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Fields.java
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Fields.java
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package org.genericsystem.cv.classifier;
import java.lang.invoke.MethodHandles;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.HashSet;
import java.util.Iterator;
import java.util.List;
import java.util.Set;
import java.util.concurrent.ThreadLocalRandom;
import java.util.stream.Collectors;
import org.genericsystem.cv.Img;
import org.genericsystem.cv.utils.ParallelTasks;
import org.genericsystem.cv.utils.RectToolsMapper;
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.utils.Converters;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
public class Fields extends AbstractFields<Field> {
private static final Logger logger = LoggerFactory.getLogger(MethodHandles.lookup().lookupClass());
private static ThreadLocalRandom rand = ThreadLocalRandom.current();
private static final int MAX_DELETE_UNMERGED = 5;
private static final int OCR_TIMEOUT = 50;
private static final double MIN_OVERLAP = 0.2;
public void reset() {
fields = new ArrayList<>();
}
public void merge(List<Rect> newRects) {
List<Field> oldFields = fields;
fields = buildNewFields(newRects, 0.5);
Iterator<Field> it = oldFields.iterator();
while (it.hasNext()) {
Field currentOldField = it.next();
List<Field> matches = findClusteredFields(currentOldField, 0.1);
if (!matches.isEmpty()) {
// Remove the false positives
matches = matches.stream().filter(f -> RectToolsMapper.inclusiveArea(f.getRect(), currentOldField.getRect()) > MIN_OVERLAP / 10).collect(Collectors.toList());
// If there is more than one match, select only the best
if (matches.size() > 1) {
logger.info("Multiple matches ({}), removing false positives", matches.size());
// Remove the overlaps with less than 10% common area
matches = matches.stream().filter(f -> RectToolsMapper.inclusiveArea(f.getRect(), currentOldField.getRect()) >= MIN_OVERLAP).collect(Collectors.toList());
if (matches.size() > 1) {
logger.warn("Still multiple matches ({}), selecting the maximum overlap", matches.size());
matches = Arrays.asList(matches.stream().max((f1, f2) -> {
double area1 = RectToolsMapper.inclusiveArea(f1.getRect(), currentOldField.getRect());
double area2 = RectToolsMapper.inclusiveArea(f2.getRect(), currentOldField.getRect());
return Double.compare(area1, area2);
}).orElseThrow(IllegalStateException::new));
}
}
matches.forEach(f -> {
double mergeArea = RectToolsMapper.inclusiveArea(f.getRect(), currentOldField.getRect());
StringBuffer sb = new StringBuffer();
sb.append(String.format("Merging fields with %.1f%% common area", mergeArea * 100));
currentOldField.getConsolidated().ifPresent(s -> sb.append(String.format(" -> %s", s)));
logger.info(sb.toString());
f.merge(currentOldField);
f.resetDeadCounter();
});
it.remove();
} else
logger.info("No match for : " + currentOldField.getLabels().keySet());
}
// Increment the deadCounter in old fields that were not merged
oldFields.forEach(f -> f.incrementDeadCounter());
oldFields.removeIf(f -> f.deadCounter >= MAX_DELETE_UNMERGED);
// At this stage, add all the remaining fields still in oldFields
fields.addAll(oldFields);
}
private List<Field> buildNewFields(List<Rect> rects, double thresholdFactor) {
double meanArea = rects.stream().mapToDouble(r -> r.area()).average().getAsDouble();
double sem = Math.sqrt(rects.stream().mapToDouble(r -> Math.pow(r.area() - meanArea, 2)).sum() / (rects.size() - 1));
return rects.stream().filter(r -> (r.area() - meanArea) <= (sem * thresholdFactor)).map(Field::new).collect(Collectors.toList());
}
public void restabilizeFields(Mat homography) {
fields.forEach(field -> field.updateRect(findNewRect(field.getRect(), homography)));
logger.info("Restabilized fields ({})", fields.size());
}
private Rect findNewRect(Rect rect, Mat homography) {
List<Point> points = restabilize(Arrays.asList(rect.tl(), rect.br()), homography);
return new Rect(points.get(0), points.get(1));
}
private List<Point> restabilize(List<Point> originals, Mat homography) {
Mat original = Converters.vector_Point2f_to_Mat(originals);
MatOfPoint2f results = new MatOfPoint2f();
Core.perspectiveTransform(original, results, homography);
List<Point> res = results.toList();
return res;
}
@Override
public void performOcr(Img rootImg) {
long TS = System.currentTimeMillis();
while (System.currentTimeMillis() - TS <= OCR_TIMEOUT) {
runParallelOcr(rootImg);
// runSequentialOcr(rootImg);
}
}
private void runSequentialOcr(Img rootImg) {
int idx = rand.nextInt(size());
fields.get(idx).ocr(rootImg);
}
private void runParallelOcr(Img rootImg) {
ParallelTasks tasks = new ParallelTasks();
Set<Integer> indexes = new HashSet<>();
while (indexes.size() < tasks.getCounter()) {
int idx = rand.nextInt(size());
if (indexes.add(idx))
tasks.add(() -> fields.get(idx).ocr(rootImg));
}
try {
tasks.run();
} catch (InterruptedException e) {
e.printStackTrace();
}
}
}