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AbstractField.java
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AbstractField.java
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package org.genericsystem.cv.classifier;
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.Optional;
import java.util.concurrent.ThreadLocalRandom;
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.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());
private static ThreadLocalRandom rand = ThreadLocalRandom.current();
protected static final int MIN_SIZE_CONSOLIDATION = 5;
protected Rect rect;
protected Point center;
protected Map<String, Integer> labels;
protected Optional<String> consolidated;
protected double confidence;
protected long attempts;
protected int deadCounter;
public AbstractField(Rect rect) {
this.rect = rect;
this.labels = new HashMap<>();
this.consolidated = Optional.empty();
this.center = new Point(rect.x + rect.width / 2, rect.y + rect.height / 2);
this.attempts = 0;
this.confidence = 0;
this.deadCounter = 0;
}
public void merge(AbstractField field) {
field.getLabels().entrySet().forEach(entry -> labels.merge(entry.getKey(), entry.getValue(), Integer::sum));
attempts += field.getAttempts();
deadCounter += field.getDeadCounter();
consolidateOcr();
}
public void ocr(Img rootImg) {
if (rootImg.getSrc().empty())
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);
if (!ocr.isEmpty()) {
labels.merge(ocr, 1, Integer::sum);
attempts++;
}
roi.release();
}
protected void consolidateOcr() {
consolidateOcr(Integer.MAX_VALUE);
}
protected void consolidateOcr(int limit) {
int labelsSize = getLabelsSize();
if (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();
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 = Optional.empty();
this.confidence = 0;
}
}
public void draw(Img stabilizedDisplay) {
Imgproc.rectangle(stabilizedDisplay.getSrc(), rect.tl(), rect.br(), new Scalar(0, 0, 255));
}
public void drawOcrPerspectiveInverse(Img display, Mat homography, Scalar color, int thickness) {
if (isOnDisplay(display)) {
Scalar scalar = new Scalar(0, 64, 255);
String text = consolidated.orElse("");
String conf = String.format("%.3f", confidence);
List<Point> points = Arrays.asList(center, new Point(rect.x, rect.y), new Point(rect.x + rect.width - 1, rect.y), new Point(rect.x + rect.width - 1, rect.y + rect.height - 1), new Point(rect.x, rect.y + rect.height - 1));
MatOfPoint2f results = new MatOfPoint2f();
Core.perspectiveTransform(Converters.vector_Point2f_to_Mat(points), results, homography);
Point[] targets = results.toArray();
Imgproc.line(display.getSrc(), targets[1], targets[2], color, thickness);
Imgproc.line(display.getSrc(), targets[2], targets[3], color, thickness);
Imgproc.line(display.getSrc(), targets[3], targets[4], color, thickness);
Imgproc.line(display.getSrc(), targets[4], targets[1], color, thickness);
Point topCenter = new Point((targets[1].x + targets[2].x) / 2, (targets[1].y + targets[2].y) / 2);
double l = Math.sqrt(Math.pow(targets[1].x - topCenter.x, 2) + Math.pow(targets[1].y - topCenter.y, 2));
Imgproc.line(display.getSrc(), new Point(topCenter.x, topCenter.y - 2), new Point(topCenter.x, topCenter.y - 20), scalar, 1);
Imgproc.putText(display.getSrc(), Normalizer.normalize(text, Normalizer.Form.NFD).replaceAll("[^\\p{ASCII}]", ""), new Point(topCenter.x - l, topCenter.y - 22), Core.FONT_HERSHEY_TRIPLEX, 0.45, scalar, 1);
Imgproc.putText(display.getSrc(), conf, new Point(topCenter.x - l, topCenter.y - 12), Core.FONT_HERSHEY_TRIPLEX, 0.35, scalar.conj());
}
}
public Rect getLargeRect(Img imgRoot, double deltaW, double deltaH) {
int adjustW = 3 + Double.valueOf(Math.floor(rect.width * deltaW)).intValue();
int adjustH = 3 + Double.valueOf(Math.floor(rect.height * deltaH)).intValue();
Point tl = new Point(rect.tl().x - adjustW > 0 ? rect.tl().x - adjustW : 0, rect.tl().y - adjustH > 0 ? rect.tl().y - adjustH : 0);
Point br = new Point(rect.br().x + adjustW > imgRoot.width() ? imgRoot.width() : rect.br().x + adjustW, rect.br().y + adjustH > imgRoot.height() ? imgRoot.height() : rect.br().y + adjustH);
return new Rect(tl, br);
}
public boolean contains(Point center) {
return Math.sqrt(Math.pow(this.center.x - center.x, 2) + Math.pow(this.center.y - center.y, 2)) <= 10;
}
public boolean isOverlapping(Rect otherRect) {
return RectangleTools.isOverlapping(this.rect, otherRect);
}
public boolean isOverlapping(AbstractField other) {
return isOverlapping(other.getRect());
}
public boolean isIn(AbstractField other) {
return RectangleTools.getInsider(rect, other.getRect()).map(r -> r.equals(rect) ? true : false).orElse(false);
}
public boolean overlapsMoreThanThresh(Rect otherRect, double overlapThreshold) {
return RectangleTools.inclusiveArea(this.rect, otherRect) > overlapThreshold;
}
public boolean isClusteredWith(Rect otherRect, double epsilon) {
return RectangleTools.isInCluster(this.rect, otherRect, epsilon);
}
public boolean overlapsMoreThanThresh(AbstractField other, double overlapThreshold) {
return overlapsMoreThanThresh(other.getRect(), overlapThreshold);
}
public boolean isOnDisplay(Img display) {
Rect imgRect = new Rect(0, 0, display.width(), display.height());
return RectangleTools.isOverlapping(imgRect, this.rect);
}
public boolean isConsolidated() {
return consolidated.isPresent();
}
public boolean needOcr() {
return rand.nextBoolean();
}
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 Optional<String> getConsolidated() {
return consolidated;
}
public long getAttempts() {
return attempts;
}
public Point getCenter() {
return center;
}
public Rect getRect() {
return rect;
}
public double getConfidence() {
return confidence;
}
public int getDeadCounter() {
return deadCounter;
}
@Override
public String toString() {
StringBuffer sb = new StringBuffer();
sb.append("AbstractField: ").append("\n").append(" -> rect: ").append(rect).append("\n").append(" -> labels size: ").append(labels.size()).append("\n").append(" -> consolidated: ").append(consolidated).append("\n").append(" -> confidence: ")
.append(confidence).append("\n");
return sb.toString();
}
@Override
public int hashCode() {
final int prime = 31;
int result = 1;
result = prime * result + ((center == null) ? 0 : center.hashCode());
long temp;
temp = Double.doubleToLongBits(confidence);
result = prime * result + (int) (temp ^ (temp >>> 32));
result = prime * result + ((consolidated == null) ? 0 : consolidated.hashCode());
result = prime * result + ((labels == null) ? 0 : labels.hashCode());
result = prime * result + ((rect == null) ? 0 : rect.hashCode());
return result;
}
@Override
public boolean equals(Object obj) {
if (this == obj)
return true;
if (obj == null)
return false;
if (getClass() != obj.getClass())
return false;
AbstractField other = (AbstractField) obj;
if (center == null) {
if (other.center != null)
return false;
} else if (!center.equals(other.center))
return false;
if (Double.doubleToLongBits(confidence) != Double.doubleToLongBits(other.confidence))
return false;
if (consolidated == null) {
if (other.consolidated != null)
return false;
} else if (!consolidated.equals(other.consolidated))
return false;
if (labels == null) {
if (other.labels != null)
return false;
} else if (!labels.equals(other.labels))
return false;
if (rect == null) {
if (other.rect != null)
return false;
} else if (!rect.equals(other.rect))
return false;
return true;
}
}