border , WlCoef_I32 coefficients ,
GrayI input , GrayI output ) {
UtilWavelet.checkShape(input,output);
final int offsetA = coefficients.offsetScaling;
final int offsetB = coefficients.offsetWavelet;
final int[] alpha = coefficients.scaling;
final int[] beta... | java | public static void vertical(BorderIndex1D border , WlCoef_I32 coefficients ,
GrayI input , GrayI output ) {
UtilWavelet.checkShape(input,output);
final int offsetA = coefficients.offsetScaling;
final int offsetB = coefficients.offsetWavelet;
final int[] alpha = coefficients.scaling;
final int[] beta... | [
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49,870 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/factory/filter/convolve/FactoryConvolve.java | FactoryConvolve.convolve | public static <Input extends ImageBase<Input>, Output extends ImageBase<Output>>
ConvolveInterface<Input,Output>
convolve(Kernel1D kernel, ImageType<Input> inputType, ImageType<Output> outputType , BorderType border , boolean isHorizontal )
{
if( inputType.getFamily() != ImageType.Family.GRAY )
throw new Illega... | java | public static <Input extends ImageBase<Input>, Output extends ImageBase<Output>>
ConvolveInterface<Input,Output>
convolve(Kernel1D kernel, ImageType<Input> inputType, ImageType<Output> outputType , BorderType border , boolean isHorizontal )
{
if( inputType.getFamily() != ImageType.Family.GRAY )
throw new Illega... | [
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@param kernel Convolution kernel.
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49,871 | lessthanoptimal/BoofCV | main/boofcv-geo/src/main/java/boofcv/alg/distort/LensDistortionOps.java | LensDistortionOps.changeCameraModel | public static <T extends ImageBase<T>,O extends CameraPinhole, D extends CameraPinhole>
ImageDistort<T,T> changeCameraModel(AdjustmentType type, BorderType borderType,
O original,
D desired,
D modified,
ImageType<T> imageType)
{
Class bandType = imageType.getImageClass();
b... | java | public static <T extends ImageBase<T>,O extends CameraPinhole, D extends CameraPinhole>
ImageDistort<T,T> changeCameraModel(AdjustmentType type, BorderType borderType,
O original,
D desired,
D modified,
ImageType<T> imageType)
{
Class bandType = imageType.getImageClass();
b... | [
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49,872 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/alg/filter/binary/impl/ImplBinaryNaiveOps.java | ImplBinaryNaiveOps.getT | public static boolean getT(GrayU8 image, int x, int y) {
if (image.isInBounds(x, y)) {
return image.get(x, y) != 0;
} else {
return true;
}
} | java | public static boolean getT(GrayU8 image, int x, int y) {
if (image.isInBounds(x, y)) {
return image.get(x, y) != 0;
} else {
return true;
}
} | [
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49,873 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/alg/filter/binary/impl/ImplBinaryNaiveOps.java | ImplBinaryNaiveOps.getF | public static boolean getF(GrayU8 image, int x, int y) {
if (image.isInBounds(x, y)) {
return image.get(x, y) != 0;
} else {
return false;
}
} | java | public static boolean getF(GrayU8 image, int x, int y) {
if (image.isInBounds(x, y)) {
return image.get(x, y) != 0;
} else {
return false;
}
} | [
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49,874 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterToGrid.java | ChessboardCornerClusterToGrid.convert | public boolean convert( ChessboardCornerGraph cluster , GridInfo info ) {
// default to an invalid value to ensure a failure doesn't go unnoticed.
info.reset();
// Get the edges in a consistent order
if( !orderEdges(cluster) )
return false;
// Now we need to order the nodes into a proper grid which follo... | java | public boolean convert( ChessboardCornerGraph cluster , GridInfo info ) {
// default to an invalid value to ensure a failure doesn't go unnoticed.
info.reset();
// Get the edges in a consistent order
if( !orderEdges(cluster) )
return false;
// Now we need to order the nodes into a proper grid which follo... | [
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49,875 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterToGrid.java | ChessboardCornerClusterToGrid.selectCorner | int selectCorner( GridInfo info ) {
info.lookupGridCorners(cornerList);
int bestCorner = -1;
double bestScore = Double.MAX_VALUE;
boolean bestIsCornerSquare = false;
for (int i = 0; i < cornerList.size(); i++) {
Node n = cornerList.get(i);
boolean corner = isCornerValidOrigin(n);
// If there are... | java | int selectCorner( GridInfo info ) {
info.lookupGridCorners(cornerList);
int bestCorner = -1;
double bestScore = Double.MAX_VALUE;
boolean bestIsCornerSquare = false;
for (int i = 0; i < cornerList.size(); i++) {
Node n = cornerList.get(i);
boolean corner = isCornerValidOrigin(n);
// If there are... | [
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49,876 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterToGrid.java | ChessboardCornerClusterToGrid.orderNodes | boolean orderNodes( FastQueue<Node> corners , GridInfo info ) {
// Find a node with just two edges. This is a corner and will be the arbitrary origin in our graph
Node seed = null;
for (int i = 0; i < corners.size; i++) {
Node n = corners.get(i);
if( n.countEdges() == 2 ) {
seed = n;
break;
}
... | java | boolean orderNodes( FastQueue<Node> corners , GridInfo info ) {
// Find a node with just two edges. This is a corner and will be the arbitrary origin in our graph
Node seed = null;
for (int i = 0; i < corners.size; i++) {
Node n = corners.get(i);
if( n.countEdges() == 2 ) {
seed = n;
break;
}
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] | f01c0243da0ec086285ee722183804d5923bc3ac | https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterToGrid.java#L182-L236 |
49,877 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterToGrid.java | ChessboardCornerClusterToGrid.isRightHanded | static boolean isRightHanded( Node seed , int idxRow , int idxCol ) {
Node r = seed.edges[idxRow];
Node c = seed.edges[idxCol];
double dirRow = Math.atan2(r.y-seed.y,r.x-seed.x);
double dirCol = Math.atan2(c.y-seed.y,c.x-seed.x);
return UtilAngle.distanceCW(dirRow,dirCol) < Math.PI;
} | java | static boolean isRightHanded( Node seed , int idxRow , int idxCol ) {
Node r = seed.edges[idxRow];
Node c = seed.edges[idxCol];
double dirRow = Math.atan2(r.y-seed.y,r.x-seed.x);
double dirCol = Math.atan2(c.y-seed.y,c.x-seed.x);
return UtilAngle.distanceCW(dirRow,dirCol) < Math.PI;
} | [
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49,878 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterToGrid.java | ChessboardCornerClusterToGrid.sortEdgesCCW | void sortEdgesCCW(FastQueue<Node> corners) {
for (int nodeIdx = 0; nodeIdx < corners.size; nodeIdx++) {
Node na = corners.get(nodeIdx);
// reference node to do angles relative to.
double ref = Double.NaN;
int count = 0;
for (int i = 0; i < 4; i++) {
order[i] = i;
tmpEdges[i] = na.edges[i];
... | java | void sortEdgesCCW(FastQueue<Node> corners) {
for (int nodeIdx = 0; nodeIdx < corners.size; nodeIdx++) {
Node na = corners.get(nodeIdx);
// reference node to do angles relative to.
double ref = Double.NaN;
int count = 0;
for (int i = 0; i < 4; i++) {
order[i] = i;
tmpEdges[i] = na.edges[i];
... | [
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49,879 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/chess/ChessboardCornerClusterToGrid.java | ChessboardCornerClusterToGrid.rotateCCW | public void rotateCCW(GridInfo grid ) {
cornerList.clear();
for (int col = 0; col < grid.cols; col++) {
for (int row = 0; row < grid.rows; row++) {
cornerList.add(grid.get(row,grid.cols - col - 1));
}
}
int tmp = grid.rows;
grid.rows = grid.cols;
grid.cols = tmp;
grid.nodes.clear();
grid.node... | java | public void rotateCCW(GridInfo grid ) {
cornerList.clear();
for (int col = 0; col < grid.cols; col++) {
for (int row = 0; row < grid.rows; row++) {
cornerList.add(grid.get(row,grid.cols - col - 1));
}
}
int tmp = grid.rows;
grid.rows = grid.cols;
grid.cols = tmp;
grid.nodes.clear();
grid.node... | [
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49,880 | lessthanoptimal/BoofCV | main/boofcv-sfm/src/main/java/boofcv/alg/sfm/StereoProcessingBase.java | StereoProcessingBase.setCalibration | public void setCalibration(StereoParameters stereoParam) {
CameraPinholeBrown left = stereoParam.getLeft();
CameraPinholeBrown right = stereoParam.getRight();
// adjust image size
imageLeftRect.reshape(left.getWidth(), left.getHeight());
imageRightRect.reshape(right.getWidth(), right.getHeight());
// comp... | java | public void setCalibration(StereoParameters stereoParam) {
CameraPinholeBrown left = stereoParam.getLeft();
CameraPinholeBrown right = stereoParam.getRight();
// adjust image size
imageLeftRect.reshape(left.getWidth(), left.getHeight());
imageRightRect.reshape(right.getWidth(), right.getHeight());
// comp... | [
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49,881 | lessthanoptimal/BoofCV | main/boofcv-sfm/src/main/java/boofcv/alg/sfm/StereoProcessingBase.java | StereoProcessingBase.computeHomo3D | public void computeHomo3D(double x, double y, Point3D_F64 pointLeft) {
// Coordinate in rectified camera frame
pointRect.z = baseline*fx;
pointRect.x = pointRect.z*(x - cx)/fx;
pointRect.y = pointRect.z*(y - cy)/fy;
// rotate into the original left camera frame
GeometryMath_F64.multTran(rectR,pointRect,poi... | java | public void computeHomo3D(double x, double y, Point3D_F64 pointLeft) {
// Coordinate in rectified camera frame
pointRect.z = baseline*fx;
pointRect.x = pointRect.z*(x - cx)/fx;
pointRect.y = pointRect.z*(y - cy)/fy;
// rotate into the original left camera frame
GeometryMath_F64.multTran(rectR,pointRect,poi... | [
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49,882 | lessthanoptimal/BoofCV | main/boofcv-ip/src/main/java/boofcv/alg/transform/ii/GIntegralImageOps.java | GIntegralImageOps.getIntegralType | public static <I extends ImageGray<I>, II extends ImageGray<II>>
Class<II> getIntegralType( Class<I> inputType ) {
if( inputType == GrayF32.class ) {
return (Class<II>)GrayF32.class;
} else if( inputType == GrayU8.class ){
return (Class<II>)GrayS32.class;
} else if( inputType == GrayS32.class ){
return ... | java | public static <I extends ImageGray<I>, II extends ImageGray<II>>
Class<II> getIntegralType( Class<I> inputType ) {
if( inputType == GrayF32.class ) {
return (Class<II>)GrayF32.class;
} else if( inputType == GrayU8.class ){
return (Class<II>)GrayS32.class;
} else if( inputType == GrayS32.class ){
return ... | [
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49,883 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/abst/fiducial/FiducialDetectorPnP.java | FiducialDetectorPnP.computeStability | @Override
public boolean computeStability(int which, double disturbance, FiducialStability results) {
if( !getFiducialToCamera(which, targetToCamera))
return false;
stability.setShape(getSideWidth(which), getSideHeight(which));
stability.computeStability(targetToCamera,disturbance,results);
return true;
... | java | @Override
public boolean computeStability(int which, double disturbance, FiducialStability results) {
if( !getFiducialToCamera(which, targetToCamera))
return false;
stability.setShape(getSideWidth(which), getSideHeight(which));
stability.computeStability(targetToCamera,disturbance,results);
return true;
... | [
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49,884 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/abst/fiducial/FiducialDetectorPnP.java | FiducialDetectorPnP.createDetectedList | private void createDetectedList(int which, List<PointIndex2D_F64> pixels) {
detected2D3D.clear();
List<Point2D3D> all = getControl3D(which);
for (int i = 0; i < pixels.size(); i++) {
PointIndex2D_F64 a = pixels.get(i);
Point2D3D b = all.get(i);
pixelToNorm.compute(a.x,a.y, b.observation);
detected2D3... | java | private void createDetectedList(int which, List<PointIndex2D_F64> pixels) {
detected2D3D.clear();
List<Point2D3D> all = getControl3D(which);
for (int i = 0; i < pixels.size(); i++) {
PointIndex2D_F64 a = pixels.get(i);
Point2D3D b = all.get(i);
pixelToNorm.compute(a.x,a.y, b.observation);
detected2D3... | [
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49,885 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/abst/fiducial/FiducialDetectorPnP.java | FiducialDetectorPnP.estimatePose | protected boolean estimatePose( int which ,List<Point2D3D> points , Se3_F64 fiducialToCamera ) {
if( !estimatePnP.process(points, initialEstimate) ) {
return false;
}
filtered.clear();
// Don't bother if there are hardly any points to work with
if( points.size() > 6 ) {
w2p.configure(lensDistortion, ini... | java | protected boolean estimatePose( int which ,List<Point2D3D> points , Se3_F64 fiducialToCamera ) {
if( !estimatePnP.process(points, initialEstimate) ) {
return false;
}
filtered.clear();
// Don't bother if there are hardly any points to work with
if( points.size() > 6 ) {
w2p.configure(lensDistortion, ini... | [
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49,886 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/feature/detect/line/HoughTransformLineFootOfNorm.java | HoughTransformLineFootOfNorm.transform | public <D extends ImageGray<D>> void transform(D derivX , D derivY , GrayU8 binary )
{
InputSanityCheck.checkSameShape(derivX,derivY,binary);
transform.reshape(derivX.width,derivY.height);
ImageMiscOps.fill(transform,0);
originX = derivX.width/2;
originY = derivX.height/2;
candidates.reset();
if( deri... | java | public <D extends ImageGray<D>> void transform(D derivX , D derivY , GrayU8 binary )
{
InputSanityCheck.checkSameShape(derivX,derivY,binary);
transform.reshape(derivX.width,derivY.height);
ImageMiscOps.fill(transform,0);
originX = derivX.width/2;
originY = derivX.height/2;
candidates.reset();
if( deri... | [
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@param derivY Image derivative along y-axis.
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49,887 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/feature/detect/line/HoughTransformLineFootOfNorm.java | HoughTransformLineFootOfNorm.parameterize | public void parameterize( int x , int y , float derivX , float derivY )
{
// put the point in a new coordinate system centered at the image's origin
// this minimizes error, which is a function of distance from origin
x -= originX;
y -= originY;
float v = (x*derivX + y*derivY)/(derivX*derivX + derivY*derivY... | java | public void parameterize( int x , int y , float derivX , float derivY )
{
// put the point in a new coordinate system centered at the image's origin
// this minimizes error, which is a function of distance from origin
x -= originX;
y -= originY;
float v = (x*derivX + y*derivY)/(derivX*derivX + derivY*derivY... | [
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@param y point in image.
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49,888 | lessthanoptimal/BoofCV | examples/src/main/java/boofcv/examples/features/ExampleDenseImageFeatures.java | ExampleDenseImageFeatures.HighLevel | public static void HighLevel( GrayF32 input) {
System.out.println("\n------------------- Dense High Level");
DescribeImageDense<GrayF32,TupleDesc_F64> describer = FactoryDescribeImageDense.
hog(new ConfigDenseHoG(),input.getImageType());
// sift(new ConfigDenseSift(),GrayF32.class);
// surfFast(new Config... | java | public static void HighLevel( GrayF32 input) {
System.out.println("\n------------------- Dense High Level");
DescribeImageDense<GrayF32,TupleDesc_F64> describer = FactoryDescribeImageDense.
hog(new ConfigDenseHoG(),input.getImageType());
// sift(new ConfigDenseSift(),GrayF32.class);
// surfFast(new Config... | [
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] | f01c0243da0ec086285ee722183804d5923bc3ac | https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/examples/src/main/java/boofcv/examples/features/ExampleDenseImageFeatures.java#L52-L72 |
49,889 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/feature/disparity/impl/StereoDisparityWtoNaiveFive.java | StereoDisparityWtoNaiveFive.process | public void process( I left , I right , GrayF32 imageDisparity ) {
// check inputs and initialize data structures
InputSanityCheck.checkSameShape(left,right,imageDisparity);
this.imageLeft = left;
this.imageRight = right;
w = left.width; h = left.height;
// Compute disparity for each pixel
for( int y = ... | java | public void process( I left , I right , GrayF32 imageDisparity ) {
// check inputs and initialize data structures
InputSanityCheck.checkSameShape(left,right,imageDisparity);
this.imageLeft = left;
this.imageRight = right;
w = left.width; h = left.height;
// Compute disparity for each pixel
for( int y = ... | [
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@param left Left camera image.
@param right Right camera image. | [
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49,890 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/feature/disparity/impl/StereoDisparityWtoNaiveFive.java | StereoDisparityWtoNaiveFive.processPixel | private void processPixel( int c_x , int c_y , int maxDisparity ) {
for( int i = minDisparity; i < maxDisparity; i++ ) {
score[i] = computeScore( c_x , c_x-i,c_y);
}
} | java | private void processPixel( int c_x , int c_y , int maxDisparity ) {
for( int i = minDisparity; i < maxDisparity; i++ ) {
score[i] = computeScore( c_x , c_x-i,c_y);
}
} | [
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@param c_x Center of region on left image. x-axis
@param c_y Center of region on left image. y-axis
@param maxDisparity Max allowed disparity | [
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49,891 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/feature/disparity/impl/StereoDisparityWtoNaiveFive.java | StereoDisparityWtoNaiveFive.selectBest | protected double selectBest( int length ) {
double best = Double.MAX_VALUE;
int index = -1;
for( int i = minDisparity; i < length; i++ ) {
if( score[i] < best ) {
best = score[i];
index = i;
}
}
return index-minDisparity;
} | java | protected double selectBest( int length ) {
double best = Double.MAX_VALUE;
int index = -1;
for( int i = minDisparity; i < length; i++ ) {
if( score[i] < best ) {
best = score[i];
index = i;
}
}
return index-minDisparity;
} | [
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@param length The max allowed disparity at this pixel
@return The best disparity selected. | [
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49,892 | lessthanoptimal/BoofCV | main/boofcv-feature/src/main/java/boofcv/alg/feature/disparity/impl/StereoDisparityWtoNaiveFive.java | StereoDisparityWtoNaiveFive.computeScore | protected double computeScore( int leftX , int rightX , int centerY ) {
double center = computeScoreRect(leftX,rightX,centerY);
four[0] = computeScoreRect(leftX-radiusX,rightX-radiusX,centerY-radiusY);
four[1] = computeScoreRect(leftX+radiusX,rightX+radiusX,centerY-radiusY);
four[2] = computeScoreRect(leftX... | java | protected double computeScore( int leftX , int rightX , int centerY ) {
double center = computeScoreRect(leftX,rightX,centerY);
four[0] = computeScoreRect(leftX-radiusX,rightX-radiusX,centerY-radiusY);
four[1] = computeScoreRect(leftX+radiusX,rightX+radiusX,centerY-radiusY);
four[2] = computeScoreRect(leftX... | [
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@param leftX X-axis center left image
@param rightX X-axis center left image
@param centerY Y-axis center for both images
@return Fit score for both regions. | [
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49,893 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/qrcode/QrCodeGenerator.java | QrCodeGenerator.render | public void render( QrCode qr ) {
initialize(qr);
render.init();
positionPattern(0,0, qr.ppCorner);
positionPattern((numModules-7)*moduleWidth,0, qr.ppRight);
positionPattern(0,(numModules-7)*moduleWidth, qr.ppDown);
timingPattern(7*moduleWidth,6*moduleWidth,moduleWidth,0);
timingPattern(6*moduleWidth,7... | java | public void render( QrCode qr ) {
initialize(qr);
render.init();
positionPattern(0,0, qr.ppCorner);
positionPattern((numModules-7)*moduleWidth,0, qr.ppRight);
positionPattern(0,(numModules-7)*moduleWidth, qr.ppDown);
timingPattern(7*moduleWidth,6*moduleWidth,moduleWidth,0);
timingPattern(6*moduleWidth,7... | [
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49,894 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/qrcode/QrCodeGenerator.java | QrCodeGenerator.renderData | private void renderData() {
QrCodeMaskPattern mask = qr.mask;
int count = 0;
int length = bitLocations.size() - bitLocations.size()%8;
while( count < length ) {
int bits = qr.rawbits[count/8]&0xFF;
int N = Math.min(8,bitLocations.size()-count);
for (int i = 0; i < N; i++) {
Point2D_I32 coor = bi... | java | private void renderData() {
QrCodeMaskPattern mask = qr.mask;
int count = 0;
int length = bitLocations.size() - bitLocations.size()%8;
while( count < length ) {
int bits = qr.rawbits[count/8]&0xFF;
int N = Math.min(8,bitLocations.size()-count);
for (int i = 0; i < N; i++) {
Point2D_I32 coor = bi... | [
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49,895 | lessthanoptimal/BoofCV | integration/boofcv-javacv/src/main/java/boofcv/javacv/UtilOpenCV.java | UtilOpenCV.loadPinholeRadial | public static CameraPinholeBrown loadPinholeRadial(String fileName ) {
FileStorage fs = new FileStorage(
new File(fileName).getAbsolutePath(), FileStorage.READ);
IntPointer width = new IntPointer(1);
IntPointer height = new IntPointer(1);
read(fs.get("image_width"),width,-1);
read(fs.get("image_height")... | java | public static CameraPinholeBrown loadPinholeRadial(String fileName ) {
FileStorage fs = new FileStorage(
new File(fileName).getAbsolutePath(), FileStorage.READ);
IntPointer width = new IntPointer(1);
IntPointer height = new IntPointer(1);
read(fs.get("image_width"),width,-1);
read(fs.get("image_height")... | [
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@param fileName path to file
@return CameraPinholeRadial | [
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] | f01c0243da0ec086285ee722183804d5923bc3ac | https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/integration/boofcv-javacv/src/main/java/boofcv/javacv/UtilOpenCV.java#L44-L79 |
49,896 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/squares/SquareNode.java | SquareNode.distanceSqCorner | public double distanceSqCorner( Point2D_F64 p ) {
double best = Double.MAX_VALUE;
for (int i = 0; i < 4; i++) {
double d = square.get(i).distance2(p);
if( d < best ) {
best = d;
}
}
return best;
} | java | public double distanceSqCorner( Point2D_F64 p ) {
double best = Double.MAX_VALUE;
for (int i = 0; i < 4; i++) {
double d = square.get(i).distance2(p);
if( d < best ) {
best = d;
}
}
return best;
} | [
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... | Finds the Euclidean distance squared of the closest corner to point p | [
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] | f01c0243da0ec086285ee722183804d5923bc3ac | https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/squares/SquareNode.java#L59-L68 |
49,897 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/squares/SquareNode.java | SquareNode.reset | public void reset() {
square = null;
touch = null;
center.set(-1,-1);
largestSide = 0;
smallestSide = Double.MAX_VALUE;
graph = RESET_GRAPH;
for (int i = 0; i < edges.length; i++) {
if ( edges[i] != null )
throw new RuntimeException("BUG!");
sideLengths[i] = 0;
}
} | java | public void reset() {
square = null;
touch = null;
center.set(-1,-1);
largestSide = 0;
smallestSide = Double.MAX_VALUE;
graph = RESET_GRAPH;
for (int i = 0; i < edges.length; i++) {
if ( edges[i] != null )
throw new RuntimeException("BUG!");
sideLengths[i] = 0;
}
} | [
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] | f01c0243da0ec086285ee722183804d5923bc3ac | https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/squares/SquareNode.java#L73-L85 |
49,898 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/squares/SquareNode.java | SquareNode.updateArrayLength | public void updateArrayLength() {
if( edges.length != square.size() ) {
edges = new SquareEdge[square.size()];
sideLengths = new double[square.size()];
}
} | java | public void updateArrayLength() {
if( edges.length != square.size() ) {
edges = new SquareEdge[square.size()];
sideLengths = new double[square.size()];
}
} | [
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49,899 | lessthanoptimal/BoofCV | main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/squares/SquareNode.java | SquareNode.getNumberOfConnections | public int getNumberOfConnections() {
int ret = 0;
for (int i = 0; i < square.size(); i++) {
if( edges[i] != null )
ret++;
}
return ret;
} | java | public int getNumberOfConnections() {
int ret = 0;
for (int i = 0; i < square.size(); i++) {
if( edges[i] != null )
ret++;
}
return ret;
} | [
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] | f01c0243da0ec086285ee722183804d5923bc3ac | https://github.com/lessthanoptimal/BoofCV/blob/f01c0243da0ec086285ee722183804d5923bc3ac/main/boofcv-recognition/src/main/java/boofcv/alg/fiducial/calib/squares/SquareNode.java#L101-L108 |
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