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Contour class, findContour function and contour finding example
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30 files changed

Lines changed: 579 additions & 53 deletions

‎.DS_Store‎

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‎distribution/OpenCVPro-1/download/OpenCVPro-1.zip‎

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‎distribution/OpenCVPro-1/download/OpenCVPro.zip‎

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‎distribution/OpenCVPro-1/examples/BackgroundSubtraction/BackgroundSubtraction.pde‎

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Original file line numberDiff line numberDiff line change
@@ -7,27 +7,29 @@ PImage before, after, colorDiff, grayDiff;
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void setup() {
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before = loadImage("before.jpg");
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after = loadImage("after.jpg");
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size(before.width, before.height);
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size(before.width, before.height, P2D);
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beforeCv = new OpenCVPro(this, before);
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afterCv = new OpenCVPro(this, after);
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// NOTE: important to not do the color diff
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// before calling these, as this makes
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// the gray buffer from the current color buffer.
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beforeCv.gray();
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afterCv.gray();
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OpenCVPro.diff(beforeCv.getBufferColor(), afterCv.getBufferColor());
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OpenCVPro.diff(beforeCv.getBufferGray(), afterCv.getBufferGray());
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colorDiff = beforeCv.getColorImage();
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// FIXME: same mysterious problem with getOutputImage()
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colorDiff = createImage(before.width, before.height, RGB);
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beforeCv.toPImage(beforeCv.getBufferColor(), colorDiff);
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grayDiff = createImage(before.width, before.height, RGB);
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beforeCv.toPImage(beforeCv.getBufferGray(), grayDiff);
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// colorDiff = createImage(before.width, before.height, RGB);
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// beforeCv.toPImage(beforeCv.getBufferColor(), colorDiff);
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// colorDiff = beforeCv.getColorImage();
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grayDiff = beforeCv.getGrayImage();
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}
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void draw() {
@@ -38,11 +40,11 @@ void draw() {
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image(colorDiff, 0, before.height);
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image(grayDiff, before.width, before.height);
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popMatrix();
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fill(255);
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text("before", 10, 20);
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text("after", before.width/2 +10, 20);
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text("color diff", 10, before.height/2+ 20);
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text("gray diff", before.width/2 + 10, before.height/2+ 20);
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}
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‎distribution/OpenCVPro-1/examples/FindContours/FindContours.pde‎

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import gab.opencvpro.*;
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import org.opencv.imgproc.Imgproc;
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import org.opencv.core.Core;
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import org.opencv.core.Mat;
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import org.opencv.core.MatOfPoint;
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import org.opencv.core.Point;
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PImage src, dst;
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OpenCVPro opencv;
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ArrayList<Contour> contours;
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void setup() {
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src = loadImage("test.jpg");
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size(src.width, src.height/2, P2D);
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opencv = new OpenCVPro(this, src);
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opencv.gray();
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opencv.threshold(50);
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contours = findContours(opencv.getBufferGray());
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dst = opencv.getGrayImage();
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println("numContours: " + contours.size());
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}
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void draw() {
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scale(0.5);
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image(src, 0, 0);
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image(dst, src.width, 0);
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noFill();
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stroke(255);
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for(Contour contour : contours){
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if(contour.points.size() > 20 && contour.points.size() < 1000){
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contour.draw();
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}
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}
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}
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void drawContour(Contour c){
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void draw(){
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beginShape();
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for(PVector point : c.points){
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vertex(point.x, point.y);
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}
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endShape();
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}
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}
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// find contours works on a binary image,
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// so you have to threshold it (or otherwise make it binary) first
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// in order to get a good result
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ArrayList<Contour> findContours(Mat buffer){
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ArrayList<MatOfPoint> cs = new ArrayList<MatOfPoint>();
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Imgproc.findContours(buffer, cs, new Mat(), Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_NONE);
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ArrayList<Contour> result = new ArrayList<Contour>();
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for(MatOfPoint c : cs){
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result.add(new Contour(c));
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}
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return result;
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}

‎distribution/OpenCVPro-1/examples/FindContours/test.jpg‎

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‎distribution/OpenCVPro-1/examples/FindEdges/FindEdges.pde‎

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Original file line numberDiff line numberDiff line change
@@ -5,7 +5,7 @@ PImage src, canny, scharr, sobel;
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void setup() {
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src = loadImage("test.jpg");
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size(src.width, src.height);
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size(src.width, src.height, P2D);
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cannyFilter = new OpenCVPro(this, src);
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scharrFilter = new OpenCVPro(this, src);
@@ -14,7 +14,7 @@ void setup() {
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sobelFilter.gray();
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cannyFilter.findCannyEdges(20, 75);
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scharrFilter.findScharrY();
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scharrFilter.findScharrX(); // also try: scharrFilter.findScharrY()
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sobelFilter.findSobelEdges(1,0);
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canny = cannyFilter.getColorImage();

‎distribution/OpenCVPro-1/examples/HistogramSkinDetection/HistogramSkinDetection.pde‎

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import gab.opencvpro.*;
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import org.opencv.core.Core;
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import org.opencv.core.Mat;
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import org.opencv.core.Size;
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import org.opencv.core.Point;
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import org.opencv.core.Scalar;
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import org.opencv.core.CvType;
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import org.opencv.imgproc.Imgproc;
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OpenCVPro opencv;
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PImage src,dst, hist, histMask;
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Mat skinHistogram;
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void setup(){
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src = loadImage("test.jpg");
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src.resize(src.width/2, 0);
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size(src.width*2 + 256, src.height, P2D);
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opencv = new OpenCVPro(this, src);
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skinHistogram = Mat.zeros(256, 256, CvType.CV_8UC1);
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Core.ellipse(skinHistogram, new Point(113.0, 155.6), new Size(40.0, 25.2), 43.0, 0.0, 360.0, new Scalar(255, 255, 255), Core.FILLED);
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histMask = createImage(256,256, ARGB);
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opencv.toPImage(skinHistogram, histMask);
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hist = loadImage("cb-cr.png");
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hist.blend(histMask, 0,0,256,256,0,0,256,256, ADD);
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dst = opencv.getColorImage();
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dst.loadPixels();
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for(int i = 0; i < dst.pixels.length; i++){
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Mat input = new Mat(new Size(1, 1), CvType.CV_8UC3);
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input.setTo(colorToScalar(dst.pixels[i]));
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Mat output = opencv.imitate(input);
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Imgproc.cvtColor(input, output, Imgproc.COLOR_BGR2YCrCb );
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double[] inputComponents = output.get(0,0);
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if(skinHistogram.get((int)inputComponents[1], (int)inputComponents[2])[0] > 0){
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dst.pixels[i] = color(255);
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} else {
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dst.pixels[i] = color(0);
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}
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}
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dst.updatePixels();
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}
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// in BGR
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Scalar colorToScalar(color c){
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return new Scalar(blue(c), green(c), red(c));
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}
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void draw(){
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image(src,0,0);
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image(dst, src.width, 0);
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image(hist, src.width*2, 0);
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}

‎distribution/OpenCVPro-1/examples/HistogramSkinDetection/data/cb-cr.png‎

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‎distribution/OpenCVPro-1/examples/HistogramSkinDetection/data/test.jpg‎

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