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rdkartono
2025-02-05 15:20:21 +07:00
parent 29884c03ed
commit 30ef123832
11 changed files with 21247 additions and 299 deletions
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285
src/main/java/id/co/gtc/erhacam/Detectors.java
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@@ -14,21 +14,55 @@ import java.util.List;
public class Detectors {
public static CascadeClassifier frontalfaceDetector;
public static CascadeClassifier eyeDetector;
public static CascadeClassifier leftEyeDetector;
public static CascadeClassifier rightEyeDetector;
public static CascadeClassifier leftEarDetector;
public static CascadeClassifier rightEarDetector;
public static CascadeClassifier profilefaceDetector;
private static CascadeClassifier eyeDetector;
private static CascadeClassifier profilefaceDetector;
private static CascadeClassifier palmDetector;
private static CascadeClassifier fistDetector;
public static void LoadAllDetectors(){
LoadFrontalFaceDetector();
LoadProfileFaceDetector();
LoadEyeDetector();
LoadLeftEarDetector();
LoadRightEarDetector();
LoadLeftEyeDetector();
LoadRightEyeDetector();
LoadProfileFaceDetector();
LoadFistDetector();
LoadRightPalmDetector();
}
private static void LoadFistDetector(){
String filename = SomeCodes.ExtractResource("/fist.xml");
if (filename!=null) {
System.out.println("Fist Detector file : " + filename);
if (fistDetector ==null) {
try{
fistDetector = new CascadeClassifier(filename);
Logger.info("FistDetector loaded");
} catch (Exception e){
Logger.error("Exception on loading FistDetector : " + e.getMessage());
}
} else Logger.info("FistDetector already loaded");
} else Logger.error("Unable to extract fist detector file");
}
private static void LoadRightPalmDetector(){
String filename = SomeCodes.ExtractResource("/rpalm.xml");
if (filename!=null) {
System.out.println("Right Palm Detector file : " + filename);
if (palmDetector ==null) {
try{
palmDetector = new CascadeClassifier(filename);
Logger.info("RightPalmDetector loaded");
} catch (Exception e){
Logger.error("Exception on loading RightPalmDetector : " + e.getMessage());
}
} else Logger.info("RightPalmDetector already loaded");
} else Logger.error("Unable to extract right palm detector file");
}
private static void LoadFrontalFaceDetector(){
@@ -64,7 +98,7 @@ public class Detectors {
}
private static void LoadEyeDetector(){
String filename = SomeCodes.ExtractResource("/haarcascade_eye_tree_eyeglasses.xml");
String filename = SomeCodes.ExtractResource("/haarcascade_eye.xml");
if (filename!=null) {
System.out.println("Eye Detector file : " + filename);
if (eyeDetector==null) {
@@ -80,179 +114,106 @@ public class Detectors {
} else Logger.error("Unable to extract eye detector file");
}
private static void LoadLeftEyeDetector(){
String filename = SomeCodes.ExtractResource("/haarcascade_lefteye_2splits.xml");
if (filename!=null) {
System.out.println("Left Eye Detector file : " + filename);
if (leftEyeDetector==null) {
try{
leftEyeDetector = new CascadeClassifier(filename);
Logger.info("LeftEyeDetector loaded");
} catch (Exception e){
Logger.error("Exception on loading LeftEyeDetector : " + e.getMessage());
}
} else Logger.info("LeftEyeDetector already loaded");
} else Logger.error("Unable to extract left eye detector file");
public static boolean HavePalm(UMat graymat){
RectVector palms = Detect(graymat, palmDetector);
return palms!=null && palms.size()>0;
}
private static void LoadRightEyeDetector(){
String filename = SomeCodes.ExtractResource("/haarcascade_righteye_2splits.xml");
if (filename!=null) {
System.out.println("Right Eye Detector file : " + filename);
if (rightEyeDetector==null) {
try{
rightEyeDetector = new CascadeClassifier(filename);
Logger.info("RightEyeDetector loaded");
} catch (Exception e){
Logger.error("Exception on loading RightEyeDetector : " + e.getMessage());
}
} else Logger.info("RightEyeDetector already loaded");
} else Logger.error("Unable to extract right eye detector file");
public static boolean HaveFist(UMat graymat){
RectVector fists = Detect(graymat, fistDetector);
return fists!=null && fists.size()>0;
}
private static void LoadLeftEarDetector(){
String filename = SomeCodes.ExtractResource("/haarcascade_mcs_leftear.xml");
if (filename!=null) {
System.out.println("Left Ear Detector file : " + filename);
if (leftEarDetector==null) {
try{
leftEarDetector = new CascadeClassifier(filename);
Logger.info("LeftEarDetector loaded");
} catch (Exception e){
Logger.error("Exception on loading LeftEarDetector : " + e.getMessage());
}
} else Logger.info("LeftEarDetector already loaded");
} else Logger.error("Unable to extract left ear detector file");
}
private static void LoadRightEarDetector(){
String filename = SomeCodes.ExtractResource("/haarcascade_mcs_rightear.xml");
if (filename!=null) {
System.out.println("Right Ear Detector file : " + filename);
if (rightEarDetector==null) {
try{
rightEarDetector = new CascadeClassifier(filename);
Logger.info("RightEarDetector loaded");
} catch (Exception e){
Logger.error("Exception on loading RightEarDetector : " + e.getMessage());
}
} else Logger.info("RightEarDetector already loaded");
} else Logger.error("Unable to extract right ear detector file");
}
//TODO buat kalkulasi range minSize dan maxSize kalau pakai BestMat (3840x2160) dan LiveMat (1280x720)
/**
* Detect if there is a frontal face, containing 2 eyes
* @param graymat Mat in Gray Scale
* @return List of Rect if face detected, otherwise empty list
*/
public static @NonNull List<Rect> HaveFrontalFace(UMat graymat){
List<Rect> result = new ArrayList<>();
public static @NonNull List<DetectorResult> HaveFrontalFace(UMat graymat){
List<DetectorResult> result = new ArrayList<>();
RectVector faces = DetectFrontalFace(graymat);
if (faces!=null && faces.size()>0){
for(Rect face : faces.get()){
UMat faceMat = new UMat(graymat, face);
RectVector eyes = DetectEye(faceMat);
RectVector eyes = DetectEye(graymat);
DetectorResult dr = new DetectorResult();
dr.setFace(face);
if (eyes!=null && eyes.size()>=2){
result.add(face);
for(Rect eye : eyes.get()){
if (eye.x() < face.x() || eye.y() < face.y() || eye.x() + eye.width() > face.x() + face.width() || eye.y() + eye.height() > face.y() + face.height()){
continue;
}
dr.AddEye(eye);
}
}
result.add(dr);
}
}
return result;
}
public static @NonNull List<Rect> HaveLeft45Face(UMat graymat){
List<Rect> result = new ArrayList<>();
public static @NonNull List<DetectorResult> HaveLeft45Face(UMat graymat){
List<DetectorResult> result = new ArrayList<>();
RectVector faces = DetectProfileFace(graymat);
if (faces!=null && faces.size()>0){
for(Rect face : faces.get()){
UMat faceMat = new UMat(graymat, face);
RectVector eyes = DetectLeftEye(faceMat);
RectVector eyes = DetectEye(graymat);
DetectorResult dr = new DetectorResult();
dr.setFace(face);
if (eyes!=null && eyes.size()>0){
result.add(face);
for(Rect eye : eyes.get()){
if (eye.x() < face.x() || eye.y() < face.y() || eye.x() + eye.width() > face.x() + face.width() || eye.y() + eye.height() > face.y() + face.height()){
continue;
}
dr.AddEye(eye);
}
}
result.add(dr);
}
}
return result;
}
public static @NonNull List<Rect> HaveRight45Face(UMat graymat){
List<Rect> result = new ArrayList<>();
RectVector faces = DetectProfileFace(graymat);
if (faces!=null && faces.size()>0){
for(Rect face : faces.get()){
UMat faceMat = new UMat(graymat, face);
RectVector eyes = DetectRightEye(faceMat);
if (eyes!=null && eyes.size()>0){
result.add(face);
}
}
}
return result;
}
public static @NonNull List<Rect> HaveLeft90Face(UMat graymat){
List<Rect> result = new ArrayList<>();
RectVector leftears = DetectLeftEar(graymat);
RectVector lefteyes = DetectLeftEye(graymat);
if (leftears!=null && leftears.size()>0 && lefteyes!=null && lefteyes.size()>0){
for(Rect ear : leftears.get()){
result.add(ear);
}
}
return result;
}
public static @NonNull List<Rect> HaveRight90Face(UMat graymat){
List<Rect> result = new ArrayList<>();
RectVector rightears = DetectRightEar(graymat);
RectVector righteyes = DetectRightEye(graymat);
if (rightears!=null && rightears.size()>0 && righteyes!=null && righteyes.size()>0){
for(Rect ear : rightears.get()){
result.add(ear);
}
}
return result;
}
private static double scaleFactor = 1.1;
private final static int minNeighbors = 3;
private final static int flags = 0;
private static Size minSize = new Size(200,200);
private static Size maxSize = new Size(400,400);
private static Size FaceminSize = new Size(200,200);
private static Size FacemaxSize = new Size(500,500);
private static final int EyetoFaceRatio = 6;
private static Size EyeminSize = new Size(FaceminSize.width()/EyetoFaceRatio,FaceminSize.height()/EyetoFaceRatio);
private static Size EyemaxSize = new Size(FacemaxSize.width()/EyetoFaceRatio,FacemaxSize.height()/EyetoFaceRatio);
public static void setScaleFactor(double value){
if (scaleFactor!=value) scaleFactor = value;
}
public static void setMinSize(int value){
if (minSize.width()!=value || minSize.height()!=value) minSize = new Size(value, value);
public static void setFaceMinSize(int value){
if (FaceminSize.width()!=value || FaceminSize.height()!=value) {
FaceminSize = new Size(value, value);
EyeminSize = new Size(value/EyetoFaceRatio, value/EyetoFaceRatio);
}
}
public static void setMaxSize(int value){
if (maxSize.width()!=value || maxSize.height()!=value) maxSize = new Size(value, value);
public static void setFaceMaxSize(int value){
if (FacemaxSize.width()!=value || FacemaxSize.height()!=value) {
FacemaxSize = new Size(value, value);
EyemaxSize = new Size(value/EyetoFaceRatio, value/EyetoFaceRatio);
}
}
public static RectVector DetectProfileFace(UMat graymat){
return Detect(graymat, profilefaceDetector, scaleFactor, minNeighbors, flags, minSize, maxSize);
return Detect(graymat, profilefaceDetector, scaleFactor, minNeighbors, flags, FaceminSize, FacemaxSize);
}
@@ -263,10 +224,12 @@ public class Detectors {
* @return RectVector if face detected, otherwise null
*/
public static RectVector DetectFrontalFace(UMat graymat){
return Detect(graymat, frontalfaceDetector, scaleFactor, minNeighbors, flags, minSize, maxSize);
return Detect(graymat, frontalfaceDetector, scaleFactor, minNeighbors, flags, FaceminSize, FacemaxSize);
}
/**
* Detect Eye from Mat
* If Eye detected, it will return RectVector with size is number of eyes detected
@@ -274,49 +237,14 @@ public class Detectors {
* @return RectVector if eye detected, otherwise null
*/
public static RectVector DetectEye(UMat graymat){
//return Detect(graymat, eyeDetector, scaleFactor, minNeighbors, flags, EyeminSize, EyemaxSize);
return Detect(graymat, eyeDetector);
}
/**
* Detect Left Eye from Mat
* @param graymat Mat in Gray Scale
* @return RectVector if left eye detected, otherwise null
*/
public static RectVector DetectLeftEye(UMat graymat){
return Detect(graymat, leftEyeDetector);
}
/**
* Detect Right Eye from Mat
* @param graymat Mat in Gray Scale
* @return RectVector if right eye detected, otherwise null
*/
public static RectVector DetectRightEye(UMat graymat){
return Detect(graymat, rightEyeDetector);
}
/**
* Detect Left Ear from Mat
* @param graymat Mat in Gray Scale
* @return RectVector if left ear detected, otherwise null
*/
public static RectVector DetectLeftEar(UMat graymat){
return Detect(graymat, leftEarDetector);
}
/**
* Detect Right Ear from Mat
* @param graymat Mat in Gray Scale
* @return RectVector if right ear detected, otherwise null
*/
public static RectVector DetectRightEar(UMat graymat){
return Detect(graymat, rightEarDetector);
}
@SuppressWarnings("unused")
private static RectVector Detect(UMat graymat, CascadeClassifier detector){
if (detector!=null){
if (graymat!=null){
@@ -336,9 +264,14 @@ public class Detectors {
if (detector!=null){
if (graymat!=null){
if (!graymat.empty()){
RectVector detected = new RectVector();
detector.detectMultiScale(graymat, detected, scaleFactor, minNeighbors, flags, minSize, maxSize);
return detected;
if (minSize!=null){
if (maxSize!=null){
RectVector detected = new RectVector();
detector.detectMultiScale(graymat, detected, scaleFactor, minNeighbors, flags, minSize, maxSize);
return detected;
}
}
}
}