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AbstractField.java
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AbstractField.java
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package org.genericsystem.cv.retriever;
import java.lang.invoke.MethodHandles;
import java.text.Normalizer;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Map.Entry;
import java.util.stream.IntStream;
import org.genericsystem.cv.Img;
import org.genericsystem.cv.Ocr;
import org.genericsystem.cv.utils.OCRPlasty;
import org.genericsystem.cv.utils.OCRPlasty.RANSAC;
import org.genericsystem.cv.utils.OCRPlasty.Tuple;
import org.genericsystem.cv.utils.RectToolsMapper;
import org.genericsystem.reinforcer.tools.GSRect;
import org.genericsystem.reinforcer.tools.RectangleTools;
import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.MatOfPoint2f;
import org.opencv.core.Point;
import org.opencv.core.Rect;
import org.opencv.core.Scalar;
import org.opencv.imgproc.Imgproc;
import org.opencv.utils.Converters;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
public abstract class AbstractField {
protected static final Logger logger = LoggerFactory.getLogger(MethodHandles.lookup().lookupClass());
protected static final int MIN_SIZE_CONSOLIDATION = 5;
private static final int OCR_CONFIDENCE_THRESH = 0;
protected GSRect rect;
protected Map<String, Integer> labels;
protected String consolidated;
protected double confidence;
protected long attempts;
protected int deadCounter;
public AbstractField() {
this(new GSRect());
}
public AbstractField(GSRect rect) {
this.rect=rect;
this.labels = new HashMap<>();
this.consolidated = null;
this.attempts = 0;
this.confidence = 0;
this.deadCounter = 0;
}
public AbstractField(AbstractField other) {
this.rect=other.getRect();
this.labels = other.getLabels();
this.consolidated = other.getConsolidated();
this.attempts = other.getAttempts();
this.confidence = other.getConfidence();
this.deadCounter = other.getDeadCounter();
}
void updateRect(GSRect rect) {
this.rect = rect;
}
public void ocr(Img rootImg) {
if (rootImg.getSrc().empty() || rootImg.getSrc().width() <= 3 || rootImg.getSrc().height() <= 3)
return;
Rect largeRect = getLargeRect(rootImg, 0.03, 0.1);
if (largeRect.empty() || largeRect.width <= 3 || largeRect.height <= 3)
return;
// Prevent OpenCV assertion failure
if (!(0 <= largeRect.x && 0 <= largeRect.y && largeRect.x + largeRect.width < rootImg.getSrc().cols() && largeRect.y + largeRect.height < rootImg.getSrc().rows()))
return;
Mat roi = new Mat(rootImg.getSrc(), largeRect);
String ocr = Ocr.doWork(roi, OCR_CONFIDENCE_THRESH);
if (!ocr.isEmpty()) {
labels.merge(ocr, 1, Integer::sum);
attempts++;
}
roi.release();
}
public void consolidateOcr(boolean force) {
consolidateOcr(Integer.MAX_VALUE, force);
}
protected void consolidateOcr(int limit, boolean force) {
int labelsSize = getLabelsSize();
if (force || labelsSize >= MIN_SIZE_CONSOLIDATION) {
List<String> strings;
if (Integer.MAX_VALUE == limit)
strings = labels.entrySet().stream().collect(ArrayList<String>::new, (list, e) -> IntStream.range(0, e.getValue()).forEach(count -> list.add(e.getKey())), List::addAll);
else
strings = labels.entrySet().stream().sorted(Entry.<String, Integer>comparingByValue().reversed()).limit(limit).collect(ArrayList<String>::new, (list, e) -> IntStream.range(0, e.getValue()).forEach(count -> list.add(e.getKey())),
List::addAll);
Tuple res = OCRPlasty.correctStringsAndGetOutliers(strings, RANSAC.NORM_LEVENSHTEIN);
this.consolidated = res.getString().orElse(null);
this.confidence = res.getConfidence();
if (labelsSize >= 2 * MIN_SIZE_CONSOLIDATION)
res.getOutliers().forEach(outlier -> labels.remove(outlier));
} else {
logger.trace("Not enough labels to consolidate OCR (current minimum = {})", MIN_SIZE_CONSOLIDATION);
this.consolidated = null;
this.confidence = 0;
}
}
public void drawOcrPerspectiveInverse(Img display, Mat homography, Scalar color, int thickness) {
Point[] targets = getRectPointsWithHomography(homography);
drawRect(display, targets, deadCounter == 0 ? color : new Scalar(0, 0, 255), thickness);
drawText(display, targets, new Scalar(0, 64, 255), thickness);
}
public void drawRect(Img stabilizedDisplay, Scalar color, int thickness) {
Point[] points = RectToolsMapper.gsPointToPoint(Arrays.asList(rect.decomposeClockwise())).toArray(new Point[0]);
drawRect(stabilizedDisplay, points, color, thickness);
}
public void drawRect(Img display, Point[] targets, Scalar color, int thickness) {
for (int i = 0; i < targets.length; ++i)
Imgproc.line(display.getSrc(), targets[i], targets[(i + 1) % targets.length], color, thickness);
}
public void drawText(Img display, Point[] targets, Scalar color, int thickness) {
if (consolidated != null) {
String text = Normalizer.normalize(consolidated, Normalizer.Form.NFD).replaceAll("[^\\p{ASCII}]", "");
String conf = String.format("%.3f", confidence);
// --- //
Point topCenter = new Point((targets[0].x + targets[1].x) / 2, (targets[0].y + targets[1].y) / 2);
double l = Math.sqrt(Math.pow(targets[0].x - topCenter.x, 2) + Math.pow(targets[0].y - topCenter.y, 2));
Imgproc.line(display.getSrc(), new Point(topCenter.x, topCenter.y - 2), new Point(topCenter.x, topCenter.y - 20), color, 1);
Imgproc.putText(display.getSrc(), text, new Point(topCenter.x - l, topCenter.y - 22), Core.FONT_HERSHEY_TRIPLEX, 0.45, color, 1);
Imgproc.putText(display.getSrc(), conf, new Point(topCenter.x - l, topCenter.y - 12), Core.FONT_HERSHEY_TRIPLEX, 0.35, color.conj());
}
}
protected Point[] getRectPointsWithHomography(Mat homography) {
List<Point> points = RectToolsMapper.gsPointToPoint(Arrays.asList(rect.decomposeClockwise()));
MatOfPoint2f results = new MatOfPoint2f();
Core.perspectiveTransform(Converters.vector_Point2f_to_Mat(points), results, homography);
return results.toArray();
}
public Rect getLargeRect(Img imgRoot, double deltaW, double deltaH) {
int adjustW = 3 + Double.valueOf(Math.floor(rect.getWidth() * deltaW)).intValue();
int adjustH = 3 + Double.valueOf(Math.floor(rect.getHeight() * deltaH)).intValue();
Point tl = new Point(rect.tl().getX() - adjustW > 0 ? rect.tl().getX() - adjustW : 0, rect.tl().getY() - adjustH > 0 ? rect.tl().getY() - adjustH : 0);
Point br = new Point(rect.br().getX() + adjustW > imgRoot.width() ? imgRoot.width() : rect.br().getX() + adjustW, rect.br().getY() + adjustH > imgRoot.height() ? imgRoot.height() : rect.br().getY() + adjustH);
return new Rect(tl, br);
}
public boolean isOverlapping(GSRect otherRect) {
return this.rect.isOverlapping(otherRect);
}
public boolean overlapsMoreThanThresh(GSRect otherRect, double overlapThreshold) {
return this.rect.inclusiveArea(otherRect) > overlapThreshold;
}
public boolean isClusteredWith(GSRect otherRect, double epsilon) {
return RectangleTools.isInCluster(this.rect, otherRect, epsilon);
}
public boolean isClusteredWith(GSRect otherRect, double epsilon, int sides) {
return RectangleTools.isInCluster(this.rect, otherRect, epsilon, sides);
}
public boolean isOnDisplay(Img display) {
GSRect imgRect = new GSRect(0, 0, display.width(), display.height());
return imgRect.isOverlapping(this.rect);
}
public boolean isConsolidated() {
return consolidated != null;
}
public void incrementDeadCounter() {
deadCounter++;
}
public void resetDeadCounter() {
deadCounter = 0;
}
public int getLabelsSize() {
return labels.entrySet().stream().mapToInt(entry -> entry.getValue()).sum();
}
public Map<String, Integer> getLabels() {
return labels;
}
public String getConsolidated() {
return consolidated;
}
public long getAttempts() {
return attempts;
}
public GSRect getRect() {
return rect;
}
public double getConfidence() {
return confidence;
}
public int getDeadCounter() {
return deadCounter;
}
}