554 lines
23 KiB
Java
554 lines
23 KiB
Java
|
package it.acxent.face.fr;
|
||
|
|
|
||
|
|
import it.acxent.common.StatusMsg;
|
||
|
|
import it.acxent.db.ApplParmFull;
|
||
|
|
import it.acxent.db.DBAdapter;
|
||
|
|
import it.acxent.db.ResParm;
|
||
|
|
import it.acxent.db.WcString;
|
||
|
|
import it.acxent.face.api.opencv.FaceRecognition;
|
||
|
|
import it.acxent.face.api.opencv.TrainingImage;
|
||
|
|
import it.acxent.util.Timer;
|
||
|
|
import it.acxent.util.Vectumerator;
|
||
|
|
import java.io.File;
|
||
|
|
import java.io.Serializable;
|
||
|
|
import java.sql.PreparedStatement;
|
||
|
|
import java.sql.SQLException;
|
||
|
|
import java.util.ArrayList;
|
||
|
|
import java.util.List;
|
||
|
|
import java.util.concurrent.ConcurrentHashMap;
|
||
|
|
import java.util.concurrent.locks.ReentrantLock;
|
||
|
|
import org.opencv.core.CvType;
|
||
|
|
import org.opencv.core.Mat;
|
||
|
|
import org.opencv.core.MatOfInt;
|
||
|
|
import org.opencv.face.EigenFaceRecognizer;
|
||
|
|
import org.opencv.face.FisherFaceRecognizer;
|
||
|
|
import org.opencv.face.LBPHFaceRecognizer;
|
||
|
|
import org.opencv.imgcodecs.Imgcodecs;
|
||
|
|
import org.opencv.imgproc.Imgproc;
|
||
|
|
|
||
|
|
public class FaceRecognizer extends it.acxent.dm.FaceRecognizer implements Serializable {
|
||
|
|
class ThreadCaricaModelli extends Thread {
|
||
|
|
private FaceRecognizerCR CR;
|
||
|
|
|
||
|
|
private boolean useFile = false;
|
||
|
|
|
||
|
|
public ThreadCaricaModelli(FaceRecognizerCR l_CR, boolean l_usaFile) {
|
||
|
|
this.CR = l_CR;
|
||
|
|
this.useFile = l_usaFile;
|
||
|
|
if (!FaceRecognizer.threadCaricaModelli) {
|
||
|
|
FaceRecognizer.threadCaricaModelli = true;
|
||
|
|
start();
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
public void run() {
|
||
|
|
boolean debug = true;
|
||
|
|
String TAG_THREAD_MSG = " CACHE MODELS ";
|
||
|
|
Timer timerTotal = new Timer();
|
||
|
|
Timer timer = new Timer();
|
||
|
|
if (debug)
|
||
|
|
System.out.println(String.valueOf(DBAdapter.getNow()) + " CACHE MODELS FaceRecognition.getInstance ");
|
||
|
|
FaceRecognition.getInstance(FaceRecognizer.this.getApFull());
|
||
|
|
timerTotal.start();
|
||
|
|
Vectumerator<FaceRecognizer> vec = FaceRecognizer.this.findByCR(this.CR, 0, 0);
|
||
|
|
int i = 0;
|
||
|
|
while (vec.hasMoreElements()) {
|
||
|
|
i++;
|
||
|
|
FaceRecognizer row = (FaceRecognizer)vec.nextElement();
|
||
|
|
if (this.useFile) {
|
||
|
|
if (row.isModelFileExist(0L)) {
|
||
|
|
timer.start();
|
||
|
|
if (debug)
|
||
|
|
System.out.println(String.valueOf(DBAdapter.getNow()) + " CACHE MODELS Recognizer modelli files " + String.valueOf(DBAdapter.getNow()) + " ...." + row.getCodice());
|
||
|
|
StatusMsg.updateMsgByTag(FaceRecognizer.this.getApFull(), " CACHE MODELS ", " Recognizer " + row.getCodice() + " ...." + String.valueOf(timer.getTStart()));
|
||
|
|
row.precaricaModelliFiles();
|
||
|
|
timer.stop();
|
||
|
|
if (debug)
|
||
|
|
System.out.println(String.valueOf(DBAdapter.getNow()) + " CACHE MODELS Recognizer modelli files " + String.valueOf(DBAdapter.getNow()) + " ...." + row.getCodice());
|
||
|
|
continue;
|
||
|
|
}
|
||
|
|
if (debug)
|
||
|
|
System.out.println(String.valueOf(DBAdapter.getNow()) + " CACHE MODELS Recognizer modelli files " + String.valueOf(DBAdapter.getNow()) + " FILE NON TROVATO: " + row.getCodice());
|
||
|
|
continue;
|
||
|
|
}
|
||
|
|
if (row.getFlgDisabilita() == 0L) {
|
||
|
|
timer.start();
|
||
|
|
if (debug)
|
||
|
|
System.out.println(String.valueOf(DBAdapter.getNow()) + " CACHE MODELS Recognizer by training " + String.valueOf(DBAdapter.getNow()) + " ...." + row.getCodice());
|
||
|
|
StatusMsg.updateMsgByTag(FaceRecognizer.this.getApFull(), " CACHE MODELS ", " Recognizer " + row.getCodice() + " ...." + String.valueOf(timer.getTStart()));
|
||
|
|
row.precaricaModelli();
|
||
|
|
timer.stop();
|
||
|
|
if (debug)
|
||
|
|
System.out.println(String.valueOf(DBAdapter.getNow()) + " CACHE MODELS Recognizer by training " + String.valueOf(DBAdapter.getNow()) + " ...." + row.getCodice());
|
||
|
|
}
|
||
|
|
}
|
||
|
|
timerTotal.stop();
|
||
|
|
StatusMsg.updateMsgByTag(FaceRecognizer.this.getApFull(), " CACHE MODELS ", "FINE: " + timerTotal.getDurata());
|
||
|
|
if (debug)
|
||
|
|
System.out.println(String.valueOf(DBAdapter.getNow()) + " CACHE MODELS FINE: " + String.valueOf(DBAdapter.getNow()));
|
||
|
|
DBAdapter.sleepInSecond(4);
|
||
|
|
StatusMsg.deleteMsgByTag(FaceRecognizer.this.getApFull(), " CACHE MODELS ");
|
||
|
|
FaceRecognizer.threadCaricaModelli = false;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
private boolean debug = false;
|
||
|
|
|
||
|
|
private static final long serialVersionUID = 1701089773600L;
|
||
|
|
|
||
|
|
private long id_users;
|
||
|
|
|
||
|
|
private Users users;
|
||
|
|
|
||
|
|
private org.opencv.face.FaceRecognizer ocvFrLBPH;
|
||
|
|
|
||
|
|
private org.opencv.face.FaceRecognizer ocvFrEigen;
|
||
|
|
|
||
|
|
private org.opencv.face.FaceRecognizer ocvFrFish;
|
||
|
|
|
||
|
|
public static boolean threadCaricaModelli = false;
|
||
|
|
|
||
|
|
private long nTrainingImagesMax;
|
||
|
|
|
||
|
|
private long flgTrainingMode;
|
||
|
|
|
||
|
|
private long flgDisabilita;
|
||
|
|
|
||
|
|
private static final ConcurrentHashMap<String, org.opencv.face.FaceRecognizer> recognizerCache = new ConcurrentHashMap<>();
|
||
|
|
|
||
|
|
private static final ReentrantLock trainingLock = new ReentrantLock();
|
||
|
|
|
||
|
|
public static final String TAG_TRAINING_RUN = "TRAINING_RUN";
|
||
|
|
|
||
|
|
public FaceRecognizer(ApplParmFull newApplParmFull) {
|
||
|
|
super(newApplParmFull);
|
||
|
|
}
|
||
|
|
|
||
|
|
public FaceRecognizer() {}
|
||
|
|
|
||
|
|
public static synchronized ResParm addNTrainingImages(FaceRecognizer bean, long newNTrainingImages) {
|
||
|
|
bean.setNTrainingImages(bean.getNTrainingImages() + newNTrainingImages);
|
||
|
|
return bean.save();
|
||
|
|
}
|
||
|
|
|
||
|
|
protected ResParm checkDeleteCascade() {
|
||
|
|
return new ResParm(true);
|
||
|
|
}
|
||
|
|
|
||
|
|
protected void deleteCascade() {}
|
||
|
|
|
||
|
|
public Vectumerator<FaceRecognizer> findByCR(FaceRecognizerCR CR, int pageNumber, int pageRows) {
|
||
|
|
String s_Sql_Find = "select A.* from FACE_RECOGNIZER AS A";
|
||
|
|
String s_Sql_Order = " order by A.descrizione";
|
||
|
|
WcString wc = new WcString();
|
||
|
|
if (CR.getId_faceRecognizer() > 0L)
|
||
|
|
wc.addWc("A.id_faceRecognizer=" + CR.getId_faceRecognizer());
|
||
|
|
try {
|
||
|
|
PreparedStatement stmt = getConn().prepareStatement(s_Sql_Find + s_Sql_Find + wc.toString());
|
||
|
|
return findRows(stmt, pageNumber, pageRows);
|
||
|
|
} catch (SQLException e) {
|
||
|
|
removeCPConnection();
|
||
|
|
handleDebug(e);
|
||
|
|
return AB_EMPTY_VECTUMERATOR;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
public void findByCode(String l_code) {
|
||
|
|
String s_Sql_Find = "select A.* from FACE_RECOGNIZER AS A";
|
||
|
|
String s_Sql_Order = "";
|
||
|
|
WcString wc = new WcString();
|
||
|
|
wc.addWc("A.codice='" + l_code + "'");
|
||
|
|
try {
|
||
|
|
PreparedStatement stmt = getConn().prepareStatement(s_Sql_Find + s_Sql_Find + wc.toString());
|
||
|
|
findFirstRecord(stmt);
|
||
|
|
} catch (SQLException e) {
|
||
|
|
removeCPConnection();
|
||
|
|
handleDebug(e);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
public void findByFaceRecognizer(long l_id_faceRecognizer) {
|
||
|
|
String s_Sql_Find = "select A.* from FACE_FACE_RECOGNIZER AS A";
|
||
|
|
String s_Sql_Order = "";
|
||
|
|
WcString wc = new WcString();
|
||
|
|
wc.addWc("A.id_faceRecognizer=" + l_id_faceRecognizer);
|
||
|
|
try {
|
||
|
|
PreparedStatement stmt = getConn().prepareStatement(s_Sql_Find + s_Sql_Find + wc.toString());
|
||
|
|
findFirstRecord(stmt);
|
||
|
|
} catch (SQLException e) {
|
||
|
|
removeCPConnection();
|
||
|
|
handleDebug(e);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
public boolean isModelFileExist(long recognizerType) {
|
||
|
|
String fullFileName = getFullFileName(recognizerType);
|
||
|
|
return new File(fullFileName).exists();
|
||
|
|
}
|
||
|
|
|
||
|
|
@Deprecated
|
||
|
|
public org.opencv.face.FaceRecognizer getOcvFaceRecognizerWithLoadedModelOriginal(long recognizerType) {
|
||
|
|
String fullFileName = getFullFileName(recognizerType);
|
||
|
|
String cacheKey = "" + recognizerType + ":" + recognizerType;
|
||
|
|
if (recognizerCache.containsKey(cacheKey))
|
||
|
|
return recognizerCache.get(cacheKey);
|
||
|
|
return null;
|
||
|
|
}
|
||
|
|
|
||
|
|
public org.opencv.face.FaceRecognizer getOcvFaceRecognizerWithLoadedModel(long recognizerType) {
|
||
|
|
boolean debug = false;
|
||
|
|
String fullFileName = getFullFileName(recognizerType);
|
||
|
|
String cacheKey = "" + recognizerType + ":" + recognizerType;
|
||
|
|
if (debug)
|
||
|
|
DBAdapter.printDebug(debug, " getOcvFaceRecognizerWithLoadedModel key: " + cacheKey);
|
||
|
|
if (debug) {
|
||
|
|
DBAdapter.printDebug(debug, " getOcvFaceRecognizerWithLoadedModel elenco chiavi presenti!!");
|
||
|
|
for (String key : recognizerCache.keySet())
|
||
|
|
System.out.println("Key: " + key);
|
||
|
|
}
|
||
|
|
if (recognizerCache.containsKey(cacheKey)) {
|
||
|
|
DBAdapter.printDebug(debug, " getOcvFaceRecognizerWithLoadedModel key: " + cacheKey + " TROVATO!!!!");
|
||
|
|
return recognizerCache.get(cacheKey);
|
||
|
|
}
|
||
|
|
trainingLock.lock();
|
||
|
|
try {
|
||
|
|
if (debug)
|
||
|
|
DBAdapter.printDebug(debug, " getOcvFaceRecognizerWithLoadedModel key: " + cacheKey + " DENTRO IL LOCK!");
|
||
|
|
if (recognizerCache.containsKey(cacheKey)) {
|
||
|
|
if (debug)
|
||
|
|
DBAdapter.printDebug(debug, " getOcvFaceRecognizerWithLoadedModel key: " + cacheKey + " TROVATO ALL'INTERNO DEL LOCK!!!!");
|
||
|
|
return recognizerCache.get(cacheKey);
|
||
|
|
}
|
||
|
|
DBAdapter.printDebug(debug, " getOcvFaceRecognizerWithLoadedModel prima di trainingAndCreateModel...");
|
||
|
|
trainingAndCreateModel(false);
|
||
|
|
DBAdapter.printDebug(debug, " getOcvFaceRecognizerWithLoadedModel FATTO!!!");
|
||
|
|
if (recognizerCache.containsKey(cacheKey)) {
|
||
|
|
if (debug)
|
||
|
|
System.out.println(
|
||
|
|
String.valueOf(DBAdapter.getNowTs()) + " getOcvFaceRecognizerWithLoadedModel key: " + String.valueOf(DBAdapter.getNowTs()) + " TROVATO DOPO IL TRAINING");
|
||
|
|
return recognizerCache.get(cacheKey);
|
||
|
|
}
|
||
|
|
if (debug)
|
||
|
|
DBAdapter.printDebug(debug, " getOcvFaceRecognizerWithLoadedModel key: " + cacheKey + " NON TROVATO DOPO IL TRAINING!!!!");
|
||
|
|
throw new IllegalStateException("Impossibile creare il modello per il tipo di recognizer: " + recognizerType);
|
||
|
|
} finally {
|
||
|
|
trainingLock.unlock();
|
||
|
|
if (debug)
|
||
|
|
DBAdapter.printDebug(debug, " getOcvFaceRecognizerWithLoadedModel key: " + cacheKey + " FUORI IL LOCK!");
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
public org.opencv.face.FaceRecognizer getOcvFaceRecognizerWithLoadedModelByFile(long recognizerType) {
|
||
|
|
boolean debug = true;
|
||
|
|
String fullFileName = getFullFileName(recognizerType);
|
||
|
|
String cacheKey = "" + recognizerType + ":" + recognizerType;
|
||
|
|
if (debug)
|
||
|
|
DBAdapter.printDebug(debug, " getOcvFaceRecognizerWithLoadedModelByFile key: " + cacheKey);
|
||
|
|
if (debug) {
|
||
|
|
DBAdapter.printDebug(debug, " getOcvFaceRecognizerWithLoadedModelByFile elenco chiavi presenti!!");
|
||
|
|
for (String key : recognizerCache.keySet())
|
||
|
|
System.out.println("Key: " + key);
|
||
|
|
}
|
||
|
|
if (recognizerCache.containsKey(cacheKey)) {
|
||
|
|
if (debug)
|
||
|
|
DBAdapter.printDebug(debug, " getOcvFaceRecognizerWithLoadedModelByFile key: " + cacheKey + " TROVATO!!!!");
|
||
|
|
return recognizerCache.get(cacheKey);
|
||
|
|
}
|
||
|
|
if (!isModelFileExist(recognizerType)) {
|
||
|
|
if (debug)
|
||
|
|
DBAdapter.printDebug(debug, " getOcvFaceRecognizerWithLoadedModelByFile key: " + cacheKey + " CACHE NON TROVATA E FILE MODELLO NON TROVATO! RITORNO NULL");
|
||
|
|
return null;
|
||
|
|
}
|
||
|
|
trainingLock.lock();
|
||
|
|
try {
|
||
|
|
if (debug)
|
||
|
|
System.out.println(
|
||
|
|
String.valueOf(DBAdapter.getNowTs()) + " getOcvFaceRecognizerWithLoadedModelByFile key: " + String.valueOf(DBAdapter.getNowTs()) + " DENTRO IL LOCK!");
|
||
|
|
if (recognizerCache.containsKey(cacheKey)) {
|
||
|
|
if (debug)
|
||
|
|
DBAdapter.printDebug(debug, " getOcvFaceRecognizerWithLoadedModelByFile key: " + cacheKey + " TROVATO ALL'INTERNO DEL LOCK!!!!");
|
||
|
|
return recognizerCache.get(cacheKey);
|
||
|
|
}
|
||
|
|
if (debug)
|
||
|
|
DBAdapter.printDebug(debug, " getOcvFaceRecognizerWithLoadedModelByFile prima di recognizer.read...");
|
||
|
|
org.opencv.face.FaceRecognizer recognizer = getOcvFaceRecognizerForModel(recognizerType);
|
||
|
|
try {
|
||
|
|
recognizer.read(fullFileName);
|
||
|
|
recognizerCache.put(cacheKey, recognizer);
|
||
|
|
} catch (Exception e) {
|
||
|
|
System.out.println(String.valueOf(DBAdapter.getNowTs()) + " getOcvFaceRecognizerWithLoadedModelByFile prima di recognizer.read ECCEZIONE! " + String.valueOf(DBAdapter.getNowTs()));
|
||
|
|
e.printStackTrace();
|
||
|
|
}
|
||
|
|
if (debug)
|
||
|
|
DBAdapter.printDebug(debug, " getOcvFaceRecognizerWithLoadedModelByFile FATTO!!!");
|
||
|
|
if (recognizerCache.containsKey(cacheKey)) {
|
||
|
|
if (debug)
|
||
|
|
DBAdapter.printDebug(debug, " getOcvFaceRecognizerWithLoadedModelByFile key: " + cacheKey + " TROVATO DOPO IL TRAINING");
|
||
|
|
return recognizerCache.get(cacheKey);
|
||
|
|
}
|
||
|
|
if (debug)
|
||
|
|
DBAdapter.printDebug(debug, " getOcvFaceRecognizerWithLoadedModelByFile key: " + cacheKey + " NON TROVATO DOPO IL TRAINING!!!!");
|
||
|
|
throw new IllegalStateException("Impossibile creare il modello per il tipo di recognizer: " + recognizerType);
|
||
|
|
} finally {
|
||
|
|
trainingLock.unlock();
|
||
|
|
if (debug)
|
||
|
|
System.out.println(
|
||
|
|
String.valueOf(DBAdapter.getNowTs()) + " getOcvFaceRecognizerWithLoadedModelByFile key: " + String.valueOf(DBAdapter.getNowTs()) + " FUORI IL LOCK!");
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
public void removeOcvFaceRecognizerWithLoadedModel(long recognizerType) {
|
||
|
|
String fullFileName = getFullFileName(recognizerType);
|
||
|
|
String cacheKey = "" + recognizerType + ":" + recognizerType;
|
||
|
|
if (recognizerCache.containsKey(cacheKey))
|
||
|
|
recognizerCache.remove(cacheKey);
|
||
|
|
}
|
||
|
|
|
||
|
|
public void removeAllOcvFaceRecognizerWithLoadedModel() {
|
||
|
|
synchronized (recognizerCache) {
|
||
|
|
recognizerCache.clear();
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
public void addOcvFaceRecognizerWithLoadedModel(long recognizerType, org.opencv.face.FaceRecognizer recognizer) {
|
||
|
|
String fullFileName = getFullFileName(recognizerType);
|
||
|
|
String cacheKey = "" + recognizerType + ":" + recognizerType;
|
||
|
|
if (recognizerCache.containsKey(cacheKey))
|
||
|
|
recognizerCache.remove(cacheKey);
|
||
|
|
DBAdapter.printDebug(this.debug, " addOcvFaceRecognizerWithLoadedModel key: " + cacheKey);
|
||
|
|
recognizerCache.put(cacheKey, recognizer);
|
||
|
|
}
|
||
|
|
|
||
|
|
public void precaricaModelliFiles() {
|
||
|
|
for (int i = 0; i < 1; i++)
|
||
|
|
getOcvFaceRecognizerWithLoadedModelByFile((long)i);
|
||
|
|
}
|
||
|
|
|
||
|
|
public void precaricaModelli() {
|
||
|
|
for (int i = 0; i < 1; i++)
|
||
|
|
getOcvFaceRecognizerWithLoadedModel((long)i);
|
||
|
|
}
|
||
|
|
|
||
|
|
private org.opencv.face.FaceRecognizer getOcvFaceRecognizerForModel(long recognizerType) {
|
||
|
|
if (recognizerType == 0L)
|
||
|
|
return (org.opencv.face.FaceRecognizer)LBPHFaceRecognizer.create();
|
||
|
|
if (recognizerType == 2L)
|
||
|
|
return (org.opencv.face.FaceRecognizer)EigenFaceRecognizer.create();
|
||
|
|
if (recognizerType == 1L)
|
||
|
|
return (org.opencv.face.FaceRecognizer)FisherFaceRecognizer.create();
|
||
|
|
return null;
|
||
|
|
}
|
||
|
|
|
||
|
|
public long getId_users() {
|
||
|
|
return this.id_users;
|
||
|
|
}
|
||
|
|
|
||
|
|
public Users getUsers() {
|
||
|
|
this.users = (Users)getSecondaryObject((DBAdapter)this.users, Users.class, getId_users());
|
||
|
|
return this.users;
|
||
|
|
}
|
||
|
|
|
||
|
|
public void setId_users(long newId_users) {
|
||
|
|
this.id_users = newId_users;
|
||
|
|
setUsers(null);
|
||
|
|
}
|
||
|
|
|
||
|
|
public void setUsers(Users newUsers) {
|
||
|
|
this.users = newUsers;
|
||
|
|
}
|
||
|
|
|
||
|
|
public String getFullFileName(long l_tipo) {
|
||
|
|
return getPathRecognizer() + getPathRecognizer() + "_" + getTipo(l_tipo);
|
||
|
|
}
|
||
|
|
|
||
|
|
public String getFullFileNameBin(long l_tipo) {
|
||
|
|
return getPathRecognizer() + getPathRecognizer() + "_" + getTipo(l_tipo) + ".dat";
|
||
|
|
}
|
||
|
|
|
||
|
|
public String getPathRecognizer() {
|
||
|
|
return getParm("path_img_base").getTesto() + "_recognizer/";
|
||
|
|
}
|
||
|
|
|
||
|
|
public ResParm trainingAndCreateModel(boolean saveModel) {
|
||
|
|
ResParm rp = new ResParm();
|
||
|
|
String TAG_THREAD_MSG = "TRAINING_RUN";
|
||
|
|
Timer timer = new Timer();
|
||
|
|
timer.start();
|
||
|
|
try {
|
||
|
|
boolean debug = true;
|
||
|
|
if (debug)
|
||
|
|
System.out.println(String.valueOf(DBAdapter.getNowTs()) + " TRAINING_RUN trainingAndCreateModel FaceRecognition.getInstance ");
|
||
|
|
FaceRecognition.getInstance(getApFull());
|
||
|
|
if (getId_faceRecognizer() == 0L) {
|
||
|
|
if (debug)
|
||
|
|
DBAdapter.printDebug(debug, " TRAINING_RUN trainingAndCreateModel NO getId_faceRecognizer ");
|
||
|
|
rp.setStatus(false);
|
||
|
|
rp.setMsg("Errore! FaceRecognizer nullo !!");
|
||
|
|
} else {
|
||
|
|
StatusMsg.updateMsgByTag(getApFull(), "TRAINING_RUN", "START TRAINING FOR: " + getCodice());
|
||
|
|
if (debug)
|
||
|
|
DBAdapter.printDebug(debug, " TRAINING_RUN START TRAINING FOR: " + getCodice());
|
||
|
|
int NUM_IMMAGINI_MAX = (int)getNTrainingImagesMax();
|
||
|
|
int totFotoElaborate = 0;
|
||
|
|
FaceFaceRecognizer faceFR = new FaceFaceRecognizer(getApFull());
|
||
|
|
long totRecord = faceFR.getTotFaceByFaceRecognizer(getId_faceRecognizer());
|
||
|
|
if (debug)
|
||
|
|
DBAdapter.printDebug(debug, " TRAINING_RUN totrecordfacebyfacerec: " + totRecord);
|
||
|
|
int j = 0;
|
||
|
|
List<TrainingImage> imageFilenames = new ArrayList<>();
|
||
|
|
Vectumerator<FaceFaceRecognizer> vec = faceFR.findByFaceRecognizer(getId_faceRecognizer(), 1, NUM_IMMAGINI_MAX);
|
||
|
|
while (vec.hasMoreElements()) {
|
||
|
|
j++;
|
||
|
|
FaceFaceRecognizer row = (FaceFaceRecognizer)vec.nextElement();
|
||
|
|
imageFilenames.add(new TrainingImage(row.getFace().getFullFileName(), (int)row.getId_faceLabel()));
|
||
|
|
if (j % 10 == 0)
|
||
|
|
StatusMsg.updateMsgByTag(getApFull(), "TRAINING_RUN", "(MAX: " + NUM_IMMAGINI_MAX + ") Preparing images for model: " + j + "/" + totRecord);
|
||
|
|
}
|
||
|
|
totFotoElaborate = j;
|
||
|
|
StatusMsg.updateMsgByTag(getApFull(), "TRAINING_RUN", "Training create for " + totFotoElaborate + "/" + totRecord + " ... FR CODE: " +
|
||
|
|
getCodice() + " .... ");
|
||
|
|
if (debug)
|
||
|
|
DBAdapter.printDebug(debug, " TRAINING_RUN trainingCreate --> trainingcreate");
|
||
|
|
rp = trainingCreate(imageFilenames, totFotoElaborate);
|
||
|
|
File path = new File(getPathRecognizer());
|
||
|
|
if (!path.exists())
|
||
|
|
path.mkdirs();
|
||
|
|
for (int i = 0; i < 1; i++) {
|
||
|
|
if (debug)
|
||
|
|
DBAdapter.printDebug(debug, " TRAINING_RUN trainingAndCreateModel salvo modello: " +
|
||
|
|
getFullFileName((long)i));
|
||
|
|
StatusMsg.updateMsgByTag(getApFull(), "TRAINING_RUN", "Saving " + getFullFileName((long)i) + " " + totFotoElaborate + "/" + totRecord + " ... FR CODE: " +
|
||
|
|
getCodice() + " .... ");
|
||
|
|
if (saveModel) {
|
||
|
|
getOcvFaceRecognizer((long)i).save(getFullFileName((long)i));
|
||
|
|
} else {
|
||
|
|
File theFile = new File(getFullFileName((long)i));
|
||
|
|
if (theFile.exists())
|
||
|
|
theFile.delete();
|
||
|
|
}
|
||
|
|
if (debug)
|
||
|
|
DBAdapter.printDebug(debug, " TRAINING_RUN trainingAndCreateModel metto in CACHE....: " +
|
||
|
|
getFullFileName((long)i));
|
||
|
|
addOcvFaceRecognizerWithLoadedModel((long)i, getOcvFaceRecognizer((long)i));
|
||
|
|
}
|
||
|
|
timer.stop();
|
||
|
|
setTsStart(timer.getTStart());
|
||
|
|
setTsStop(timer.getTStop());
|
||
|
|
setNTrainingImages((long)totFotoElaborate);
|
||
|
|
rp.append(save());
|
||
|
|
}
|
||
|
|
} catch (Exception e) {
|
||
|
|
e.printStackTrace();
|
||
|
|
rp.setStatus(false);
|
||
|
|
rp.setException(e);
|
||
|
|
if (this.debug)
|
||
|
|
DBAdapter.printDebug(this.debug, " TRAINING_RUN trainingAndCreateModel ECCEZIONE!!!! " + e.getMessage());
|
||
|
|
}
|
||
|
|
if (this.debug)
|
||
|
|
System.out.println(
|
||
|
|
String.valueOf(DBAdapter.getNowTs()) + " TRAINING_RUN FINITO MODELLO " + String.valueOf(DBAdapter.getNowTs()) + " DURATA: " + getCodice());
|
||
|
|
StatusMsg.updateMsgByTag(getApFull(), "TRAINING_RUN", "FINITO MODELLO " + getCodice() + " DURATA: " + timer.getDurata());
|
||
|
|
DBAdapter.sleepInSecond(5);
|
||
|
|
StatusMsg.deleteMsgByTag(getApFull(), "TRAINING_RUN");
|
||
|
|
return rp;
|
||
|
|
}
|
||
|
|
|
||
|
|
private ResParm trainingCreate(List<TrainingImage> trainingImages, int counter) {
|
||
|
|
ResParm rp = new ResParm();
|
||
|
|
try {
|
||
|
|
boolean debug = true;
|
||
|
|
int j = 0;
|
||
|
|
if (debug)
|
||
|
|
System.out.println(String.valueOf(DBAdapter.getNow()) + "trainingCreate " + String.valueOf(DBAdapter.getNow()) + " immagini. counterStart: " + trainingImages.size());
|
||
|
|
if (trainingImages.size() > 0) {
|
||
|
|
Mat labels = new Mat(trainingImages.size(), 1, CvType.CV_32SC1);
|
||
|
|
MatOfInt labelsMat = new MatOfInt();
|
||
|
|
List<Mat> trainingImagesMat = new ArrayList<>();
|
||
|
|
if (debug)
|
||
|
|
System.out.println(String.valueOf(DBAdapter.getNow()) + "train: ciclo trainingImages. size: " + String.valueOf(DBAdapter.getNow()));
|
||
|
|
for (TrainingImage trainingImage : trainingImages) {
|
||
|
|
File imageFile = new File(trainingImage.getImageFileName());
|
||
|
|
Mat image = Imgcodecs.imread(imageFile.getAbsolutePath());
|
||
|
|
Mat grayImage = new Mat();
|
||
|
|
Imgproc.cvtColor(image, grayImage, 6);
|
||
|
|
trainingImagesMat.add(grayImage);
|
||
|
|
labels.put(j, 0, new double[] { (double)trainingImage.getLabel() });
|
||
|
|
j++;
|
||
|
|
if (debug)
|
||
|
|
System.out.println(String.valueOf(DBAdapter.getNow()) + " train: " + String.valueOf(DBAdapter.getNow()) + " count...:" + trainingImage.getImageFileName() + "/" + j + " label: " + counter);
|
||
|
|
}
|
||
|
|
labels.convertTo((Mat)labelsMat, CvType.CV_32SC1);
|
||
|
|
for (int i = 0; i < 1; i++) {
|
||
|
|
if (debug)
|
||
|
|
System.out.println(String.valueOf(DBAdapter.getNow()) + " addestramento per modello n.: " + String.valueOf(DBAdapter.getNow()) + " ...");
|
||
|
|
getOcvFaceRecognizer((long)i).train(trainingImagesMat, labels);
|
||
|
|
if (debug)
|
||
|
|
System.out.println(String.valueOf(DBAdapter.getNow()) + " addestramento per modello n.: " + String.valueOf(DBAdapter.getNow()) + " FATTO!");
|
||
|
|
}
|
||
|
|
}
|
||
|
|
} catch (Exception e) {
|
||
|
|
e.printStackTrace();
|
||
|
|
rp.setStatus(false);
|
||
|
|
rp.setException(e);
|
||
|
|
if (this.debug)
|
||
|
|
System.out.println(String.valueOf(DBAdapter.getNow()) + " trainingCreate ECCEZIONE!!!! " + String.valueOf(DBAdapter.getNow()));
|
||
|
|
}
|
||
|
|
return rp;
|
||
|
|
}
|
||
|
|
|
||
|
|
public ResParm resetTraining() {
|
||
|
|
FaceFaceRecognizer ffr = new FaceFaceRecognizer(getApFull());
|
||
|
|
return ffr.resetTrainingByFaceRecognizer(getId_faceRecognizer());
|
||
|
|
}
|
||
|
|
|
||
|
|
private org.opencv.face.FaceRecognizer getOcvFaceRecognizer(long l_type) {
|
||
|
|
if (l_type == 0L) {
|
||
|
|
if (this.ocvFrLBPH == null)
|
||
|
|
this.ocvFrLBPH = (org.opencv.face.FaceRecognizer)LBPHFaceRecognizer.create();
|
||
|
|
return this.ocvFrLBPH;
|
||
|
|
}
|
||
|
|
if (l_type == 2L) {
|
||
|
|
if (this.ocvFrEigen == null)
|
||
|
|
this.ocvFrEigen = (org.opencv.face.FaceRecognizer)EigenFaceRecognizer.create();
|
||
|
|
return this.ocvFrEigen;
|
||
|
|
}
|
||
|
|
if (l_type == 1L) {
|
||
|
|
if (this.ocvFrFish == null)
|
||
|
|
this.ocvFrFish = (org.opencv.face.FaceRecognizer)FisherFaceRecognizer.create();
|
||
|
|
return this.ocvFrFish;
|
||
|
|
}
|
||
|
|
return null;
|
||
|
|
}
|
||
|
|
|
||
|
|
public final ResParm startCaricaModelli(FaceRecognizerCR l_CR, boolean useFile) {
|
||
|
|
if (!threadCaricaModelli) {
|
||
|
|
new ThreadCaricaModelli(l_CR, useFile);
|
||
|
|
return new ResParm(true, "Thread threadCaricaModelli avviato. usefile: " + useFile);
|
||
|
|
}
|
||
|
|
return new ResParm(false, "ATTENZIONE!! Thread in esecuzione!!!");
|
||
|
|
}
|
||
|
|
|
||
|
|
public long getNTrainingImagesMax() {
|
||
|
|
return (this.nTrainingImagesMax <= 0L) ? 10000L : this.nTrainingImagesMax;
|
||
|
|
}
|
||
|
|
|
||
|
|
public void setNTrainingImagesMax(long nTrainingImagesMax) {
|
||
|
|
this.nTrainingImagesMax = nTrainingImagesMax;
|
||
|
|
}
|
||
|
|
|
||
|
|
public long getFlgTrainingMode() {
|
||
|
|
return this.flgTrainingMode;
|
||
|
|
}
|
||
|
|
|
||
|
|
public void setFlgTrainingMode(long flgTrainingMode) {
|
||
|
|
this.flgTrainingMode = flgTrainingMode;
|
||
|
|
}
|
||
|
|
|
||
|
|
public long getFlgDisabilita() {
|
||
|
|
return this.flgDisabilita;
|
||
|
|
}
|
||
|
|
|
||
|
|
public void setFlgDisabilita(long flgDisabilita) {
|
||
|
|
this.flgDisabilita = flgDisabilita;
|
||
|
|
}
|
||
|
|
}
|