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CamLiveRetriever.java
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CamLiveRetriever.java
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package org.genericsystem.cv.classifier;
import java.lang.invoke.MethodHandles;
import java.util.ArrayList;
import java.util.List;
import java.util.concurrent.Executors;
import java.util.concurrent.ScheduledExecutorService;
import java.util.concurrent.TimeUnit;
import java.util.stream.Collectors;
import org.genericsystem.cv.AbstractApp;
import org.genericsystem.cv.Img;
import org.genericsystem.cv.utils.NativeLibraryLoader;
import org.genericsystem.cv.utils.Tools;
import org.opencv.calib3d.Calib3d;
import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.DMatch;
import org.opencv.core.KeyPoint;
import org.opencv.core.Mat;
import org.opencv.core.MatOfDMatch;
import org.opencv.core.MatOfKeyPoint;
import org.opencv.core.MatOfPoint;
import org.opencv.core.MatOfPoint2f;
import org.opencv.core.Point;
import org.opencv.core.Rect;
import org.opencv.core.RotatedRect;
import org.opencv.core.Scalar;
import org.opencv.core.Size;
import org.opencv.features2d.DescriptorExtractor;
import org.opencv.features2d.DescriptorMatcher;
import org.opencv.imgproc.Imgproc;
import org.opencv.utils.Converters;
import org.opencv.videoio.VideoCapture;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import javafx.scene.image.ImageView;
import javafx.scene.layout.GridPane;
public class CamLiveRetriever extends AbstractApp {
private static final Logger logger = LoggerFactory.getLogger(MethodHandles.lookup().lookupClass());
private MatOfKeyPoint oldKeypoints;
private MatOfKeyPoint newKeypoints;
private Mat oldDescriptors;
private Mat newDescriptors;
// private Layout layout;
private final Fields fields = new Fields();
private boolean stabilizationHasChanged = true;
Mat homography = null;
Mat frame = new Mat();
double angle = 0;
static {
NativeLibraryLoader.load();
}
public static void main(String[] args) {
launch(args);
}
private final VideoCapture capture = new VideoCapture(0);
private final ScheduledExecutorService timer = Executors.newSingleThreadScheduledExecutor();
@Override
protected void fillGrid(GridPane mainGrid) {
// FeatureDetector detector = FeatureDetector.create(FeatureDetector.FAST);
DescriptorExtractor extractor = DescriptorExtractor.create(DescriptorExtractor.ORB);
DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING);
capture.read(frame);
ImageView src0 = new ImageView(Tools.mat2jfxImage(frame));
mainGrid.add(src0, 0, 0);
ImageView src1 = new ImageView(Tools.mat2jfxImage(frame));
// ImageView src2 = new ImageView(Tools.mat2jfxImage(frame));
// ImageView src3 = new ImageView(Tools.mat2jfxImage(frame));
mainGrid.add(src1, 0, 1);
// mainGrid.add(src2, 1, 0);
// mainGrid.add(src3, 0, 1);
oldKeypoints = new MatOfKeyPoint();
oldDescriptors = new Mat();
Mat stabilizedMat = new Mat();
timer.scheduleAtFixedRate(() -> {
synchronized (this) {
try {
capture.read(frame);
Img frameImg = new Img(frame, false).bilateralFilter(5, 100, 100);
Img deskewed_ = deskew(frameImg);
newKeypoints = detect(deskewed_);
newDescriptors = new Mat();
extractor.compute(deskewed_.getSrc(), newKeypoints, newDescriptors);
// Img deskiewedCopy = new Img(deskewed_.getSrc(), true);
// Img binary = deskewed_/* .cleanFaces(0.1, 0.26) */.adaptativeGaussianThreshold(17, 7).cleanTables(0.05);
// binary.buildLayout().draw(deskiewedCopy, new Scalar(0, 255, 0), 1);
Img stabilized = stabilize(stabilizedMat, matcher);
if (stabilized != null) {
if (stabilizationHasChanged) {
fields.merge(detectRects(stabilized));
stabilizationHasChanged = false;
}
// layout.ocrTree(stabilized, 0.03, 0.1);
Img display = new Img(frame, true);
// layout.drawOcrPerspectiveInverse(display, homography[0].inv(), new Scalar(0, 0, 255), 1);
Img stabilizedDisplay = new Img(stabilized.getSrc(), true);
fields.consolidateOcr(stabilized);
// fields.drawConsolidated(stabilizedDisplay);
fields.drawOcrPerspectiveInverse(display, homography.inv(), new Scalar(0, 0, 255), 1);
src0.setImage(display.toJfxImage());
// src1.setImage(old.absDiff(new Img(frame, false)).adaptativeGaussianInvThreshold(17, 9).morphologyEx(Imgproc.MORPH_CLOSE, Imgproc.MORPH_ELLIPSE, new Size(5, 5)).toJfxImage());// deskewed_.toJfxImage());
// src2.setImage(deskiewedCopy.toJfxImage());
src1.setImage(stabilizedDisplay.toJfxImage());
}
} catch (Throwable e) {
logger.warn("Exception while computing layout.", e);
}
}
}, 500, 33, TimeUnit.MILLISECONDS);
timer.scheduleAtFixedRate(() -> onSpace(), 0, 110, TimeUnit.MILLISECONDS);
}
@Override
protected synchronized void onSpace() {
if (homography != null) {
fields.storeLastHomography(homography.inv());
fields.storeLastRotation(Imgproc.getRotationMatrix2D(new Point(frame.width() / 2, frame.height() / 2), angle, 1));
}
oldKeypoints = newKeypoints;
oldDescriptors = newDescriptors;
stabilizationHasChanged = true;
}
private Img stabilize(Mat stabilized, DescriptorMatcher matcher) {
MatOfDMatch matches = new MatOfDMatch();
if (oldDescriptors != null && !oldDescriptors.empty() && (!newDescriptors.empty())) {
matcher.match(oldDescriptors, newDescriptors, matches);
List<DMatch> goodMatches = new ArrayList<>();
for (DMatch dMatch : matches.toArray()) {
if (dMatch.distance <= 40) {
goodMatches.add(dMatch);
}
}
List<KeyPoint> newKeypoints_ = newKeypoints.toList();
List<KeyPoint> oldKeypoints_ = oldKeypoints.toList();
// System.out.println(goodMatches.size() + " " + newKeypoints_.size() + " " + oldKeypoints_.size());
List<Point> goodNewKeypoints = new ArrayList<>();
List<Point> goodOldKeypoints = new ArrayList<>();
for (DMatch goodMatch : goodMatches) {
goodNewKeypoints.add(newKeypoints_.get(goodMatch.trainIdx).pt);
goodOldKeypoints.add(oldKeypoints_.get(goodMatch.queryIdx).pt);
}
if (goodMatches.size() > 30) {
Mat goodNewPoints = Converters.vector_Point2f_to_Mat(goodNewKeypoints);
MatOfPoint2f originalNewPoints = new MatOfPoint2f();
Core.transform(goodNewPoints, originalNewPoints, Imgproc.getRotationMatrix2D(new Point(frame.size().width / 2, frame.size().height / 2), -angle, 1));
homography = Calib3d.findHomography(originalNewPoints, new MatOfPoint2f(goodOldKeypoints.stream().toArray(Point[]::new)), Calib3d.RANSAC, 10);
Mat mask = new Mat(frame.size(), CvType.CV_8UC1, new Scalar(255));
Mat maskWarpped = new Mat();
Imgproc.warpPerspective(mask, maskWarpped, homography, frame.size());
Mat tmp = new Mat();
Imgproc.warpPerspective(frame, tmp, homography, frame.size(), Imgproc.INTER_LINEAR, Core.BORDER_REPLICATE, Scalar.all(255));
tmp.copyTo(stabilized, maskWarpped);
return new Img(stabilized, false);
}
}
System.out.println("No stabilized image");
return null;
}
private List<Rect> detectRects(Img stabilized) {
List<MatOfPoint> contours = new ArrayList<>();
Img closed = stabilized.adaptativeGaussianInvThreshold(7, 3).morphologyEx(Imgproc.MORPH_CLOSE, Imgproc.MORPH_RECT, new Size(9, 1));
Imgproc.findContours(closed.getSrc(), contours, new Mat(), Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
return contours.stream().filter(contour -> Imgproc.contourArea(contour) > 200).map(c -> Imgproc.boundingRect(c)).collect(Collectors.toList());
}
private MatOfKeyPoint detect(Img frame) {
Img closed = frame.adaptativeGaussianInvThreshold(17, 3).morphologyEx(Imgproc.MORPH_CLOSE, Imgproc.MORPH_ELLIPSE, new Size(5, 5));
List<MatOfPoint> contours = new ArrayList<>();
Imgproc.findContours(closed.getSrc(), contours, new Mat(), Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
double minArea = 100;
List<KeyPoint> keyPoints = new ArrayList<>();
contours.stream().filter(contour -> Imgproc.contourArea(contour) > minArea).map(Imgproc::boundingRect).forEach(rect -> {
keyPoints.add(new KeyPoint((float) rect.tl().x, (float) rect.tl().y, 6));
keyPoints.add(new KeyPoint((float) rect.tl().x, (float) rect.br().y, 6));
keyPoints.add(new KeyPoint((float) rect.br().x, (float) rect.tl().y, 6));
keyPoints.add(new KeyPoint((float) rect.br().x, (float) rect.br().y, 6));
});
return new MatOfKeyPoint(keyPoints.stream().toArray(KeyPoint[]::new));
}
private Img deskew(Img frame) {
Img closed = frame.adaptativeGaussianInvThreshold(17, 3).morphologyEx(Imgproc.MORPH_CLOSE, Imgproc.MORPH_ELLIPSE, new Size(5, 5));
angle = detection_contours(frame.getSrc(), closed.getSrc());
Mat matrix = Imgproc.getRotationMatrix2D(new Point(frame.width() / 2, frame.height() / 2), angle, 1);
Mat rotated = new Mat(frame.size(), CvType.CV_8UC3, new Scalar(255, 255, 255));
Imgproc.warpAffine(frame.getSrc(), rotated, matrix, frame.size());
return new Img(rotated);
}
private double detection_contours(Mat frame, Mat dilated) {
List<MatOfPoint> contours = new ArrayList<>();
Imgproc.findContours(dilated, contours, new Mat(), Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
double minArea = 100;
// double crop = 0;
// Predicate<RotatedRect> filter = rect -> rect.center.x > Double.valueOf(frame.width() * crop).intValue() && rect.center.y > Double.valueOf(frame.height() * crop).intValue() && rect.center.x < Double.valueOf(frame.width() * (1 - crop)).intValue()
// && rect.center.y < Double.valueOf(frame.height() * (1 - crop)).intValue();
List<RotatedRect> rotatedRects = contours.stream().filter(contour -> Imgproc.contourArea(contour) > minArea).map(contour -> Imgproc.minAreaRect(new MatOfPoint2f(contour.toArray())))/* .filter(filter) */.collect(Collectors.toList());
for (RotatedRect rotatedRect : rotatedRects) {
if (rotatedRect.angle <= -45.) {
rotatedRect.angle += 90.0;
double tmp = rotatedRect.size.width;
rotatedRect.size.width = rotatedRect.size.height;
rotatedRect.size.height = tmp;
}
}
final double average = rotatedRects.stream().mapToDouble(r -> r.angle).average().getAsDouble();
List<RotatedRect> goodRects = rotatedRects.stream().filter(rotatedRect -> Math.abs(rotatedRect.angle - average) < 5).collect(Collectors.toList());
return goodRects.stream().mapToDouble(r -> r.angle).average().orElse(average);
}
@Override
public void stop() throws Exception {
super.stop();
timer.shutdown();
timer.awaitTermination(5000, TimeUnit.MILLISECONDS);
capture.release();
}
}