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@Override public void getCenter(int which, Point2D_F64 location) { CalibrationObservation view = detector.getDetectedPoints(); location.set(0,0); for (int i = 0; i < view.size(); i++) { PointIndex2D_F64 p = view.get(i); location.x += p.x; location.y += p.y; } location.x /= view.size(); location....
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public void setConstraints( boolean zeroSkew , boolean principlePointOrigin , boolean knownAspect, double aspect ) { if( knownAspect && !zeroSkew ) throw new IllegalArgumentException("If aspect is known then skew must be zero"); this.zeroSkew = zeroSkew; this.principlePointOrigin = pr...
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void extractReferenceW(DMatrixRMaj nv ) { W0.a11 = nv.data[0]; W0.a12 = W0.a21 = nv.data[1]; W0.a13 = W0.a31 = nv.data[2]; W0.a22 = nv.data[3]; W0.a23 = W0.a32 = nv.data[4]; W0.a33 = nv.data[5]; }
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void convertW( Homography2D_F64 w , CameraPinhole c ) { // inv(w) = K*K' tmp.set(w); CommonOps_DDF3.divide(tmp,tmp.a33); CommonOps_DDF3.cholU(tmp); CommonOps_DDF3.invert(tmp,K); CommonOps_DDF3.divide(K,K.a33); c.fx = K.a11; c.fy = knownAspectRatio ? (K.a22 + c.fx*aspectRatio)/2.0 : K.a22; c.skew = ze...
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void extractCalibration( Homography2D_F64 Hinv , CameraPinhole c ) { CommonOps_DDF3.multTransA(Hinv,W0,tmp); CommonOps_DDF3.mult(tmp,Hinv,Wi); convertW(Wi,c); }
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public boolean computeInverseH(List<Homography2D_F64> homography0toI) { listHInv.reset(); int N = homography0toI.size(); for (int i = 0; i < N; i++) { Homography2D_F64 H = homography0toI.get(i); Homography2D_F64 Hinv = listHInv.grow(); // Ensure the determinant is one double d = CommonOps_DDF3.det(H)...
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protected void startCameraTexture( TextureView view ) { if( verbose ) Log.i(TAG,"startCamera(TextureView="+(view!=null)+")"); this.mTextureView = view; this.mView = null; this.mTextureView.setSurfaceTextureListener(mSurfaceTextureListener); }
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protected void configureCamera( CameraDevice device , CameraCharacteristics characteristics, CaptureRequest.Builder captureRequestBuilder ) { if( verbose ) Log.i(TAG,"configureCamera() default function"); captureRequestBuilder.set(CaptureRequest.CONTROL_AF_MODE, CaptureRequest.CONTROL_AF_MODE_C...
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protected boolean selectCamera( String id , CameraCharacteristics characteristics ) { if( verbose ) Log.i(TAG,"selectCamera() default function"); Integer facing = characteristics.get(CameraCharacteristics.LENS_FACING); return facing == null || facing != CameraCharacteristics.LENS_FACING_FRONT; }
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protected void reopenCameraAtResolution(int cameraWidth, int cameraHeight) { if (Looper.getMainLooper().getThread() != Thread.currentThread()) { throw new RuntimeException("Attempted to reopenCameraAtResolution main looper thread!"); } boolean releaseLock = true; open.mLock.lock(); try { if (verbose) ...
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protected boolean closeCamera() { if( verbose ) Log.i(TAG,"closeCamera() activity="+getClass().getSimpleName()); if (Looper.getMainLooper().getThread() != Thread.currentThread()) { throw new RuntimeException("Attempted to close camera not on the main looper thread!"); } boolean closed = false; // if( v...
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private void startPreview() { // Sanity check. Parts of this code assume it's on this thread. If it has been put into a handle // that's fine just be careful nothing assumes it's on the main looper if (Looper.getMainLooper().getThread() != Thread.currentThread()) { throw new RuntimeException("Not on main loope...
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public void cameraIntrinsicNominal(CameraPinhole intrinsic ) { open.mLock.lock(); try { // This might be called before the camera is open if (open.mCameraCharacterstics != null) { SizeF physicalSize = open.mCameraCharacterstics.get(CameraCharacteristics.SENSOR_INFO_PHYSICAL_SIZE); Rect activeSize = op...
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private float displayDensityAdjusted() { open.mLock.lock(); try { if (open.mCameraSize == null) return displayMetrics.density; int rotation = getWindowManager().getDefaultDisplay().getRotation(); int screenWidth = (rotation == 0 || rotation == 2) ? displayMetrics.widthPixels : displayMetrics.heightPix...
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public static <T extends ImageGray<T>> StereoDisparitySparse<T> regionSparseWta( int minDisparity , int maxDisparity, int regionRadiusX, int regionRadiusY , double maxPerPixelError , double texture , boolean subpixelInterpolation , Class<T> imageType ) { double maxError = (regionRadius...
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public void addPoint( float x , float y , float z ) { norm.grow().set(x/z, y/z); }
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public void process() { computeCovarince(); float eigenvalue = smallestEigenvalue(); // eigenvalue is the variance, convert to standard deviation double stdev = Math.sqrt(eigenvalue); // System.out.println("stdev "+stdev+" total "+norm.size()+" mean "+meanX+" "+meanY); // approximate the spread in by d...
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public static ClassifierAndSource vgg_cifar10() { List<String> sources = new ArrayList<>(); sources.add( "http://boofcv.org/notwiki/largefiles/likevgg_cifar10.zip" ); ClassifierAndSource ret = new ClassifierAndSource(); ret.data0 = new ImageClassifierVggCifar10(); ret.data1 = sources; return ret; }
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public static ClassifierAndSource nin_imagenet() { List<String> sources = new ArrayList<>(); sources.add( "http://boofcv.org/notwiki/largefiles/nin_imagenet.zip" ); ClassifierAndSource ret = new ClassifierAndSource(); ret.data0 = new ImageClassifierNiNImageNet(); ret.data1 = sources; return ret; }
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public Exit launch( Class mainClass , String ...args ) { jvmArgs = configureArguments(mainClass,args); try { Runtime rt = Runtime.getRuntime(); Process pr = rt.exec(jvmArgs); // If it exits too quickly it might not get any error messages if it crashes right away ...
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private boolean monitorSlave(Process pr, BufferedReader input, BufferedReader error) throws IOException, InterruptedException { // flush the input buffer System.in.skip(System.in.available()); // If the total amount of time allocated to the slave ex...
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protected void computeWeightBlockPixels() { int rows = cellsPerBlockY*pixelsPerCell; int cols = cellsPerBlockX*pixelsPerCell; weights = new double[ rows*cols ]; double offsetRow=0,offsetCol=0; int radiusRow=rows/2,radiusCol=cols/2; if( rows%2 == 0 ) { offsetRow = 0.5; } if( cols%2 == 0 ) { offs...
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private void computePixelFeatures() { for (int y = 0; y < derivX.height; y++) { int pixelIndex = y*derivX.width; int endIndex = pixelIndex+derivX.width; for (; pixelIndex < endIndex; pixelIndex++ ) { float dx = derivX.data[pixelIndex]; float dy = derivY.data[pixelIndex]; // angle from 0 to pi ra...
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void addToHistogram(int cellX, int cellY, int orientationIndex, double magnitude) { // see if it's being applied to a valid cell in the histogram if( cellX < 0 || cellX >= cellsPerBlockX) return; if( cellY < 0 || cellY >= cellsPerBlockY) return; int index = (cellY*cellsPerBlockX + cellX)*orientationBins ...
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public void setInput(float x[], float y[], int size) { if (x.length < size || y.length < size) { throw new IllegalArgumentException("Arrays too small for size."); } if (size < M) { throw new IllegalArgumentException("Not enough data points for M"); } this.x = x; this.y = y; this.size = size; this...
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public float process(float testX) { if (doHunt) { hunt(testX); } else { bisectionSearch(testX, 0, size - 1); } return compute(testX); }
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protected void hunt(float val) { int lowerLimit = center; int upperLimit; int inc = 1; if (val >= x[lowerLimit] && ascend) { // hunt up for (; ; ) { upperLimit = lowerLimit + inc; // see if it is outside the table if (upperLimit >= size - 1) { upperLimit = size - 1; break; } els...
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public static void process( GrayI orig, GrayI derivX, GrayI derivY) { final int width = orig.getWidth(); final int height = orig.getHeight(); for (int y = 1; y < height - 1; y++) { for (int x = 1; x < width - 1; x++) { int dy = -(orig.get(x - 1, y - 1) + 2 * orig.get(x, y - 1) + orig.get...
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public static <T extends ImageBase<T>> void performSegmentation( ImageSuperpixels<T> alg , T color ) { // Segmentation often works better after blurring the image. Reduces high frequency image components which // can cause over segmentation GBlurImageOps.gaussian(color, color, 0.5, -1, null); // Storage for...
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public static <T extends ImageBase<T>> void visualize(GrayS32 pixelToRegion , T color , int numSegments ) { // Computes the mean color inside each region ImageType<T> type = color.getImageType(); ComputeRegionMeanColor<T> colorize = FactorySegmentationAlg.regionMeanColor(type); FastQueue<float[]> segmentCol...
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public static GrayU8 denseDisparity(GrayU8 rectLeft , GrayU8 rectRight , int regionSize, int minDisparity , int maxDisparity ) { // A slower but more accuracy algorithm is selected // All of these parameters should be turned StereoDisparity<GrayU8,GrayU8> disparityAlg = FactoryStereoDispa...
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public static GrayF32 denseDisparitySubpixel(GrayU8 rectLeft , GrayU8 rectRight , int regionSize , int minDisparity , int maxDisparity ) { // A slower but more accuracy algorithm is selected // All of these parameters should be turned StereoDisparity<GrayU8,GrayF32> disparityAlg = F...
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public static RectifyCalibrated rectify(GrayU8 origLeft , GrayU8 origRight , StereoParameters param , GrayU8 rectLeft , GrayU8 rectRight ) { // Compute rectification RectifyCalibrated rectifyAlg = RectifyImageOps.createCalibrated(); Se3_F64 leftToRight = param.getRightToLeft().invert(null);...
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public boolean isRangeSet() { for (int i = 0; i < getDimensions(); i++) { if( valueMin[i] == 0 && valueMax[i] == 0 ) { return false; } } return true; }
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public void setRange( int dimension , double min , double max ) { valueMin[dimension] = min; valueMax[dimension] = max; }
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public int getDimensionIndex( int dimension , int value ) { double min = valueMin[dimension]; double max = valueMax[dimension]; double fraction = ((value-min)/(max-min+1.0)); return (int)(fraction*length[dimension]); }
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public final int getIndex( int coordinate[] ) { int index = coordinate[0]*strides[0]; for (int i = 1; i < coordinate.length; i++) { index += strides[i]*coordinate[i]; } return index; }
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public Histogram_F64 copy() { Histogram_F64 out = newInstance(); System.arraycopy(value,0,out.value,0,length.length); return out; }
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@Override public boolean refine(Polygon2D_F64 input, Polygon2D_F64 output) { if( input.size() != output.size()) throw new IllegalArgumentException("Input and output sides do not match. "+input.size()+" "+output.size()); // sanity check input. If it's too small this algorithm won't work if( checkShapeTooSma...
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private boolean checkShapeTooSmall(Polygon2D_F64 input) { // must be longer than the border plus some small fudge factor double minLength = cornerOffset*2 + 2; for (int i = 0; i < input.size(); i++) { int j = (i+1)%input.size(); Point2D_F64 a = input.get(i); Point2D_F64 b = input.get(j); if( a.distanc...
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protected boolean optimize(Polygon2D_F64 seed , Polygon2D_F64 current ) { previous.set(seed); // pixels squares is faster to compute double convergeTol = convergeTolPixels*convergeTolPixels; // initialize the lines since they are used to check for corner divergence for (int i = 0; i < seed.size(); i++) { ...
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protected boolean optimize( Point2D_F64 a , Point2D_F64 b , LineGeneral2D_F64 found ) { computeAdjustedEndPoints(a, b); return snapToEdge.refine(adjA, adjB, found); }
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public static BufferedImage watersheds(GrayS32 segments , BufferedImage output , int radius ) { if( output == null ) output = new BufferedImage(segments.width,segments.height,BufferedImage.TYPE_INT_RGB); if( radius <= 0 ) { for (int y = 0; y < segments.height; y++) { for (int x = 0; x < segments.width; x...
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public static BufferedImage regions(GrayS32 pixelToRegion , int numRegions , BufferedImage output ) { return VisualizeBinaryData.renderLabeled(pixelToRegion,numRegions,output); }
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private static void randomGaussian( Random rand , double sigma , int radius , Point2D_I32 pt ) { int x,y; while( true ) { x = (int)(rand.nextGaussian()*sigma); y = (int)(rand.nextGaussian()*sigma); if( Math.sqrt(x*x + y*y) < radius ) break; } pt.set(x,y); }
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public static <T extends ImageBase<T>> PyramidDiscrete<T> discreteGaussian( int[] scaleFactors , double sigma , int radius , boolean saveOriginalReference, ImageType<T> imageType ) { Class<Kernel1D> kernelType = FactoryKernel.getKernelType(imageType.getDataType(),1); Kernel1D kernel = FactoryKernelGau...
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public static <T extends ImageGray<T>> PyramidFloat<T> floatGaussian( double scaleFactors[], double []sigmas , Class<T> imageType ) { InterpolatePixelS<T> interp = FactoryInterpolation.bilinearPixelS(imageType, BorderType.EXTENDED); return new PyramidFloatGaussianScale<>(interp, scaleFactors, sigmas, imageType);...
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public static double process_F64(double sample, double x[], double y[], int i0, int i1) { double result = 0; for (int i = i0; i <= i1; i++) { double numerator = 1.0; for (int j = i0; j <= i1; j++) { if (i != j) numerator *= sample - x[j]; } double denominator = 1.0; double a = x[i]; ...
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public void add( Color color , Point3D_F64... polygon ) { final Poly p = new Poly(polygon.length,color); for( int i = 0; i < polygon.length; i++ ) p.pts[i] = polygon[i].copy(); synchronized (polygons) { polygons.add( p ); } }
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public static BufferedImage checkDeclare( int width , int height , BufferedImage image , int type ) { if( image == null ) return new BufferedImage(width,height,type); if( image.getType() != type ) return new BufferedImage(width,height,type); if( image.getWidth() != width || image.getHeight() != height ) ...
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public static BufferedImage checkCopy( BufferedImage original , BufferedImage output ) { ColorModel cm = original.getColorModel(); boolean isAlphaPremultiplied = cm.isAlphaPremultiplied(); if( output == null || original.getWidth() != output.getWidth() || original.getHeight() != output.getHeight() || original...
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public static BufferedImage stripAlphaChannel( BufferedImage image ) { int numBands = image.getRaster().getNumBands(); if( numBands == 4 ) { BufferedImage output = new BufferedImage(image.getWidth(),image.getHeight(),BufferedImage.TYPE_INT_RGB); output.createGraphics().drawImage(image,0,0,null); return ou...
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public static InterleavedU8 extractInterleavedU8(BufferedImage img) { DataBuffer buffer = img.getRaster().getDataBuffer(); if (buffer.getDataType() == DataBuffer.TYPE_BYTE && isKnownByteFormat(img) ) { WritableRaster raster = img.getRaster(); InterleavedU8 ret = new InterleavedU8(); ret.width = img.getW...
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public static GrayU8 extractGrayU8(BufferedImage img) { WritableRaster raster = img.getRaster(); DataBuffer buffer = raster.getDataBuffer(); if (buffer.getDataType() == DataBuffer.TYPE_BYTE && isKnownByteFormat(img) ) { if (raster.getNumBands() != 1) throw new IllegalArgumentException("Input image has mor...
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public static <T extends ImageGray<T>> T convertFromSingle(BufferedImage src, T dst, Class<T> type) { if (type == GrayU8.class) { return (T) convertFrom(src, (GrayU8) dst); } else if( GrayI16.class.isAssignableFrom(type) ) { return (T) convertFrom(src, (GrayI16) dst,(Class)type); } else if (type == GrayF32....
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public static BufferedImage convertTo(JComponent comp, BufferedImage storage) { if (storage == null) storage = new BufferedImage(comp.getWidth(), comp.getHeight(), BufferedImage.TYPE_INT_RGB); Graphics2D g2 = storage.createGraphics(); comp.paintComponents(g2); return storage; }
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public static Planar orderBandsIntoBuffered(Planar src, BufferedImage dst) { // see if no change is required if( dst.getType() == BufferedImage.TYPE_INT_RGB ) return src; Planar tmp = new Planar(src.type, src.getNumBands()); tmp.width = src.width; tmp.height = src.height; tmp.stride = src.stride; tmp....
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public static double computeError(GrayF32 imgA, GrayF32 imgB ) { final int h = imgA.getHeight(); final int w = imgA.getWidth(); double total = 0; for (int y = 0; y < h; y++) { for (int x = 0; x < w; x++) { double difference = Math.abs(imgA.get(x,y)-imgB.get(x,y)); total += difference; } } ...
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public static double computeWeightedError(GrayF32 imgA, GrayF32 imgB , GrayF32 imgWeight ) { final int h = imgA.getHeight(); final int w = imgA.getWidth(); double total = 0; double totalWeight = 0; for (int y = 0; y < h; y++) { for (int x = 0; x < w; x++) { float weight = imgWeight.get(x...
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private static boolean nearBorder( Point2D_F64 p , StitchingFromMotion2D<?,?> stitch ) { int r = 10; if( p.x < r || p.y < r ) return true; if( p.x >= stitch.getStitchedImage().width-r ) return true; if( p.y >= stitch.getStitchedImage().height-r ) return true; return false; }
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public void setShape(double width , double height ) { points2D3D.get(0).location.set(-width/2,-height/2,0); points2D3D.get(1).location.set(-width/2, height/2,0); points2D3D.get(2).location.set( width/2, height/2,0); points2D3D.get(3).location.set( width/2,-height/2,0); }
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public void computeStability(Se3_F64 targetToCamera , double disturbance, FiducialStability results) { targetToCamera.invert(referenceCameraToTarget); maxOrientation = 0; maxLocation = 0; Point3D_F64 cameraPt = new Point3D_F64(); for (int i = 0; i < points2D3D.size(); i++) { Point2D3D ...
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private void perturb(double disturbance , Point2D_F64 pixel , Point2D3D p23 ) { double x; double y = pixel.y; x = pixel.x + disturbance; computeDisturbance( x,y, p23); x = pixel.x - disturbance; computeDisturbance( x,y, p23); x = pixel.x; y = pixel.y + disturbance; computeDisturbance( x,y, p23); y ...
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public static<T extends ImageGray<T>, D extends ImageGray<D>> void detectLines( BufferedImage image , Class<T> imageType , Class<D> derivType ) { // convert the line into a single band image T input = ConvertBufferedImage.convertFromSingle(image, null, imageType ); // Comment/uncomment to ...
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public static<T extends ImageGray<T>, D extends ImageGray<D>> void detectLineSegments( BufferedImage image , Class<T> imageType , Class<D> derivType ) { // convert the line into a single band image T input = ConvertBufferedImage.convertFromSingle(image, null, imageType ); // Comment/uncomment t...
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public static List<double[]> coupledHueSat( List<String> images ) { List<double[]> points = new ArrayList<>(); Planar<GrayF32> rgb = new Planar<>(GrayF32.class,1,1,3); Planar<GrayF32> hsv = new Planar<>(GrayF32.class,1,1,3); for( String path : images ) { BufferedImage buffered = UtilImageIO.loadImage(path...
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public static List<double[]> independentHueSat( List<File> images ) { List<double[]> points = new ArrayList<>(); // The number of bins is an important parameter. Try adjusting it TupleDesc_F64 histogramHue = new TupleDesc_F64(30); TupleDesc_F64 histogramValue = new TupleDesc_F64(30); List<TupleDesc_F64> h...
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public static List<double[]> coupledRGB( List<File> images ) { List<double[]> points = new ArrayList<>(); Planar<GrayF32> rgb = new Planar<>(GrayF32.class,1,1,3); for( File f : images ) { BufferedImage buffered = UtilImageIO.loadImage(f.getPath()); if( buffered == null ) throw new RuntimeException("Can't ...
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public static List<double[]> histogramGray( List<File> images ) { List<double[]> points = new ArrayList<>(); GrayU8 gray = new GrayU8(1,1); for( File f : images ) { BufferedImage buffered = UtilImageIO.loadImage(f.getPath()); if( buffered == null ) throw new RuntimeException("Can't load image!"); gray....
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public static int[] imageOffsets(double radius, int imgWidth) { double PI2 = Math.PI * 2.0; double circumference = PI2 * radius; int num = (int) Math.ceil(circumference); num = num - num % 4; double angleStep = PI2 / num; int temp[] = new int[(int) Math.ceil(circumference)]; int i = 0; int prev =...
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public static <T extends ImageGray<T>, TD extends TupleDesc> DetectDescribePoint<T, TD> createFromPremade( Class<T> imageType ) { return (DetectDescribePoint)FactoryDetectDescribe.surfStable( new ConfigFastHessian(1, 2, 200, 1, 9, 4, 4), null,null, imageType); // return (DetectDescribePoint)FactoryDetectDescrib...
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public static <T extends ImageGray<T>, TD extends TupleDesc> DetectDescribePoint<T, TD> createFromComponents( Class<T> imageType ) { // create a corner detector Class derivType = GImageDerivativeOps.getDerivativeType(imageType); GeneralFeatureDetector corner = FactoryDetectPoint.createShiTomasi(new ConfigGeneral...
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protected void computeWeights(int numSamples, double numSigmas) { weights = new float[ numSamples*numSamples ]; float w[] = new float[ numSamples ]; for( int i = 0; i < numSamples; i++ ) { float x = i/(float)(numSamples-1); w[i] = (float) UtilGaussian.computePDF(0, 1, 2f*numSigmas * (x - 0.5f)); } for...
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protected void createSamplePoints(int numSamples) { for( int y = 0; y < numSamples; y++ ) { float regionY = (y/(numSamples-1.0f) - 0.5f); for( int x = 0; x < numSamples; x++ ) { float regionX = (x/(numSamples-1.0f) - 0.5f); samplePts.add( new Point2D_F32(regionX,regionY)); } } }
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protected void computeHistogramInside( RectangleRotate_F32 region) { for( int i = 0; i < samplePts.size(); i++ ) { Point2D_F32 p = samplePts.get(i); squareToImageSample(p.x, p.y, region); interpolate.get_fast(imageX,imageY,value); int indexHistogram = computeHistogramBin(value); sampleHistIndex[ i ...
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protected void computeHistogramBorder(T image, RectangleRotate_F32 region) { for( int i = 0; i < samplePts.size(); i++ ) { Point2D_F32 p = samplePts.get(i); squareToImageSample(p.x, p.y, region); // make sure its inside the image if( !BoofMiscOps.checkInside(image, imageX, imageY)) { sampleHistIndex...
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protected int computeHistogramBin( float value[] ) { int indexHistogram = 0; int binStride = 1; for( int bandIndex = 0; bandIndex < value.length; bandIndex++ ) { int bin = (int)(numBins*value[bandIndex]/maxPixelValue); indexHistogram += bin*binStride; binStride *= numBins; } return indexHistogram; ...
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protected boolean isInFastBounds(RectangleRotate_F32 region) { squareToImageSample(-0.5f, -0.5f, region); if( !interpolate.isInFastBounds(imageX, imageY)) return false; squareToImageSample(-0.5f, 0.5f, region); if( !interpolate.isInFastBounds(imageX, imageY)) return false; squareToImageSample(0.5f, 0.5...
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protected void squareToImageSample(float x, float y, RectangleRotate_F32 region) { // -1 because it starts counting at 0. otherwise width+1 samples are made x *= region.width-1; y *= region.height-1; imageX = x*c - y*s + region.cx; imageY = x*s + y*c + region.cy; }
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private void createSparseDerivatives() { Kernel1D_F32 kernelD = new Kernel1D_F32(new float[]{-1,0,1},3); Kernel1D_F32 kernelDD = KernelMath.convolve1D_F32(kernelD, kernelD); Kernel2D_F32 kernelXY = KernelMath.convolve2D(kernelD, kernelD); derivXX = FactoryConvolveSparse.horizontal1D(GrayF32.class, kernelDD); ...
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public void process( GrayF32 input ) { scaleSpace.initialize(input); detections.reset(); do { // scale from octave to input image pixelScaleToInput = scaleSpace.pixelScaleCurrentToInput(); // detect features in the image for (int j = 1; j < scaleSpace.getNumScales()+1; j++) { // not really sur...
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protected void detectFeatures( int scaleIndex ) { extractor.process(dogTarget); FastQueue<NonMaxLimiter.LocalExtreme> found = extractor.getLocalExtreme(); derivXX.setImage(dogTarget); derivXY.setImage(dogTarget); derivYY.setImage(dogTarget); for (int i = 0; i < found.size; i++) { NonMaxLimiter.LocalExt...
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boolean isScaleSpaceExtremum(int c_x, int c_y, float value, float signAdj) { if( c_x <= 1 || c_y <= 1 || c_x >= dogLower.width-1 || c_y >= dogLower.height-1) return false; float v; value *= signAdj; for( int y = -1; y <= 1; y++ ) { for( int x = -1; x <= 1; x++ ) { v = dogLower.unsafe_get(c_x+x,c...
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public static PixelTransformAffine_F32 transformScale(ImageBase from, ImageBase to, PixelTransformAffine_F32 distort) { if( distort == null ) distort = new PixelTransformAffine_F32(); float scaleX = (float)(to.width)/(float)(from.width); float scaleY = (float)(to.height)/(float)(from.height);...
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protected boolean projectOntoEssential( DMatrixRMaj E ) { if( !svdConstraints.decompose(E) ) { return false; } svdV = svdConstraints.getV(svdV,false); svdU = svdConstraints.getU(svdU,false); svdS = svdConstraints.getW(svdS); SingularOps_DDRM.descendingOrder(svdU, false, svdS, svdV, false); // project...
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protected boolean projectOntoFundamentalSpace( DMatrixRMaj F ) { if( !svdConstraints.decompose(F) ) { return false; } svdV = svdConstraints.getV(svdV,false); svdU = svdConstraints.getU(svdU,false); svdS = svdConstraints.getW(svdS); SingularOps_DDRM.descendingOrder(svdU, false, svdS, svdV, false); // ...
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public void learnFern(boolean positive, ImageRectangle r) { float rectWidth = r.getWidth(); float rectHeight = r.getHeight(); float c_x = r.x0+(rectWidth-1)/2f; float c_y = r.y0+(rectHeight-1)/2f; for( int i = 0; i < ferns.length; i++ ) { // first learn it with no noise int value = computeFernValue(...
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public void learnFernNoise(boolean positive, ImageRectangle r) { float rectWidth = r.getWidth(); float rectHeight = r.getHeight(); float c_x = r.x0+(rectWidth-1)/2.0f; float c_y = r.y0+(rectHeight-1)/2.0f; for( int i = 0; i < ferns.length; i++ ) { // first learn it with no noise int value = computeF...
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private void increment( TldFernFeature f , boolean positive ) { if( positive ) { f.incrementP(); if( f.numP > maxP ) maxP = f.numP; } else { f.incrementN(); if( f.numN > maxN ) maxN = f.numN; } }
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public boolean lookupFernPN( TldRegionFernInfo info ) { ImageRectangle r = info.r; float rectWidth = r.getWidth(); float rectHeight = r.getHeight(); float c_x = r.x0+(rectWidth-1)/2.0f; float c_y = r.y0+(rectHeight-1)/2.0f; int sumP = 0; int sumN = 0; for( int i = 0; i < ferns.length; i++ ) { Tl...
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protected int computeFernValue(float c_x, float c_y, float rectWidth , float rectHeight , TldFernDescription fern ) { rectWidth -= 1; rectHeight -= 1; int desc = 0; for( int i = 0; i < fern.pairs.length; i++ ) { Point2D_F32 p_a = fern.pairs[i].a; Point2D_F32 p_b = fern.pairs[i].b; float valA = inter...
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public void renormalizeP() { int targetMax = maxP/20; for( int i = 0; i < managers.length; i++ ) { TldFernManager m = managers[i]; for( int j = 0; j < m.table.length; j++ ) { TldFernFeature f = m.table[j]; if( f == null ) continue; f.numP = targetMax*f.numP/maxP; } } maxP = targetMax;...
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public void renormalizeN() { int targetMax = maxN/20; for( int i = 0; i < managers.length; i++ ) { TldFernManager m = managers[i]; for( int j = 0; j < m.table.length; j++ ) { TldFernFeature f = m.table[j]; if( f == null ) continue; f.numN = targetMax*f.numN/maxN; } } maxN = targetMax;...
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public void describe(double x, double y, double angle, double scale, TupleDesc_F64 ret) { double c = Math.cos(angle),s=Math.sin(angle); // By assuming that the entire feature is inside the image faster algorithms can be used // the results are also of dubious value when interacting with the image border. bool...
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public boolean computeLaplaceSign(int x, int y, double scale) { int s = (int)Math.ceil(scale); kerXX = DerivativeIntegralImage.kernelDerivXX(9*s,kerXX); kerYY = DerivativeIntegralImage.kernelDerivYY(9*s,kerYY); double lap = GIntegralImageOps.convolveSparse(ii,kerXX,x,y); lap += GIntegralImageOps.convolveSpars...
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public static <I extends ImageGray<I>, D extends ImageGray<D>> DetectLineHoughPolar<I,D> houghPolar(ConfigHoughPolar config , Class<I> imageType , Class<D> derivType ) { if( config == null ) throw new IllegalArgumentException("This is no default since minCounts must be specified"); Image...
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public static BufferedImage renderContours(List<Contour> contours , int colorExternal, int colorInternal , int width , int height , BufferedImage out) { if( out == null ) { out = new BufferedImage(width,height,BufferedImage.TYPE_INT_RGB); } else { Graphics2D g2 = out.createGraphics(); g2.set...
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public static void render(List<Contour> contours , int colors[] , BufferedImage out) { colors = checkColors(colors,contours.size()); for( int i = 0; i < contours.size(); i++ ) { Contour c = contours.get(i); int color = colors[i]; for(Point2D_I32 p : c.external ) { out.setRGB(p.x,p.y,color); } }...
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public static BufferedImage renderBinary(GrayU8 binaryImage, boolean invert, BufferedImage out) { if( out == null || ( out.getWidth() != binaryImage.width || out.getHeight() != binaryImage.height) ) { out = new BufferedImage(binaryImage.getWidth(),binaryImage.getHeight(),BufferedImage.TYPE_BYTE_GRAY); } try ...
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public void process(PairLineNorm line, AssociatedPair point) { // t0 = (F*x) cross l' GeometryMath_F64.mult(F,point.p1,Fx); GeometryMath_F64.cross(Fx,line.getL2(),t0); // t1 = x' cross ((f*x) cross l') GeometryMath_F64.cross(point.p2, t0, t1); // t0 = x' cross e' GeometryMath_F64.cross(point.p2,e2,t0); ...
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