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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.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 GSRect ocrRect;
protected Map<String, Integer> labels;
protected String consolidated;
protected double confidence;
protected long attempts;
public AbstractField() {
this(new GSRect());
}
public AbstractField(GSRect rect) {
this.rect = rect;
this.ocrRect = rect;
this.labels = new HashMap<>();
this.consolidated = null;
this.attempts = 0;
this.confidence = 0;
}
void updateRect(GSRect rect) {
this.rect = rect;
}
void updateOcrRect(GSRect rect) {
this.ocrRect = rect;
}
public void setConsolidated(String consolidated) {
this.consolidated = consolidated;
}
public String ocr(Img rootImg) {
if (rootImg.getSrc().empty() || rootImg.getSrc().width() <= 3 || rootImg.getSrc().height() <= 3)
return null;
if (ocrRect.isNearEdge(rootImg.width(), rootImg.height(), 10))
return null;
Rect rect = new Rect((int) getOcrRect().getX(), (int) getOcrRect().getY(), (int) getOcrRect().getWidth(), (int) getOcrRect().getHeight());
if (rect.empty() || rect.width <= 3 || rect.height <= 3)
return null;
if (!(0 <= rect.x && 0 <= rect.y && rect.x + rect.width < rootImg.getSrc().cols() && rect.y + rect.height < rootImg.getSrc().rows()))
return null;
Mat roi = new Mat(rootImg.getSrc(), rect);
String ocr = Ocr.doWork(roi, OCR_CONFIDENCE_THRESH);
if (!ocr.isEmpty()) {
labels.merge(ocr, 1, Integer::sum);
attempts++;
}
return ocr;
}
// public void consolidateOcr(boolean force) {
// consolidateOcr(Integer.MAX_VALUE, force);
// }
public void consolidateOcr(boolean force) {
int labelsSize = getLabelsSize();
if (force || labelsSize >= MIN_SIZE_CONSOLIDATION) {
List<String> strings = labels.entrySet().stream().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, int thickness) {
Point[] targets = getRectPointsWithHomography(homography);
drawRect(display, targets, new Scalar(0, 255, 0), thickness);
drawText(display, targets, new Scalar(0, 255, 0), 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, Scalar color, int thickness) {
Point[] points = RectToolsMapper.gsPointToPoint(Arrays.asList(rect.decomposeClockwise())).toArray(new Point[0]);
drawText(display, points, 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}]", "");
// --- //
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 - 12), color, 1);
Imgproc.putText(display.getSrc(), text, new Point(topCenter.x - l, topCenter.y - 14), Core.FONT_HERSHEY_TRIPLEX, 0.45, color, 1);
}
}
public void drawDebugText(Img display, Scalar color, int thickness) {
Point[] points = RectToolsMapper.gsPointToPoint(Arrays.asList(rect.decomposeClockwise())).toArray(new Point[0]);
drawDebugText(display, points, color, thickness);
}
public void drawDebugText(Img display, Point[] targets, Scalar color, int thickness) {
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.putText(display.getSrc(), conf, new Point(topCenter.x - l, topCenter.y - 12), Core.FONT_HERSHEY_TRIPLEX, 0.35, color);
}
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 isConsolidated() {
return consolidated != null;
}
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 GSRect getOcrRect() {
return ocrRect;
}
public double getConfidence() {
return confidence;
}
@Override
public String toString() {
StringBuffer sb = new StringBuffer();
sb.append("AbstractField: ").append("\n").append(" -> rect: ").append(rect).append("\n").append(" -> labels size: ").append(getLabelsSize()).append("\n").append(" -> consolidated: ").append(consolidated).append("\n").append(" -> confidence: ")
.append(confidence).append("\n");
return sb.toString();
}
}