List of usage examples for org.opencv.core Core divide
public static void divide(double scale, Mat src2, Mat dst)
From source file:Questao1.java
void divisao() { System.loadLibrary(Core.NATIVE_LIBRARY_NAME); Core.divide(image1, image2, output); Imgcodecs.imwrite("divisao.jpg", output); showResult("divisao.jpg"); }
From source file:ch.zhaw.facerecognitionlibrary.PreProcessor.BrightnessCorrection.GammaCorrection.java
License:Open Source License
public PreProcessor preprocessImage(PreProcessor preProcessor) { List<Mat> images = preProcessor.getImages(); List<Mat> processed = new ArrayList<Mat>(); for (Mat img : images) { img.convertTo(img, CvType.CV_32F); Core.divide(img, INT_MAX, img); Core.pow(img, gamma, img);//ww w . j a v a2s. com Core.multiply(img, INT_MAX, img); img.convertTo(img, CvType.CV_8U); processed.add(img); } preProcessor.setImages(processed); return preProcessor; }
From source file:ch.zhaw.facerecognitionlibrary.PreProcessor.PreProcessor.java
License:Open Source License
public void normalize01(Mat norm) { Core.normalize(norm, norm, 0.0, 1.0, Core.NORM_MINMAX, CvType.CV_64FC1); Core.MinMaxLocResult minmax = Core.minMaxLoc(norm); Scalar min = new Scalar(minmax.minVal); Core.subtract(norm, min, norm);/*from ww w . j ava 2s. c o m*/ minmax = Core.minMaxLoc(norm); Scalar max = new Scalar(minmax.maxVal); Core.divide(norm, max, norm); }
From source file:com.shootoff.camera.Camera.java
License:Open Source License
public static Mat colorTransfer(Mat source, Mat target) { Mat src = new Mat(); Mat dst = new Mat(); Imgproc.cvtColor(source, src, Imgproc.COLOR_BGR2Lab); Imgproc.cvtColor(target, dst, Imgproc.COLOR_BGR2Lab); ArrayList<Mat> src_channels = new ArrayList<Mat>(); ArrayList<Mat> dst_channels = new ArrayList<Mat>(); Core.split(src, src_channels);/*from w w w.j a v a2s . com*/ Core.split(dst, dst_channels); for (int i = 0; i < 3; i++) { MatOfDouble src_mean = new MatOfDouble(), src_std = new MatOfDouble(); MatOfDouble dst_mean = new MatOfDouble(), dst_std = new MatOfDouble(); Core.meanStdDev(src_channels.get(i), src_mean, src_std); Core.meanStdDev(dst_channels.get(i), dst_mean, dst_std); dst_channels.get(i).convertTo(dst_channels.get(i), CvType.CV_64FC1); Core.subtract(dst_channels.get(i), dst_mean, dst_channels.get(i)); Core.divide(dst_std, src_std, dst_std); Core.multiply(dst_channels.get(i), dst_std, dst_channels.get(i)); Core.add(dst_channels.get(i), src_mean, dst_channels.get(i)); dst_channels.get(i).convertTo(dst_channels.get(i), CvType.CV_8UC1); } Core.merge(dst_channels, dst); Imgproc.cvtColor(dst, dst, Imgproc.COLOR_Lab2BGR); return dst; }
From source file:com.wallerlab.compcellscope.calcDPCTask.java
License:BSD License
protected Long doInBackground(Mat... matrix_list) { //int count = urls.length; Mat in1 = matrix_list[0];/*from w w w . ja va 2s . c om*/ Mat in2 = matrix_list[1]; Mat outputMat = matrix_list[2]; Mat Mat1 = new Mat(in1.width(), in1.height(), in1.type()); Mat Mat2 = new Mat(in2.width(), in2.height(), in2.type()); in1.copyTo(Mat1); in2.copyTo(Mat2); Imgproc.cvtColor(Mat1, Mat1, Imgproc.COLOR_RGBA2GRAY, 1); Imgproc.cvtColor(Mat2, Mat2, Imgproc.COLOR_RGBA2GRAY, 1); Mat output = new Mat(Mat1.width(), Mat1.height(), CvType.CV_8UC4); Mat dpcSum = new Mat(Mat1.width(), Mat1.height(), CvType.CV_32FC1); Mat dpcDifference = new Mat(Mat1.width(), Mat1.height(), CvType.CV_32FC1); Mat dpcImgF = new Mat(Mat1.width(), Mat1.height(), CvType.CV_32FC1); /* Log.d(TAG,String.format("Mat1 format is %.1f-%.1f, type: %d",Mat1.size().width,Mat1.size().height,Mat1.type())); Log.d(TAG,String.format("Mat2 format is %.1f-%.1f, type: %d",Mat2.size().width,Mat2.size().height,Mat2.type())); */ // Convert to Floats Mat1.convertTo(Mat1, CvType.CV_32FC1); Mat2.convertTo(Mat2, CvType.CV_32FC1); Core.add(Mat1, Mat2, dpcSum); Core.subtract(Mat1, Mat2, dpcDifference); Core.divide(dpcDifference, dpcSum, dpcImgF); Core.add(dpcImgF, new Scalar(1.0), dpcImgF); // Normalize to 0-2.0 Core.multiply(dpcImgF, new Scalar(110), dpcImgF); // Normalize to 0-255 dpcImgF.convertTo(output, CvType.CV_8UC1); // Convert back into RGB Imgproc.cvtColor(output, output, Imgproc.COLOR_GRAY2RGBA, 4); dpcSum.release(); dpcDifference.release(); dpcImgF.release(); Mat1.release(); Mat2.release(); Mat maskedImg = Mat.zeros(output.rows(), output.cols(), CvType.CV_8UC4); int radius = maskedImg.width() / 2 + 25; Core.circle(maskedImg, new Point(maskedImg.width() / 2, maskedImg.height() / 2), radius, new Scalar(255, 255, 255), -1, 8, 0); output.copyTo(outputMat, maskedImg); output.release(); maskedImg.release(); return null; }
From source file:com.wallerlab.compcellscope.MultiModeViewActivity.java
License:BSD License
public Mat calcDPC(Mat in1, Mat in2, Mat out) { Mat Mat1 = new Mat(in1.width(), in1.height(), in1.type()); Mat Mat2 = new Mat(in2.width(), in2.height(), in2.type()); in1.copyTo(Mat1);//from ww w .j a v a 2 s. c om in2.copyTo(Mat2); Imgproc.cvtColor(Mat1, Mat1, Imgproc.COLOR_RGBA2GRAY, 1); Imgproc.cvtColor(Mat2, Mat2, Imgproc.COLOR_RGBA2GRAY, 1); Mat output = new Mat(Mat1.width(), Mat1.height(), CvType.CV_8UC4); Mat dpcSum = new Mat(Mat1.width(), Mat1.height(), CvType.CV_32FC1); Mat dpcDifference = new Mat(Mat1.width(), Mat1.height(), CvType.CV_32FC1); Mat dpcImgF = new Mat(Mat1.width(), Mat1.height(), CvType.CV_32FC1); /* Log.d(TAG,String.format("Mat1 format is %.1f-%.1f, type: %d",Mat1.size().width,Mat1.size().height,Mat1.type())); Log.d(TAG,String.format("Mat2 format is %.1f-%.1f, type: %d",Mat2.size().width,Mat2.size().height,Mat2.type())); */ // Convert to Floats Mat1.convertTo(Mat1, CvType.CV_32FC1); Mat2.convertTo(Mat2, CvType.CV_32FC1); Core.add(Mat1, Mat2, dpcSum); Core.subtract(Mat1, Mat2, dpcDifference); Core.divide(dpcDifference, dpcSum, dpcImgF); Core.add(dpcImgF, new Scalar(1.0), dpcImgF); // Normalize to 0-2.0 Core.multiply(dpcImgF, new Scalar(110), dpcImgF); // Normalize to 0-255 dpcImgF.convertTo(output, CvType.CV_8UC1); // Convert back into RGB Imgproc.cvtColor(output, output, Imgproc.COLOR_GRAY2RGBA, 4); dpcSum.release(); dpcDifference.release(); dpcImgF.release(); Mat1.release(); Mat2.release(); Mat maskedImg = Mat.zeros(output.rows(), output.cols(), CvType.CV_8UC4); int radius = maskedImg.width() / 2 + 25; Core.circle(maskedImg, new Point(maskedImg.width() / 2, maskedImg.height() / 2), radius, new Scalar(255, 255, 255), -1, 8, 0); output.copyTo(out, maskedImg); output.release(); maskedImg.release(); return out; }
From source file:ctPrincipal.Operacoes.java
String realizarOperacoes(int op) { String resultImgOutput = ""; switch (op) { case 1://and imagemBinaria();//from www. java2s . c om Core.bitwise_and(image1bin, image2bin, output); normalizarBinario(); Imgcodecs.imwrite("OutputImg/and.jpg", output); resultImgOutput = "OutputImg/and.jpg"; break; case 2://or imagemBinaria(); Core.bitwise_or(image1bin, image2bin, output); normalizarBinario(); Imgcodecs.imwrite("OutputImg/or.jpg", output); resultImgOutput = "OutputImg/or.jpg"; break; case 3://xor imagemBinaria(); Core.bitwise_xor(image1bin, image2bin, output); normalizarBinario(); Imgcodecs.imwrite("OutputImg/xor.jpg", output); resultImgOutput = "OutputImg/xor.jpg"; break; case 4://not Core.bitwise_not(image1bin, output); Imgcodecs.imwrite("OutputImg/not.jpg", output); resultImgOutput = "OutputImg/not.jpg"; break; case 5://soma Core.add(image1, image2, output); Imgcodecs.imwrite("OutputImg/soma.jpg", output); resultImgOutput = "OutputImg/soma.jpg"; break; case 6://subtracao Core.subtract(image1, image2, output); Imgcodecs.imwrite("OutputImg/subtracao.jpg", output); resultImgOutput = "OutputImg/subtracao.jpg"; break; case 7:// multiplicacao Core.multiply(image1, image2, output); Imgcodecs.imwrite("OutputImg/multiplicacao.jpg", output); resultImgOutput = "OutputImg/multiplicacao.jpg"; break; case 8://divisao Core.divide(image1, image2, output); Imgcodecs.imwrite("OutputImg/divisao.jpg", output); resultImgOutput = "OutputImg/divisao.jpg"; break; } return resultImgOutput; }
From source file:cx.uni.jk.mms.iaip.tools.SimpleBrushTool.java
License:Open Source License
/** * @param brush// www .j a v a 2 s . c o m * @param inverseEffect * @param workMat */ private void applyToWorkMat(BrushModel brush, boolean inverseEffect, Mat workMat) { switch (brush.getMode()) { case SET: { if (!inverseEffect) { /** set */ Core.add(workMat.mul(brush.getOneMinusAlphaMat()), brush.getMultipliedMat(), workMat); } else { /** clear */ Core.multiply(workMat, brush.getOneMinusAlphaMat(), workMat); } } break; case ADD: { if (!inverseEffect) { /** add */ Core.add(workMat, brush.getMultipliedMat(), workMat); } else { /** subtract */ Core.subtract(workMat, brush.getMultipliedMat(), workMat); } } break; case MULTIPLY: { if (!inverseEffect) { /** multiply */ Core.add(workMat.mul(brush.getOneMinusAlphaMat()), workMat.mul(brush.getMultipliedMat(), 0.01d), workMat); } else { /** multiply by 1/alpha. trick: divide twice ;) */ Core.divide(1.0d, workMat, workMat); Core.add(workMat.mul(brush.getOneMinusAlphaMat()), workMat.mul(brush.getMultipliedMat(), 0.01d), workMat); Core.divide(1.0d, workMat, workMat); } } break; default: /** do nothing */ } }