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View file @ a2136e1b
GNU LESSER GENERAL PUBLIC LICENSE
Version 2.1, February 1999
Copyright (C) 1991, 1999 Free Software Foundation, Inc.
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Everyone is permitted to copy and distribute verbatim copies
of this license document, but changing it is not allowed.
[This is the first released version of the Lesser GPL. It also counts
as the successor of the GNU Library Public License, version 2, hence
the version number 2.1.]
Preamble
The licenses for most software are designed to take away your freedom to share and change it. By contrast, the GNU General Public Licenses are intended to guarantee your freedom to share and change free software--to make sure the software is free for all its users.
This license, the Lesser General Public License, applies to some specially designated software packages--typically libraries--of the Free Software Foundation and other authors who decide to use it. You can use it too, but we suggest you first think carefully about whether this license or the ordinary General Public License is the better strategy to use in any particular case, based on the explanations below.
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That's all there is to it!
ProyectoAndroid/ChessTrack/src/uy/edu/chesstrack/communication/Client.java deleted 100644 → 0
View file @ 65200ec2
package uy.edu.chesstrack.communication;
import java.io.DataOutputStream;
import java.io.IOException;
import java.net.InetAddress;
import java.net.Socket;
import android.util.Log;
public class Client {
private static final String TAG = "CLIENT";
private static Client _clientInstance;
private Socket _serverSocket;
private int _serverPort;
private String _serverIp;
// private BufferedReader _input;
private DataOutputStream _output;
protected Client() {
}
public static Client getInstance() {
if (_clientInstance == null) {
_clientInstance = new Client();
}
return _clientInstance;
}
public void EstablishConnection(String serverIp, int serverPort) {
Log.i(TAG, "init client-server communication");
this._serverIp = serverIp;
this._serverPort = serverPort;
try {
InetAddress serverAddr = InetAddress.getByName(this._serverIp);
_serverSocket = new Socket(serverAddr, _serverPort);
Log.i(TAG, "Server on " + this._serverIp + ":" + _serverPort);
if (_serverSocket != null) {
// get stream to send data
this._output = new DataOutputStream(
this._serverSocket.getOutputStream());
}
// get stream to receive data
// this._input = new BufferedReader(new
// InputStreamReader(this._serverSocket.getInputStream()));
} catch (IOException e) {
e.printStackTrace();
}
}
public void SendData(String msg) {
if (this._serverSocket != null && this._output != null) {
try {
Log.i(TAG, "sending=" + msg);
this._output.writeBytes(msg);
} catch (IOException e) {
e.printStackTrace();
}
}
}
/*
* public String ReceiveData() { try { String read = _input.readLine();
* Log.i(TAG, "received="+ read); return read; } catch (IOException e) {
* e.printStackTrace(); return null; } }
*/
public void Stop() {
try {
// _input.close();
_output.close();
_serverSocket.close();
} catch (IOException e) {
e.printStackTrace();
}
}
}
ProyectoAndroid/ChessTrack/src/uy/edu/fing/chesstrack/ChessTrackActivity.java
View file @ a2136e1b
......@@ -8,15 +8,10 @@ import org.opencv.android.LoaderCallbackInterface;
import org.opencv.android.OpenCVLoader;
import org.opencv.core.Mat;
import uy.edu.fing.chesstrack.communication.Client;
import uy.edu.fing.chesstrack.modulomodelador.Modelador;
import uy.edu.fing.chesstrack.modulovision.Adquisicion;
import uy.edu.fing.chesstrack.modulovision.Calibracion;
import uy.edu.fing.chesstrack.modulovision.Manager;
import android.app.Activity;
import android.app.AlertDialog;
import android.content.DialogInterface;
import android.media.AudioManager;
import android.media.ToneGenerator;
import android.os.Bundle;
import android.text.Editable;
import android.util.Log;
......@@ -24,50 +19,43 @@ import android.view.Menu;
import android.view.MenuItem;
import android.view.SurfaceView;
import android.view.WindowManager;
import android.widget.Button;
import android.widget.EditText;
public class ChessTrackActivity extends Activity implements
CvCameraViewListener {
CvCameraViewListener {
private static final String TAG = "CHESSTRACK::Activity";
private static final String IPV4_REGEX = "^(\\d{1,3})\\.(\\d{1,3})\\.(\\d{1,3})\\.(\\d{1,3})$";
private static final String PORT_REGEX = "^(\\d{4,5})$";
private static final String welcomeMSG = ""
+ "--------------------------------------------------------------------------\n"
+ " .:: CHESSTRACK ::. seguimiento de una partida de Ajedrez\n"
+ "\n"
+ " Aylen Ricca - Nicolas Furquez\n"
+ "--------------------------------------------------------------------------\n";
private CameraBridgeViewBase mOpenCvCameraView;
// private JavaCameraView mOpenCvCameraView;
// estados
private static final int IDLE = 0;
private static final int CALIBRAR = 1;
private static final int JUGAR = 2;
private Adquisicion adq;
private Calibracion calibrar;
private Button btnCalibrar;
private Client ClientCommunication;
private MenuItem mItemCalibrar;
private MenuItem mItemServer;
// TODO es chancho pero ver luego
private Mat frame;
private boolean isUsed;
private boolean isCalibrada;
private CameraBridgeViewBase _mOpenCvCameraView;
// private JavaCameraView _mOpenCvCameraView;
private Manager _manager;
private MenuItem _mItemCalibrar;
private MenuItem _mItemServer;
private int _estado;
private final BaseLoaderCallback mLoaderCallback = new BaseLoaderCallback(
this) {
@Override
public void onManagerConnected(int status) {
switch (status) {
case LoaderCallbackInterface.SUCCESS: {
Log.i(TAG, "OpenCV loaded successfully");
mOpenCvCameraView.enableView();
_mOpenCvCameraView.enableView();
}
break;
break;
default: {
super.onManagerConnected(status);
}
break;
break;
}
}
};
......@@ -83,22 +71,14 @@ CvCameraViewListener {
public void onCreate(Bundle savedInstanceState) {
Log.i(TAG, "called onCreate");
super.onCreate(savedInstanceState);
getWindow().addFlags(WindowManager.LayoutParams.FLAG_KEEP_SCREEN_ON);
setContentView(R.layout.chess_track_layout);
mOpenCvCameraView = (JavaCameraView) findViewById(R.id.chess_track_layout);
mOpenCvCameraView.setVisibility(SurfaceView.VISIBLE);
mOpenCvCameraView.setCvCameraViewListener(this);
_mOpenCvCameraView = (JavaCameraView) findViewById(R.id.chess_track_layout);
_mOpenCvCameraView.setVisibility(SurfaceView.VISIBLE);
_mOpenCvCameraView.setCvCameraViewListener(this);
Modelador.getInstance();
try {
isUsed = false;
isCalibrada = false;
} catch (Exception e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
// getServerIp();
_manager = Manager.getInstance();
}
public void getServerIp() {
......@@ -113,7 +93,8 @@ CvCameraViewListener {
@Override
public void onClick(DialogInterface dialog, int whichButton) {
Editable value = input.getText();
if (value == null || value.toString().equals("") || !value.toString().matches(IPV4_REGEX)) {
if (value == null || value.toString().equals("")
|| !value.toString().matches(IPV4_REGEX)) {
Log.i(TAG, "INPUT= not valid IP" + value.toString());
getServerIp();
} else {
......@@ -125,13 +106,6 @@ CvCameraViewListener {
}
});
/*
* alert.setNegativeButton("Cancel", new
* DialogInterface.OnClickListener() { public void
* onClick(DialogInterface dialog, int whichButton) { // no server
* communication -- FIXME do not send info to client } });
*/
alert.show();
}
......@@ -157,9 +131,7 @@ CvCameraViewListener {
int port = Integer.parseInt(value.toString());
Log.i(TAG, "PORT=" + port);
// ClientCommunication = Client.getInstance();
// ClientCommunication.EstablishConnection(ip, port);
// ClientCommunication.SendData(welcomeMSG);
_manager.setConnection(ip, port);
}
}
});
......@@ -170,40 +142,19 @@ CvCameraViewListener {
@Override
public boolean onCreateOptionsMenu(Menu menu) {
Log.i(TAG, "called onCreateOptionsMenu");
mItemCalibrar = menu.add("Calibrar..");
mItemServer = menu.add("Conectar Server");
_mItemCalibrar = menu.add("Calibrar..");
_mItemServer = menu.add("Conectar Server");
return true;
}
@Override
public boolean onOptionsItemSelected(MenuItem item) {
Log.i(TAG, "Menu Item selected " + item);
if (item == mItemCalibrar) {
isUsed = true;
if (frame != null) {
if (Calibracion.getInstance().calibrar(frame)) {
ToneGenerator toneG = new ToneGenerator(
AudioManager.STREAM_ALARM, 50);
toneG.startTone(ToneGenerator.TONE_CDMA_ALERT_CALL_GUARD,
200); // 200 is duration in ms
try {
adq = new Adquisicion();
} catch (Exception e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
isCalibrada = true;
} else {
ToneGenerator toneG = new ToneGenerator(
AudioManager.STREAM_ALARM, 50);
toneG.startTone(ToneGenerator.TONE_CDMA_ALERT_CALL_GUARD,
700); // 200 is duration in ms
}
if (item == _mItemCalibrar) {
if (_estado == IDLE) {
_estado = CALIBRAR;
}
isUsed = false;
}else if(item == mItemServer){
} else if (item == _mItemServer) {
getServerIp();
}
return true;
......@@ -212,19 +163,19 @@ CvCameraViewListener {
@Override
public void onPause() {
super.onPause();
if (mOpenCvCameraView != null) {
mOpenCvCameraView.disableView();
if (_mOpenCvCameraView != null) {
_mOpenCvCameraView.disableView();
}
}
@Override
public void onDestroy() {
super.onDestroy();
if (mOpenCvCameraView != null) {
mOpenCvCameraView.disableView();
if (_mOpenCvCameraView != null) {
_mOpenCvCameraView.disableView();
}
if (this.ClientCommunication != null) {
this.ClientCommunication.Stop();
if (_manager != null) {
_manager.destroy();
}
}
......@@ -238,22 +189,24 @@ CvCameraViewListener {
@Override
public Mat onCameraFrame(Mat inputFrame) {
// TODO MANEJAR ESTADOS
if (!isUsed) {
frame = inputFrame;
}
if (isCalibrada) {
Log.i(TAG, "calibrada");
inputFrame = adq.processFrame(inputFrame);
Modelador.getInstance().dividirTablero(inputFrame);
return Modelador.getInstance().dibujarEscaquesSobel();
// return inputFrame;
if (inputFrame != null) {
switch (_estado) {
case CALIBRAR:
Log.i(TAG, "calibrando...");
if (_manager.calibrar(inputFrame)) {
_estado = JUGAR;
} else {
_estado = IDLE;
}
break;
case JUGAR:
Log.i(TAG, "jugando...");
_manager.processFrame(inputFrame);
break;
case IDLE:
break;
}
}
return inputFrame;
}
}
ProyectoAndroid/ChessTrack/src/uy/edu/fing/chesstrack/ajedrez/Logica.java 0 → 100644
View file @ a2136e1b
package uy.edu.fing.chesstrack.ajedrez;
import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.core.Size;
public class Logica {
private static final String TAG = "CHESSTRACK::Logica";
private Mat _tableroInicio;
private Mat _tableroAnterior;
public Logica() {
double[] vectorONES = { 1, 1, 1, 1, 1, 1, 1, 1 };
_tableroInicio = Mat.zeros(new Size(8, 8), CvType.CV_8UC1);
_tableroInicio.put(0, 0, vectorONES);
_tableroInicio.put(1, 0, vectorONES);
_tableroInicio.put(6, 0, vectorONES);
_tableroInicio.put(7, 0, vectorONES);
_tableroAnterior = _tableroInicio;
}
public Mat getTableroInicio() {
return _tableroInicio;
}
public boolean validarNuevoTablero(Mat actual) {
Mat result = new Mat(8, 8, CvType.CV_8UC1);
Core.absdiff(actual, _tableroAnterior, result);
if (Core.countNonZero(result) != 0) {
_tableroAnterior = actual;
}
return (Core.countNonZero(result) != 0);
}
public boolean validarTableroArmado(Mat nuevo) {
Mat result = new Mat(8, 8, CvType.CV_8UC1);
Core.absdiff(nuevo, _tableroInicio, result);
return (Core.countNonZero(result) == 0);
}
}
ProyectoAndroid/ChessTrack/src/uy/edu/fing/chesstrack/communication/Client.java
View file @ a2136e1b
......@@ -13,18 +13,18 @@ public class Client {
private static Client _clientInstance;
private Socket serverSocket;
private int _serverPort;
private String _serverIp;
private int _serverPort = 5556;
private String _serverIp = "192.168.1.23";
//private BufferedReader input;
// private BufferedReader input;
private DataOutputStream output;
protected Client(){
protected Client() {
}
public static Client getInstance(){
if(_clientInstance == null){
public static Client getInstance() {
if (_clientInstance == null) {
_clientInstance = new Client();
}
return _clientInstance;
......@@ -32,8 +32,8 @@ public class Client {
public void EstablishConnection(String serverIp, int serverPort) {
Log.i(TAG, "init client-server communication");
this._serverIp = serverIp;
this._serverPort = serverPort;
this._serverIp = serverIp;
this._serverPort = serverPort;
try {
Log.i(TAG, "Server on " + this._serverIp + ":" + _serverPort);
......@@ -41,10 +41,12 @@ public class Client {
serverSocket = new Socket(serverAddr, _serverPort);
// get stream to send data
this.output = new DataOutputStream(this.serverSocket.getOutputStream());
this.output = new DataOutputStream(
this.serverSocket.getOutputStream());
// get stream to receive data
//this.input = new BufferedReader(new InputStreamReader(this.serverSocket.getInputStream()));
// this.input = new BufferedReader(new
// InputStreamReader(this.serverSocket.getInputStream()));
} catch (IOException e) {
e.printStackTrace();
}
......@@ -52,7 +54,7 @@ public class Client {
public void SendData(String msg) {
try {
Log.i(TAG, "sending="+ msg);
Log.i(TAG, "sending=" + msg);
this.output.writeBytes(msg);
} catch (IOException e) {
e.printStackTrace();
......@@ -60,21 +62,14 @@ public class Client {
}
/*
public String ReceiveData() {
try {
String read = input.readLine();
Log.i(TAG, "received="+ read);
return read;
} catch (IOException e) {
e.printStackTrace();
return null;
}
}
*/
* public String ReceiveData() { try { String read = input.readLine();
* Log.i(TAG, "received="+ read); return read; } catch (IOException e) {
* e.printStackTrace(); return null; } }
*/
public void Stop() {
try {
//input.close();
// input.close();
output.close();
serverSocket.close();
} catch (IOException e) {
......
ProyectoAndroid/ChessTrack/src/uy/edu/fing/chesstrack/modulomodelador/Modelador.java
View file @ a2136e1b
......@@ -6,6 +6,7 @@ import org.opencv.core.Mat;
import org.opencv.core.Point;
import org.opencv.core.Rect;
import org.opencv.core.Scalar;
import org.opencv.core.Size;
import org.opencv.imgproc.Imgproc;
import uy.edu.fing.chesstrack.modulovision.Calibracion;
......@@ -13,122 +14,196 @@ import android.util.Log;
public class Modelador {
private static final String TAG = "CHESSTRACK::Modelador";
private final int CANT_FILAS= 8;
private final int CANT_SCAQUE = CANT_FILAS* CANT_FILAS;
private final int[][] tablero;
private final int CANT_FILAS = 8;
// private final int CANT_SCAQUE = CANT_FILAS * CANT_FILAS;
private final int MIN_CANT_PIX_WHITE = 30;
private Mat tablero;
// se cuentan de arrib a abajo y de izquierda a derecha
private final Mat[][] escaques;
private static Modelador instance;
// private static Modelador instance;
private Modelador(){
tablero = new int[CANT_FILAS][CANT_FILAS];
public Modelador() {
tablero = Mat.zeros(new Size(8, 8), CvType.CV_8UC1);
escaques = new Mat[CANT_FILAS][CANT_FILAS];
//TODO init tablero
}
public static Modelador getInstance(){
if (instance == null){
instance = new Modelador();
public void dividirTablero(Mat inputFrame) {
Imgproc.cvtColor(inputFrame, inputFrame, Imgproc.COLOR_RGBA2GRAY, 4);
int largo = inputFrame.rows();
int ancho = inputFrame.cols();
// obtengo cuanto mide en ancho y largo un escaque
int largoEscaque = (int) Math.floor(largo / (CANT_FILAS + 2));// +2
// porque
// se
// toma
// un
// escaque
// mas
// de
// borde
int anchoEscaque = (int) Math.floor(ancho / (CANT_FILAS + 2));
Log.i(TAG, "largoEscaque= " + largoEscaque);
Log.i(TAG, "anchoEscaque= " + anchoEscaque);
for (int i = 0; i < CANT_FILAS; i++) {
for (int j = 0; j < CANT_FILAS; j++) {
int rowStart = (int) Math.floor(largoEscaque) + i
* largoEscaque + 4;
int rowEnd = (int) Math.floor(largoEscaque) + i * largoEscaque
+ largoEscaque - 4;
int colStart = (int) Math.floor(anchoEscaque) + j
* anchoEscaque + 4;
int colEnd = (int) Math.floor(anchoEscaque) + j * anchoEscaque
+ anchoEscaque - 4;
escaques[i][j] = inputFrame.submat(colStart, colEnd, rowStart,
rowEnd);
}
}
return instance;
}
public void dividirTablero(Mat inputFrame){
private int getHayFichaEnEscaque(int i, int j) {
int ret = 0;
Mat mIntermediateMat = new Mat();
Imgproc.Sobel(escaques[i][j], mIntermediateMat, CvType.CV_8U, 1, 1);
Core.convertScaleAbs(mIntermediateMat, mIntermediateMat, 10, 0);
Imgproc.threshold(mIntermediateMat, mIntermediateMat, 70, 255,
Imgproc.THRESH_BINARY);
// int cant_pix = mIntermediateMat.cols() * mIntermediateMat.rows();
int cant_pix_white = Core.countNonZero(mIntermediateMat);
if (cant_pix_white > (MIN_CANT_PIX_WHITE)) {
ret = 1;
}
return ret;
}
Rect roi = Calibracion.getInstance().getRectPOI();
Mat proccesFrame = inputFrame.submat(roi);
int largo = proccesFrame.rows();
int ancho = proccesFrame.cols();
// obtengo cuanto mide en ancho y largo un escaque
int largoEscaque = (int) Math.floor(largo /(CANT_FILAS+2) );//+1 porque se toma un escaque mas de borde
int anchoEscaque = (int) Math.floor(ancho /(CANT_FILAS+2) );
Log.i(TAG, "largoEscaque= " + largoEscaque);
Log.i(TAG, "anchoEscaque= " + anchoEscaque);
for (int i = 0; i < CANT_FILAS; i++){
for (int j = 0; j < CANT_FILAS; j++){
int rowStart=(int)Math.floor(largoEscaque)+ i*largoEscaque;
int rowEnd = (int)Math.floor(largoEscaque)+i*largoEscaque + largoEscaque;
int colStart = (int)Math.floor(anchoEscaque)+j*anchoEscaque;
int colEnd = (int)Math.floor(anchoEscaque)+j*anchoEscaque + anchoEscaque;
escaques[i][j]= inputFrame.submat(colStart, colEnd,rowStart, rowEnd);
public Mat getMatrizFichas(Mat frame) {
dividirTablero(frame);
tablero = Mat.zeros(new Size(8, 8), CvType.CV_8UC1);
for (int i = 0; i < CANT_FILAS; i++) {
for (int j = 0; j < CANT_FILAS; j++) {
tablero.put(i, j, getHayFichaEnEscaque(i, j));
}
}
return tablero.t();
}
public Mat dibujarEscaque(){
Mat tmp = Mat.ones(Calibracion.getInstance().getImagenCalibrada().size(), CvType.CV_8UC4);
Mat subm ; //tmp.submat(new Rect(new Point(0,0) ,escaques[i][j].size()));
//escaques[i][j].copyTo(subm);
public Mat dibujarEscaque() {
Mat tmp = Mat.ones(Calibracion.getInstance().get_sizeFrame(),
CvType.CV_8UC4);
Mat subm; // tmp.submat(new Rect(new Point(0,0)
// ,escaques[i][j].size()));
// escaques[i][j].copyTo(subm);
int pos_x = 0;
int pos_y = 0;
for (int i = 0; i < CANT_FILAS; i++){
for (int j = 0; j < CANT_FILAS; j++){
pos_x = (int) (escaques[i][j].size().width*i);
pos_y = (int) (escaques[i][j].size().height*j);
subm = tmp.submat(new Rect(new Point(pos_x,pos_y) ,escaques[i][j].size()));
for (int i = 0; i < CANT_FILAS; i++) {
for (int j = 0; j < CANT_FILAS; j++) {
pos_x = (int) (escaques[i][j].size().width * i);
pos_y = (int) (escaques[i][j].size().height * j);
subm = tmp.submat(new Rect(new Point(pos_x, pos_y),
escaques[i][j].size()));
escaques[i][j].copyTo(subm);
Core.putText(tmp, Integer.toString(i)+ "-" +Integer.toString(j), new Point(pos_x+1, pos_y+1),Core.FONT_HERSHEY_SIMPLEX, 0.3 , new Scalar(255,0,0));
Core.putText(tmp,
Integer.toString(i) + "-" + Integer.toString(j),
new Point(pos_x + 1, pos_y + 1),
Core.FONT_HERSHEY_SIMPLEX, 0.3, new Scalar(255, 0, 0));
}
}
return tmp;
}
public Mat dibujarEscaquesCanny(){
Mat tmp = Mat.zeros(Calibracion.getInstance().getImagenCalibrada().size(), CvType.CV_8UC4);
Mat subm ; //tmp.submat(new Rect(new Point(0,0) ,escaques[i][j].size()));
//escaques[i][j].copyTo(subm);
public Mat dibujarEscaquesCanny() {
Mat tmp = Mat.zeros(Calibracion.getInstance().get_sizeFrame(),
CvType.CV_8UC4);
Mat subm; // tmp.submat(new Rect(new Point(0,0)
// ,escaques[i][j].size()));
// escaques[i][j].copyTo(subm);
Mat mIntermediateMat = new Mat();
int pos_x = 0;
int pos_y = 0;
for (int i = 0; i < CANT_FILAS; i++){
for (int j = 0; j < CANT_FILAS; j++){
pos_x = (int) (escaques[i][j].size().width*i);
pos_y = (int) (escaques[i][j].size().height*j);
subm = tmp.submat(new Rect(new Point(pos_x,pos_y) ,escaques[i][j].size()));
for (int i = 0; i < CANT_FILAS; i++) {
for (int j = 0; j < CANT_FILAS; j++) {
pos_x = (int) (escaques[i][j].size().width * i);
pos_y = (int) (escaques[i][j].size().height * j);
subm = tmp.submat(new Rect(new Point(pos_x, pos_y),
escaques[i][j].size()));
Imgproc.Canny(escaques[i][j], mIntermediateMat, 80, 90);
Imgproc.cvtColor(mIntermediateMat, subm, Imgproc.COLOR_GRAY2RGBA,4);
Imgproc.cvtColor(mIntermediateMat, subm,
Imgproc.COLOR_GRAY2RGBA, 4);
// escaques[i][j].copyTo(subm);
// Core.putText(tmp, Integer.toString(i)+ "-" +Integer.toString(j), new Point(pos_x+1, pos_y+1),Core.FONT_HERSHEY_SIMPLEX, 0.3 , new Scalar(255,0,0));
escaques[i][j].copyTo(subm);
Core.putText(tmp,
Integer.toString(i) + "-" + Integer.toString(j),
new Point(pos_x + 1, pos_y + 1),
Core.FONT_HERSHEY_SIMPLEX, 0.3, new Scalar(255, 0, 0));
}
}
return tmp;
}
public Mat dibujarEscaquesSobel(){
Mat tmp = Mat.zeros(Calibracion.getInstance().getImagenCalibrada().size(), CvType.CV_8UC4);
Mat subm ; //tmp.submat(new Rect(new Point(0,0) ,escaques[i][j].size()));
//escaques[i][j].copyTo(subm);
public Mat dibujarEscaquesSobel(int version) {
Mat tmp = Mat.zeros(Calibracion.getRectROI().size(), CvType.CV_8UC4);
Mat subm; // tmp.submat(new Rect(new Point(0,0)
// ,escaques[i][j].size()));
// escaques[i][j].copyTo(subm);
Mat mIntermediateMat = new Mat();
int pos_x = 0;
int pos_y = 0;
for (int i = 0; i < CANT_FILAS; i++){
for (int j = 0; j < CANT_FILAS; j++){
pos_x = (int) (escaques[i][j].size().width*i);
pos_y = (int) (escaques[i][j].size().height*j);
subm = tmp.submat(new Rect(new Point(pos_x,pos_y) ,escaques[i][j].size()));
Imgproc.cvtColor(escaques[i][j] ,mIntermediateMat, Imgproc.COLOR_RGBA2GRAY,4);
Imgproc.Sobel(mIntermediateMat, mIntermediateMat, CvType.CV_8U, 1, 1);
Log.i(TAG, "cant_pix_INI");
for (int i = 0; i < CANT_FILAS; i++) {
for (int j = 0; j < CANT_FILAS; j++) {
pos_x = (int) (escaques[i][j].size().width * i);
pos_y = (int) (escaques[i][j].size().height * j);
subm = tmp.submat(new Rect(new Point(pos_x, pos_y),
escaques[i][j].size()));
// Imgproc.cvtColor(escaques[i][j] ,mIntermediateMat,
// Imgproc.COLOR_RGBA2GRAY,4);
Imgproc.Sobel(escaques[i][j], mIntermediateMat, CvType.CV_8U,
1, 1);
Core.convertScaleAbs(mIntermediateMat, mIntermediateMat, 10, 0);
Imgproc.threshold(mIntermediateMat, mIntermediateMat, 70, 255, Imgproc.THRESH_BINARY);
int cant_pix = mIntermediateMat.cols()*mIntermediateMat.rows();
Imgproc.threshold(mIntermediateMat, mIntermediateMat, 70, 255,
Imgproc.THRESH_BINARY);
Imgproc.erode(mIntermediateMat, mIntermediateMat, Imgproc
.getStructuringElement(Imgproc.MORPH_RECT, new Size(1,
1)));
Imgproc.dilate(mIntermediateMat, mIntermediateMat, Imgproc
.getStructuringElement(Imgproc.MORPH_RECT, new Size(1,
1)));
int cant_pix = mIntermediateMat.cols()
* mIntermediateMat.rows();
int cant_pix_white = Core.countNonZero(mIntermediateMat);
Log.i(TAG, "cant_pix=" + cant_pix);
Log.i(TAG, "cant_pix_white=" + cant_pix_white);
switch (version) {
case 1:
if (cant_pix_white > (MIN_CANT_PIX_WHITE)) {
Imgproc.cvtColor(mIntermediateMat, subm,
Imgproc.COLOR_GRAY2RGBA, 4);
} else {
Imgproc.cvtColor(escaques[i][j], subm,
Imgproc.COLOR_GRAY2RGBA, 4);
}
break;
case 2:
if (cant_pix_white > (MIN_CANT_PIX_WHITE)) {
Log.i(TAG, "NUEVA FICHA" + (i + 1) + "-" + (j + 1));
}
Imgproc.cvtColor(mIntermediateMat, subm,
Imgproc.COLOR_GRAY2RGBA, 4);
break;
default:
Imgproc.cvtColor(escaques[i][j], subm,
Imgproc.COLOR_GRAY2RGBA, 4);
break;
if (cant_pix_white > (50) ){
Imgproc.cvtColor(mIntermediateMat, subm, Imgproc.COLOR_GRAY2RGBA,4);
}else{
escaques[i][j].copyTo(subm);
}
}
}
Log.i(TAG, "cant_pix_FIN");
return tmp;
}
}
ProyectoAndroid/ChessTrack/src/uy/edu/fing/chesstrack/modulovision/Adquisicion.java
View file @ a2136e1b
package uy.edu.fing.chesstrack.modulovision;
import java.util.ArrayList;
import java.util.List;
import org.opencv.core.Mat;
import uy.edu.fing.chesstrack.modulovision.imgproc.BackgroundSupress;
import uy.edu.fing.chesstrack.modulovision.imgproc.EcualizarImagen;
import uy.edu.fing.chesstrack.modulovision.imgproc.Homografia;
import uy.edu.fing.chesstrack.modulovision.imgproc.ImgProcInterface;
import android.util.Log;
public class Adquisicion {
private static final String TAG = "CHESSTRACK::Adquisicion";
......@@ -27,7 +21,6 @@ public class Adquisicion {
_listProc.add(new Homografia());
//_listProc.add(new EcualizarImagen());
_listProc.add(new BackgroundSupress());
}
/**
......
ProyectoAndroid/ChessTrack/src/uy/edu/fing/chesstrack/modulovision/Calibracion.java
View file @ a2136e1b
......@@ -8,76 +8,64 @@ import org.opencv.core.Size;
import android.util.Log;
public class Calibracion {
private Mat imagenCalibrada;
private Mat imagenOriginal;
private MatOfPoint2f vertices;
public class Calibracion {
private static final String TAG = "CHESSTRACK::Calibracion";
private static Rect rectPOI = null;
private static Calibracion instance;
private Size _sizeFrame = null;
private MatOfPoint2f _vertices = null;
private static Rect _rectROI = null;
private static Calibracion _instance;
protected Calibracion(){
protected Calibracion() {
}
public static Calibracion getInstance(){
if(instance == null){
instance = new Calibracion();
public static Calibracion getInstance() {
if (_instance == null) {
_instance = new Calibracion();
}
return instance;
return _instance;
}
public boolean calibrar(Mat img){
public boolean calibrar(Mat img) {
Log.i(TAG, "INI calibrando");
boolean OK = false;
imagenOriginal = img;
imagenCalibrada = img;
Size patternSize = new Size(7,7);
Size patternSize = new Size(7, 7);
MatOfPoint2f corners = new MatOfPoint2f();
boolean ret = Calib3d.findChessboardCorners(imagenOriginal, patternSize, corners);
if (ret){
boolean ret = Calib3d.findChessboardCorners(img, patternSize, corners);
if (ret) {
Log.i(TAG, "Encontro = " + corners.total());
Log.i(TAG, "Encontro = " + corners.size().toString());
Calib3d.drawChessboardCorners(imagenCalibrada, patternSize, corners, ret);
vertices = corners;
// Calib3d.drawChessboardCorners(img, patternSize, corners, ret);
// only for debug
_vertices = corners;
_sizeFrame = img.size();
}
OK = ret;
Log.i(TAG, "FIN calibrando = " + ret);
return OK;
return ret;
}
public Mat getImagenCalibrada() {
return imagenCalibrada;
public Size get_sizeFrame() {
return _sizeFrame;
}
public void setImagenCalibrada(Mat imagenCalibrada) {
this.imagenCalibrada = imagenCalibrada;
public void set_sizeFrame(Size _sizeFrame) {
this._sizeFrame = _sizeFrame;
}
public MatOfPoint2f getVertices() {
return vertices;
return _vertices;
}
public void setVertices(MatOfPoint2f vertices) {
this.vertices = vertices;
this._vertices = vertices;
}
public static Rect getRectPOI() {
return rectPOI;
public static Rect getRectROI() {
return _rectROI;
}
public static void setRectPOI(Rect rectPOI) {
Calibracion.rectPOI = rectPOI;
public static void setRectROI(Rect rectROI) {
Calibracion._rectROI = rectROI;
}
}
ProyectoAndroid/ChessTrack/src/uy/edu/fing/chesstrack/modulovision/DetectorOclusion.java 0 → 100644
View file @ a2136e1b
package uy.edu.fing.chesstrack.modulovision;
import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.core.Scalar;
import org.opencv.core.Size;
import org.opencv.imgproc.Imgproc;
import org.opencv.video.BackgroundSubtractorMOG2;
import android.util.Log;
public class DetectorOclusion {
private static final String TAG = "CHESSTRACK::BackgroundSupress";
private static final int OCLUSION = 0;
private static final int ESTABLE = 1;
private static final int TRANSICION = 2;
private static final int ENVIAR_TABLERO = 3;
private static final int START = -1;
private final Mat _fgMaskMOG2;
private Mat _resultado;
private BackgroundSubtractorMOG2 _pMOG2;
private final Mat _morphKernel;
private int _estadoANTERIOR;
private int _estadoACTUAL;
public DetectorOclusion() {
super();
Log.i(TAG, "constructor INI");
_morphKernel = Imgproc.getStructuringElement(Imgproc.MORPH_RECT,
new Size(3, 3));
_fgMaskMOG2 = new Mat(4, 1, CvType.CV_8UC1);
_pMOG2 = new BackgroundSubtractorMOG2();
_estadoACTUAL = START;
_resultado = new Mat();
Log.i(TAG, "constructor FIN");
}
public Mat get_resultado() {
return _resultado;
}
public void set_resultado(Mat _resultado) {
this._resultado = _resultado;
}
public boolean hayNuevoTableroValido(Mat inputFrame) {
/*
* if (_estadoACTUAL == START){ _pMOG2 = new BackgroundSubtractorMOG2();
* // MOG2 approach }
*/
Log.i(TAG, "Procesar!");
Log.i(TAG, "Region SIZE=" + inputFrame.size());
_pMOG2.apply(inputFrame, _fgMaskMOG2);
Imgproc.erode(_fgMaskMOG2, _fgMaskMOG2, _morphKernel);
Log.i(TAG, "Apply erode");
Imgproc.threshold(_fgMaskMOG2, _fgMaskMOG2, 200, 255,
Imgproc.THRESH_BINARY);
Log.i(TAG, "Apply threshold");
// Imgproc.dilate(_fgMaskMOG2, _fgMaskMOG2, _morphKernel);
// Log.i(TAG, "Apply dilate");
Scalar suma = Core.sumElems(_fgMaskMOG2);
Log.i(TAG, "SUMA = " + suma);
_estadoANTERIOR = _estadoACTUAL;
if (suma.val[0] > 1250000) {
Log.i(TAG, "VEO MANO !!!");
_estadoACTUAL = OCLUSION;
/*
* Core.putText(_fgMaskMOG2, "MANO !!!", new Point(20, 20),
* Core.FONT_HERSHEY_SIMPLEX, 0.8, new Scalar(255, 255, 0));
*/
} else {
if (_estadoANTERIOR == OCLUSION) {
/*
* Core.putText(_fgMaskMOG2, "TRANSI !!!", new Point(20, 20),
* Core.FONT_HERSHEY_SIMPLEX, 0.8, new Scalar(255, 255, 0));
*/
Log.i(TAG, "VEO TRANSICION !!!");
_estadoACTUAL = TRANSICION;
}
if (_estadoANTERIOR == TRANSICION) {
/*
* Core.putText(_fgMaskMOG2, "ESTABLE !!!", new Point(20, 20),
* Core.FONT_HERSHEY_SIMPLEX, 0.8, new Scalar(255, 255, 0));
*/
_estadoACTUAL = ENVIAR_TABLERO;
_pMOG2 = new BackgroundSubtractorMOG2(); // MOG2 approach
Log.i(TAG, "VEO ENVIAR !!!");
}
if (_estadoANTERIOR == ENVIAR_TABLERO) {
_estadoACTUAL = ESTABLE;
Log.i(TAG, "VEO ESTABLE !!!");
}
}
Log.i(TAG, "END");
Imgproc.cvtColor(_fgMaskMOG2, _resultado, Imgproc.COLOR_GRAY2RGBA, 4);
return (_estadoACTUAL == ENVIAR_TABLERO);
}
}
/*
* double maxArea = 0; MatOfPoint largestContour = null;
* Imgproc.findContours(_fgMaskMOG2, contours, new Mat(), Imgproc.RETR_LIST,
* Imgproc.CHAIN_APPROX_TC89_L1); for (MatOfPoint contour : contours) { double
* area = Imgproc.contourArea(contour); if (area > maxArea) { maxArea = area;
* largestContour = contour; } } Log.i(TAG, "ESTABLE !!!" + maxArea); if
* ((largestContour != null) && (maxArea > 10000)){ Log.i(TAG, "MANO !!!" +
* maxArea); Rect boundingRect = Imgproc.boundingRect(largestContour);
* ToneGenerator toneG = new ToneGenerator(AudioManager.STREAM_ALARM, 50);
* toneG.startTone(ToneGenerator.TONE_CDMA_ALERT_CALL_GUARD, 200); // 200 is
* duration in ms }
*/
/*
* Imgproc.findContours(_fgMaskMOG2, contours, new Mat(), Imgproc.RETR_LIST,
* Imgproc.CHAIN_APPROX_NONE);
*
* for(int idx = 0; idx < contours.size(); idx++) { double area =
* Imgproc.contourArea(contours.get(idx)); Log.i(TAG, "CONTOUR = AREA: " +
* area); if ((area > 15000) && (area < 70000)){ Log.i(TAG, "DRAW !!! : " +
* area); Scalar color = new Scalar(255,127,127); Rect r =
* Imgproc.boundingRect(contours.get(idx)); Log.i(TAG,
* "3 at backgroundS "+(_fgMaskMOG2.type() == CvType.CV_8UC1));
* Core.rectangle(_fgMaskMOG2, r.tl(), r.br(), color, 2, 8, 0);
* //Imgproc.drawContours(_fgMaskMOG2, contours, idx, color); } }
*
* contours.clear();
*/
\ No newline at end of file
ProyectoAndroid/ChessTrack/src/uy/edu/fing/chesstrack/modulovision/Manager.java 0 → 100644
View file @ a2136e1b
package uy.edu.fing.chesstrack.modulovision;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import uy.edu.fing.chesstrack.ajedrez.Logica;
import uy.edu.fing.chesstrack.communication.Client;
import uy.edu.fing.chesstrack.modulomodelador.Modelador;
import android.media.AudioManager;
import android.media.ToneGenerator;
import android.util.Log;
public class Manager {
private static final String TAG = "CHESSTRACK::MANAGER";
private static Manager _instance;
private static final int ARMANDO_TABLERO = 0;
private static final int JUGANDO = 1;
private static final int OK = 1;
private static final int NOT = 0;
private static final String WELCOME_MSG = ""
+ "--------------------------------------------------------------------------\n"
+ " .:: CHESSTRACK ::. seguimiento de una partida de Ajedrez\n"
+ "\n"
+ " TImag 2014\n"
+ " Nicolas Furquez - Aylen Ricca\n"
+ "--------------------------------------------------------------------------\n";
private static int _estado;
private static int _salida;
private static Adquisicion _adquisicion;
private static Client _client;
private static DetectorOclusion _detectorOclusion;
private static Modelador _modelador;
private static Logica _logica;
private final boolean _debug;
private int _cantJugada;
protected Manager() {
_estado = ARMANDO_TABLERO;
_salida = NOT;
_adquisicion = null;
_client = null;
_debug = false;
_cantJugada = 0;
}
public static Manager getInstance() {
if (_instance == null) {
_instance = new Manager();
}
return _instance;
}
public static int get_estado() {
return _estado;
}
public static void set_estado(int _estado) {
Manager._estado = _estado;
}
public void setConnection(String ip, int port) {
Log.i(TAG, "Setting connection");
_client = Client.getInstance();
_client.EstablishConnection(ip, port);
_client.SendData(WELCOME_MSG);
_salida = OK;
}
public boolean calibrar(Mat frame) {
Log.i(TAG, "Calibrando");
if (Calibracion.getInstance().calibrar(frame)) {
ToneGenerator toneG = new ToneGenerator(AudioManager.STREAM_ALARM,
50);
toneG.startTone(ToneGenerator.TONE_CDMA_ALERT_CALL_GUARD, 200); // ms
if (_salida == OK) {
_client.SendData("FIN calibrar\n . . . armando tablero!\n");
}
try {
_adquisicion = new Adquisicion();
_modelador = new Modelador();
_logica = new Logica();
} catch (Exception e) {
e.printStackTrace();
return false;
}
return true;
}
Log.i(TAG, "No calibrado");
ToneGenerator toneG = new ToneGenerator(AudioManager.STREAM_ALARM, 50);
toneG.startTone(ToneGenerator.TONE_CDMA_ALERT_CALL_GUARD, 700);
return false;
}
public void iniciarJuego() {
_estado = JUGANDO;
// beep
_detectorOclusion = new DetectorOclusion();
ToneGenerator toneG = new ToneGenerator(AudioManager.STREAM_ALARM, 50);
toneG.startTone(ToneGenerator.TONE_CDMA_ALERT_CALL_GUARD, 200); // ms
if (_salida == OK) {
Mat tableroInicio = _logica.getTableroInicio();
_client.SendData("TableroINICIO!\n");
_client.SendData(" ".concat(tableroInicio.dump().concat("\n")));
}
}
public Mat processFrame(Mat inputFrame) {
Log.i(TAG, "Acondicionamiento");
Mat region = _adquisicion.processFrame(inputFrame);
Log.i(TAG, "TYPE=" + (inputFrame.type() == CvType.CV_8UC4));
Log.i(TAG, "CHANNEL=" + (inputFrame.channels() == 4));
switch (_estado) {
case ARMANDO_TABLERO:
Log.i(TAG, "Armando Tablero");
Mat nuevo = _modelador.getMatrizFichas(region);
if (_logica.validarTableroArmado(nuevo)) {
iniciarJuego();
}
break;
case JUGANDO:
Log.i(TAG, "Jugando");
if (_detectorOclusion.hayNuevoTableroValido(region)) {
Log.i(TAG, "Tablero Valido");
// llamar al modelador
Mat aux = _modelador.getMatrizFichas(region);
// Log.i(TAG, "MATRIZ=" + aux.dump());
// region = _modelador.dibujarEscaquesSobel(2);
if (_logica.validarNuevoTablero(aux)) {
if (_salida == OK) {
_client.SendData("Nuevo Tablero Valido = ["
+ String.valueOf(_cantJugada) + "]\n");
_cantJugada++;
_client.SendData(" ".concat(aux.dump().concat("\n")));
}
}
}
break;
}
if (_debug) {
Log.i(TAG, "DEBUG");
Mat tmp = Mat.zeros(inputFrame.size(), CvType.CV_8UC4);
Mat matTMP = tmp.submat(Calibracion.getRectROI());
region.copyTo(matTMP);
return tmp;
}
return inputFrame;
}
public void destroy() {
if (_client != null) {
_client.Stop();
}
}
}
ProyectoAndroid/ChessTrack/src/uy/edu/fing/chesstrack/modulovision/imgproc/BackgroundSupress.java deleted 100644 → 0
View file @ 65200ec2
package uy.edu.fing.chesstrack.modulovision.imgproc;
import java.util.ArrayList;
import java.util.List;
import java.util.Random;
import java.util.Vector;
import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.core.MatOfPoint;
import org.opencv.core.Point;
import org.opencv.core.Rect;
import org.opencv.core.Scalar;
import org.opencv.core.Size;
import org.opencv.video.BackgroundSubtractorMOG;
import org.opencv.video.BackgroundSubtractorMOG2;
import org.opencv.imgproc.*;
import uy.edu.fing.chesstrack.communication.Client;
import android.graphics.SumPathEffect;
import android.media.AudioManager;
import android.media.ToneGenerator;
import android.util.Log;
public class BackgroundSupress implements ImgProcInterface {
private static final String TAG = "CHESSTRACK::BackgroundSupress";
private static int e = 0;
private final Mat fgMaskMOG;
private Mat fgMaskMOG2;
private final Mat morphKernel;
private final BackgroundSubtractorMOG pMOG;
private BackgroundSubtractorMOG2 pMOG2;
//private final List<MatOfPoint> contours;
private Client communicator;
private int estadoANTERIOR = 0;
private int estadoACTUAL = 0;
public BackgroundSupress() {
super();
morphKernel = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(3,3));
fgMaskMOG = new Mat(4,1,CvType.CV_8UC1);
fgMaskMOG2 = new Mat(4,1,CvType.CV_8UC1);
pMOG = new BackgroundSubtractorMOG(); //MOG approach
pMOG2 = new BackgroundSubtractorMOG2(); //MOG approach
Log.i(TAG, "at background supress constructor");
//contours = new ArrayList<MatOfPoint>();
communicator = Client.getInstance();
}
@Override
public Mat procesarImagen(Mat inputFrame) {
Log.i(TAG, "BackgroundS ");
Mat copy = new Mat(inputFrame.size(),CvType.CV_8UC3);
inputFrame.convertTo(copy, CvType.CV_8UC3);
Imgproc.cvtColor(inputFrame, copy, Imgproc.COLOR_BGRA2BGR);
pMOG.apply(copy, fgMaskMOG);
pMOG2.apply(copy, fgMaskMOG2,0);
Log.i(TAG, "Apply pMOG");
Imgproc.erode(fgMaskMOG2, fgMaskMOG2, morphKernel);
Log.i(TAG, "Apply erode");
Imgproc.threshold(fgMaskMOG2, fgMaskMOG2, 200, 255, Imgproc.THRESH_BINARY);
Log.i(TAG, "Apply threshold");
//Imgproc.dilate(fgMaskMOG2, fgMaskMOG2, morphKernel);
//Log.i(TAG, "Apply dilate");
Scalar suma = Core.sumElems(fgMaskMOG2);
Log.i(TAG, "SUMA = " + suma);
/*double maxArea = 0;
MatOfPoint largestContour = null;
Imgproc.findContours(fgMaskMOG2, contours, new Mat(), Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_TC89_L1);
for (MatOfPoint contour : contours) {
double area = Imgproc.contourArea(contour);
if (area > maxArea) {
maxArea = area;
largestContour = contour;
}
}
Log.i(TAG, "ESTABLE !!!" + maxArea);
if ((largestContour != null) && (maxArea > 10000)){
Log.i(TAG, "MANO !!!" + maxArea);
Rect boundingRect = Imgproc.boundingRect(largestContour);
ToneGenerator toneG = new ToneGenerator(AudioManager.STREAM_ALARM, 50);
toneG.startTone(ToneGenerator.TONE_CDMA_ALERT_CALL_GUARD, 200); // 200 is duration in ms
}*/
if (suma.val[0] > 100000){
estadoANTERIOR = estadoACTUAL;
estadoACTUAL = 1;
Log.i(TAG, "MANO !!!");
communicator.SendData("1\n");
Core.putText(fgMaskMOG2, "MANO !!!", new Point(50, 50),Core.FONT_HERSHEY_SIMPLEX, 0.8 , new Scalar(255,255,0));
// ToneGenerator toneG = new ToneGenerator(AudioManager.STREAM_ALARM, 50);
// toneG.startTone(ToneGenerator.TONE_CDMA_ALERT_CALL_GUARD, 200); // 200 is duration in ms
} else {
estadoANTERIOR = estadoACTUAL;
if (estadoANTERIOR == 1){
// estado transicion
estadoACTUAL = 3;
}
if (estadoANTERIOR == 3){
// estado estable
estadoACTUAL = 2;
pMOG2 = new BackgroundSubtractorMOG2(); //MOG2 approach
}
Log.i(TAG, "ESTABLE !!!");
communicator.SendData("0\n");
Core.putText(fgMaskMOG2, "ESTABLE !!!", new Point(50, 50),Core.FONT_HERSHEY_SIMPLEX, 0.5 , new Scalar(255,255,0));
}
/*Imgproc.findContours(fgMaskMOG2, contours, new Mat(), Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_NONE);
for(int idx = 0; idx < contours.size(); idx++)
{
double area = Imgproc.contourArea(contours.get(idx));
Log.i(TAG, "CONTOUR = AREA: " + area);
if ((area > 15000) && (area < 70000)){
Log.i(TAG, "DRAW !!! : " + area);
Scalar color = new Scalar(255,127,127);
Rect r = Imgproc.boundingRect(contours.get(idx));
Log.i(TAG, "3 at backgroundS "+(fgMaskMOG2.type() == CvType.CV_8UC1));
Core.rectangle(fgMaskMOG2, r.tl(), r.br(), color, 2, 8, 0);
//Imgproc.drawContours(fgMaskMOG2, contours, idx, color);
}
}
contours.clear();*/
Log.i(TAG, "END Background Sss");
return fgMaskMOG2;
}
}
ProyectoAndroid/ChessTrack/src/uy/edu/fing/chesstrack/modulovision/imgproc/EcualizarImagen.java
View file @ a2136e1b
......@@ -3,17 +3,32 @@ package uy.edu.fing.chesstrack.modulovision.imgproc;
import org.opencv.core.Mat;
import org.opencv.imgproc.Imgproc;
import android.util.Log;
public class EcualizarImagen implements ImgProcInterface {
private static final String TAG = "CHESSTRACK::Ecualizar";
@Override
public Mat procesarImagen(Mat inputFrame) {
// TODO Auto-generated method stub
//cvEqualizeHist(src,dest)
Mat viewGray = new Mat();
Imgproc.cvtColor(inputFrame, viewGray, Imgproc.COLOR_BGR2GRAY);
Imgproc.equalizeHist(viewGray,viewGray);
//Imgproc.equalizeHist(inputFrame,inputFrame);
return viewGray;
}
//List<Mat> channels = new ArrayList<Mat>();
Mat img_hist_equalized = new Mat();
Log.i(TAG, "processing Frame - INI");
Imgproc.cvtColor(inputFrame, img_hist_equalized, Imgproc.COLOR_BGR2GRAY);
Imgproc.equalizeHist(img_hist_equalized, img_hist_equalized);
Imgproc.cvtColor(img_hist_equalized, inputFrame, Imgproc.COLOR_GRAY2BGR);
/*// ecualizar en cada canal
Core.split(inputFrame, channels); // split the image into channels
//Imgproc.equalizeHist(channels.get(0), channels.get(0));
Imgproc.equalizeHist(channels.get(1), channels.get(1));
//Imgproc.equalizeHist(channels.get(2), channels.get(2));
Core.merge(channels, inputFrame);
*/
Log.i(TAG, "processing Frame - FIN");
return img_hist_equalized;
}
}
ProyectoAndroid/ChessTrack/src/uy/edu/fing/chesstrack/modulovision/imgproc/Homografia.java
View file @ a2136e1b
......@@ -16,7 +16,7 @@ public class Homografia implements ImgProcInterface {
private static final String TAG = "CHESSTRACK::Homografia";
private final Mat _matrizTransformada;
private final Rect _rectPOI;
private final Rect _rectROI;
private int _media;
private int _offset;
......@@ -29,9 +29,9 @@ public class Homografia implements ImgProcInterface {
Mat dst = new Mat(4,1,CvType.CV_32FC2);
Point p1, p2, p3, p4;
Point[] ret = getBestPoints(vertices, Calibracion.getInstance().getImagenCalibrada().size());
Point[] ret = getBestPoints(vertices, Calibracion.getInstance().get_sizeFrame());
Log.i(TAG, "Best Points= " + ret);
Log.i(TAG, "Best Points= " + ret.toString());
p1 = ret[0];
p2 = ret[1];
p3 = ret[2];
......@@ -46,7 +46,7 @@ public class Homografia implements ImgProcInterface {
_media = (int) Math.floor( Math.round((d12+d23+d34+d14)/4));
// El offset es el tamaño de dos celdas (para abarcar el primer casillero y dejar un borde al tablero
_offset = (_media/6);
_offset = 2*(_media/6);
Log.i(TAG, "media= " + _media);
Log.i(TAG, "offset= " + _offset);
......@@ -54,11 +54,11 @@ public class Homografia implements ImgProcInterface {
src.put(0,0, (int)p1.x,(int)p1.y, (int)p2.x,(int)p2.y, (int)p3.x,(int)p3.y, (int)p4.x,(int)p4.y);
dst.put(0,0, _offset,_offset, _offset+_media,_offset, _offset+_media,_offset+_media, _offset,_offset+_media );
_rectPOI = new Rect(new Point(0,0), new Point(2*_offset+_media,2*_offset+_media));
_rectROI = new Rect(new Point(0,0), new Point(2*_offset+_media,2*_offset+_media));
Calibracion.getInstance();
Calibracion.setRectPOI(_rectPOI);
Calibracion.setRectROI(_rectROI);
Log.i(TAG, "rectPOI size= " + _rectPOI.size());
Log.i(TAG, "rectROI size= " + _rectROI.size());
_matrizTransformada = Imgproc.getPerspectiveTransform(src,dst);
} else {
......@@ -72,13 +72,20 @@ public class Homografia implements ImgProcInterface {
@Override
public Mat procesarImagen(Mat inputFrame) {
Log.i(TAG, "processing Frame - INI");
double x = inputFrame.size().width;
double y = inputFrame.size().height;
if (x < _rectROI.size().width){
x = _rectROI.size().width;
}
if (y < _rectROI.size().height){
y = _rectROI.size().height;
}
Mat aux = new Mat();
// hace la homografia con la matriz calculada en un ppio
Imgproc.warpPerspective(inputFrame,inputFrame, _matrizTransformada, inputFrame.size());
Mat subMat = inputFrame.submat(_rectPOI);
Mat tmp = Mat.zeros(inputFrame.size(), CvType.CV_8UC4);
Mat matTMP = tmp.submat(_rectPOI);
subMat.copyTo(matTMP);
Imgproc.warpPerspective(inputFrame,aux, _matrizTransformada, new Size(x,y));
Mat tmp = Mat.zeros(_rectROI.size(), CvType.CV_8UC4);
(aux.submat(_rectROI)).copyTo(tmp);
Log.i(TAG, "processing Frame - FIN");
return tmp;
......
ProyectoAndroid/ChessTrack/src/uy/edu/fing/chesstrack/modulovision/imgproc/SustraccionDeFondo.java deleted 100644 → 0
View file @ 65200ec2
package uy.edu.fing.chesstrack.modulovision.imgproc;
import org.opencv.core.Mat;
import org.opencv.imgproc.Imgproc;
import org.opencv.video.BackgroundSubtractorMOG2;
public class SustraccionDeFondo implements ImgProcInterface {
private Mat fMaskMOG = null;
private final BackgroundSubtractorMOG2 pMOG;
private static final String TAG = "CHESSTRACK::SustraccionDeFondo";
public SustraccionDeFondo(){
pMOG = new BackgroundSubtractorMOG2();
//fMaskMOG = new Mat();
}
@Override
public Mat procesarImagen(Mat inputFrame) {
Imgproc.cvtColor(inputFrame, inputFrame, Imgproc.COLOR_RGBA2RGB);
fMaskMOG = new Mat(inputFrame.size(),inputFrame.channels());
pMOG.apply(inputFrame, fMaskMOG);
//Mat frame = inputFrame.submat(Calibracion.getInstance().getRectPOI());
//fMaskMOG = new Mat(frame.size(),frame.channels());
//pMOG.apply(frame, fMaskMOG);
//Imgproc.resize(inputFrame, frame, frame.size());
//Log.i(TAG, "Size frame= " + frame.size());
//Log.i(TAG, "Size fMaskMOG= " + fMaskMOG.size());
//Rect aux = Calibracion.getInstance().getRectPOI();
//frame.copyTo(frame,fMaskMOG);
//Mat subMat = inputFrame.submat(0,frame.rows(),0,frame.cols());
//frame.copyTo(subMat);
//Mat frame = new Mat();
//inputFrame.copyTo(frame,fMaskMOG);
return fMaskMOG;
}
}
samples/CMakeLists.txt
View file @ a2136e1b
......@@ -3,3 +3,6 @@ project( SubsBackground )
find_package( OpenCV REQUIRED )
add_executable( SubsBackground SubsBackground.cpp )
target_link_libraries( SubsBackground ${OpenCV_LIBS} )
project( Corners )
add_executable( Corners Corners.cpp )
target_link_libraries( Corners ${OpenCV_LIBS} )
samples/Corners.cpp 0 → 100644
View file @ a2136e1b
#include <string>
#include <iostream>
#include <vector>
#include "opencv2/opencv.hpp"
using namespace std;
using namespace cv;
//----------------------------------------------------------
// MAIN
//----------------------------------------------------------
int main(int argc, char* argv[])
{
// src image
Mat src;
// dst image
Mat dst;
// Image loading
namedWindow("result");
namedWindow("src");
src=imread("image.png",0);
cv::cvtColor(src,dst,cv::COLOR_GRAY2BGR);
Mat corners;
cv::goodFeaturesToTrack(src,corners,100,0.01,20.0);
for(int i=0;i<corners.rows;++i)
{
circle(dst,cv::Point(corners.at<float>(i,0),corners.at<float>(i,1)),3,Scalar(255,0,0),-1,CV_AA);
}
imshow("src",src);
imshow("result",dst);
//----------------------------------------------------------
// Wait key press
//----------------------------------------------------------
while (waitKey(0) != 'q');
destroyAllWindows();
return 0;
}
web/css/style.css
View file @ a2136e1b
......@@ -45,6 +45,7 @@ h5 {
}
p {
margin-bottom: 20px;
font-size: 15px;
}
.lead {
font-size: 14px;
......
web/desarrollo.html 0 → 100644
View file @ a2136e1b
<!DOCTYPE html>
<html lang="en">
<head>
<title>ChessTrack.::.Desarrollo</title>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<meta name="description" content="Your description">
<meta name="keywords" content="Your keywords">
<meta name="author" content="Your name">
<link rel="icon" href="img/favicon.ico" type="image/x-icon">
<link rel="shortcut icon" href="img/favicon.ico" type="image/x-icon" />
<link rel="stylesheet" href="css/bootstrap.css" type="text/css" media="screen">
<link rel="stylesheet" href="css/responsive.css" type="text/css" media="screen">
<link rel="stylesheet" href="css/camera.css" type="text/css" media="screen">
<link rel="stylesheet" href="css/style.css" type="text/css" media="screen">
<link href='http://fonts.googleapis.com/css?family=Open+Sans:400,600,700' rel='stylesheet' type='text/css'>
<script type="text/javascript" src="js/jquery.js"></script>
<script type="text/javascript" src="js/jquery.easing.1.3.js"></script>
<script type="text/javascript" src="js/camera.js"></script>
<script src="js/jquery.ui.totop.js" type="text/javascript"></script>
</head>
<body>
<!--==============================header=================================-->
<header class="p0">
<div class="container">
<div class="row">
<div class="span12">
<div class="header-block clearfix">
<div class="clearfix header-block-pad">
<h1 class="brand"><a href="index.html"><img src="img/logo.png" alt=""></a><span>Seguimiento de una Partida de Ajedrez.</span></h1>
<span class="contacts">Integrantes:<br>
<span>&nbsp;&nbsp;&nbsp;Aylen Ricca (<a href="mailto:aricca@fing.edu.uy">aricca@fing.edu.uy</a>)<br>&nbsp;&nbsp;&nbsp;Nicolás Furquez (<a href="mailto:nfurquez@fing.edu.uy">nfurquez@fing.edu.uy</a>)</span>
<br>Tutor:<br>
<span>&nbsp;&nbsp;&nbsp;Álvaro Gómez (<a href="mailto:agomez@fing.edu.uy">agomez@fing.edu.uy</a>)</span>
</span>
<span class="contacts">
<img src="img/chess0.png" alt="">
</span>
</div>
<div class="navbar navbar_ clearfix">
<div class="navbar-inner navbar-inner_">
<div class="container">
<a class="btn btn-navbar" data-toggle="collapse" data-target=".nav-collapse_">MENU</a>
<div class="nav-collapse nav-collapse_ collapse">
<ul class="nav sf-menu">
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<li class="sub-menu"><a href="#">Introducción</a>
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<h4>Desarrollo de la Solución</h4>
<h4>Armado del ambiente</h4>
<p><strong class="clr">A continuación se describe el ambiente utilizado para desarrollar.</strong><br>
Para desarrollar en Android, el ambiente utilizado fue el propuesto por la documentación que se presenta en este <a href="http://web.stanford.edu/class/ee368/Android/index.html">tutorial</a>.
Para armar el proyecto ChessTrack como una aplicación para Android se utilizaron los tutoriales que presenta <a href="http://docs.opencv.org/doc/tutorials/introduction/android_binary_package/O4A_SDK.html">Opencv4Android</a> en su documentación.
Debido a que el emulador para Android es sumamente lento en lo que respecta a su ejecución, y debuggear sobre un dispositivo es una tarea engorrosa, se decidió realizar las pruebas de conceptos en Matlab con OpenCV, valiéndose del kit de funciones mex de opencv para matlab obtenidas de <a href="http://www.cs.stonybrook.edu/~kyamagu/mexopencv/">mexopencv</a>.
Una vez validadas las funcionalidades se realizaron pruebas sobre dispositivos con Android.
También se hicieron algunas pruebas conceptuales en C/C++ utilizando la librería OpenCV dado que es más cómodo migrar luego el código programado al lenguaje Java.</p>
<figure><img src="galeria/eclipse4Android.png" class="img-radius" alt=""></figure>
<p>A modo de versionar el trabajo realizado, desde el desarrollo de la actividad para Android, las pruebas de conceptos y el contenido y análisis de las mismas, se generó un <a href="https://gitlab.fing.edu.uy/aricca/chessTrack">repositorio</a> con soporte institucional.</p>
<figure><img src="galeria/gitlab.png" class="img-radius" alt="" style="height: 440px"></figure>
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<h4>Pruebas desde matlab y desde C/C++</h4>
<p><strong class="clr">A continuación se describen las pruebas desarrolladas en matlab y C/C++.</strong><br>
Sobre Matlab y código en C++ se armaron pruebas de concepto de las ideas que iban surgiendo para varios aspectos del procesamiento.</p>
<p>Para la detección del tablero se pensó en una detección de esquinas</p>
<p>Detección de esquinas con la función <strong class="clr">corners</strong> desde matlab:</p>
<figure><img src="galeria/cornersM2.png" class="img-radius" alt="" style="width: 200px">&nbsp;&nbsp;&nbsp;<img src="galeria/cornersM1.png" class="img-radius" alt="" style="width: 200px"></figure>
<p>Detección de esquinas con la función <strong class="clr">goodFeaturesToTrack</strong> desde C++ con OpenCV:</p>
<figure><img src="galeria/cornersC2.png" class="img-radius" alt="" style="width: 200px">&nbsp;&nbsp;&nbsp;<img src="galeria/cornersC1.png" class="img-radius" alt="" style="width: 200px"></figure>
<p>Nos decidimos por utilizar la función <strong class="clr">findChessboardCorners</strong> que se utiliza para calibrar con tableros de ajedrez y retorna cuando encuentra un tablero interno de determinado tamaño, en este caso 7x7:</p>
<figure><img src="galeria/findChessBoardCorners.png" class="img-radius" alt=""></figure>
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<h4>Más Pruebas desde matlab y desde C/C++</h4>
<p>Para la detección de la mano se utilizó la estructura de OpenCV <a href="http://docs.opencv.org/trunk/doc/tutorials/video/background_subtraction/background_subtraction.html#background-subtraction">BackgroundSubtractorMOG</a> obteniendo luego la cantidad de píxeles que se diferencian del fondo, y seteando un umbral para determinar cuando hay una mano sobre el tablero y descartar esos frames, un ejemplo en C++ ejecutado sobre un video que realizamos:</p>
<p>A la izquierda se visualiza un video con la máscara, y a la derecha el video etiquetado con los estados: <strong class="clr">ESTABLE</strong> y <strong class="clr">MANO</strong> para diferenciar cuando descartar frames</p>
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<embed width="450" height="300" src="https://www.youtube.com/v/uiF0cZDhafI" type="application/x-shockwave-flash">
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<embed width="450" height="300" src="https://www.youtube.com/v/LCNMyQp4ANw" type="application/x-shockwave-flash">
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<p>A continuación se muestran los tableros obtenidos en la transición de estado <strong class="clr">MANO</strong> a estado <strong class="clr">ESTABLE</strong>.</p>
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<img src="galeria/tablero0.png" class="img-radius" alt="" style="width: 180px">
<img src="galeria/tablero1.png" class="img-radius" alt="" style="width: 180px">
<img src="galeria/tablero2.png" class="img-radius" alt="" style="width: 180px">
<img src="galeria/tablero3.png" class="img-radius" alt="" style="width: 180px">
<img src="galeria/tablero4.png" class="img-radius" alt="" style="width: 180px">
<img src="galeria/tablero5.png" class="img-radius" alt="" style="width: 180px">
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<img src="galeria/tablero6.png" class="img-radius" alt="" style="width: 180px">
<img src="galeria/tablero7.png" class="img-radius" alt="" style="width: 180px">
<img src="galeria/tablero8.png" class="img-radius" alt="" style="width: 180px">
<img src="galeria/tablero9.png" class="img-radius" alt="" style="width: 180px">
<img src="galeria/tablero10.png" class="img-radius" alt="" style="width: 180px">
<img src="galeria/tablero11.png" class="img-radius" alt="" style="width: 180px">
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<h4>Descripción general de módulos</h4>
<p>En esta sección se describen brevemente los módulos y sus actividades principales.</p>
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<h5>Modulo</h5>
<h3>Activity</h3>
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<p>Este módulo es la actividad Android que se encarga de recibir los eventos de la aplicación, en esta primera versión se cuenta con un menú con opciones de conexión y de calibración, mantiene una máquina de estados para modelar si se está en estado Calibrando o Jugando.</p>
<p>Cuando se selecciona del menú la conexión se ingresan los datos necesarios (a saber ip y puerto del servidor) y luego es el módulo Manager el encargado de mantener la misma.</p>
<p>Es en este módulo donde se reciben los frames de la cámara, y es el encargado de pasarlos al Manager a partir de que se selecciona la opción calibrar.</p>
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<h5>Modulo</h5>
<h3>Manager</h3>
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<p>Este módulo se encarga de manejar los estados de la aplicación. Comienza a tomar partido desde el evento calibrar, y es quien se comunica con el resto de los módulos que procesan los frames y también con el módulo que se comunica con el servidor para enviar las partidas.</p>
<p>Luego de la calibración válida este módulo se encuentra en el estado Armando Tablero, y cuando le notifican que está pronto el tablero para iniciar la partida, se pasa a estado Jugando.</p>
<p>Mantiene una bandera para saber si se debe enviar información al servidor, o no se ha seleccionado salida alguna.</p>
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<h5>Modulo de</h5>
<h3>Adquisición</h3>
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<p>En este módulo se emplean técnicas para el acondicionamiento de la imagen. Se cuenta con la clase Adquisición que dentro posee una lista de clases que implementan la interface ImgProcInterface. Dicha interfaz solo posee el método procesarImagen, que es llamado por el módulo Adquisición para cada una de las clases que se agregaron a la lista.</p>
<p>La idea detrás de este módulo es que el frame adquirido pase por una serie de acondicionamientos, cada uno siendo una clase que implementa la interface ImgProcInterface y agregándose a la lista en Adquisición. Se ejecutarán en el orden en que son agregadas.</p>
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<h5>Modulo de</h5>
<h3>Calibración</h3>
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<p>Este módulo es el encargado de calibrar el sistema antes de empezar la partida. Se encarga de localizar el tablero, obteniendo las esquinas internas y calculando la arista promedio del tablero interno.</p>
<p>Para la localización de las esquinas se utiliza como ya se mencionó la función de OpenCV findChessboardCorners.</p>
<p>Para que los usuarios sepan si pueden comenzar a armar el tablero se emite un beep, en caso de que no se hayan encontrado las esquinas se emiten dos beep y se deberá ajustar el dispositivo para lograr que la cámara visualice la totalidad del tablero.</p>
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<h5>Modulo</h5>
<h3>Oclusión</h3>
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<p>Se encarga de detectar si la imagen obtenida se encuentra estable para ser procesada o si por el contrario un jugador está realizando un movimiento, por lo cual no debe procesarse el tablero.</p>
<p>Para la detección de la oclusión, es decir, que hay una mano realizando una movida, se utiliza la estructura BackgroundSubtractorMOG.</p>
<p>Internamente este módulo mantiene estados. Oclusión: es cuando hay un jugador realizando una jugada; Transición: al cual se pasa inmediatamente se ha dejado de visualizar la mano; Enviar Tablero: donde se valida que es un tablero limpio para detectar fichas.
La existencia del estado Transición se realiza para asegurar un tablero completamente libre de sombras.</p>
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<h5>Modulo</h5>
<h3>Modelador</h3>
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<p>Este módulo es el encargado de a partir de una imagen obtener información de cada escaque reconociendo si existe una ficha o no en el mismo.</p>
<p>Para la detección de piezas se utiliza una detección utilizando sobel sobre la región céntrica del escaque, y se aplica un umbral para determinar la existencia de una pieza.</p>
<p>La detección de piezas es empleada durante el armado, para saber si se ha llegado a la configuración inicial del tablero, y también se utiliza para detectar las piezas en un tablero válido (sin oclusión).</p>
<p>La salida de la detección de piezas es una matriz binaria de tamaño 8x8 con 1 donde hay fichas y 0 sino</p>
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<h5>Modulo</h5>
<h3>Lógica</h3>
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<p>Este módulo contiene la lógica de las reglas de Ajedrez y se encarga de procesar las matrices que Modelador retorna para saber qué fichas se movieron y a dónde.</p>
<p>En esta primera versión únicamente valida el tablero actual contra el anterior para saber si se ha producido un cambio. También valida al comienzo, luego del calibrado si el tablero está en la configuración inicial.</p>
<p>La idea de la primer validación mencionada es para saber cuándo enviarle al servidor un tablero con cambios.</p>
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<h5>Modulo</h5>
<h3>Comunicación</h3>
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<p>En este módulo se debería implementar todas las posibles salidas que se desee obtener de la partida, quizás a partir de una interfaz que recibe el movimiento y se implementa un tipo de salida (persistencia en archivo, enviar a un servidor, texto a voz,etc).</p>
<p>Por temas de tiempo en este módulo sólo se implementó una clase que se encarga de enviar la matriz de las fichas a un servidor configurable.</p>
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<h4>Técnicas empleadas</h4>
<p><strong class="clr">A continuación se describen las tecnicas empleadas, algunas ya mencionadas anteriormente.</strong><br>
Primeramente, se emplea para la calibración, una detección de esquinas usando el metodo findChessboardCorners. De esta manera se obtienen las esquinas interiores del tablero de ajedrez. Con las esquinas detectadas se determinan las cuatro más externas, la distancia promedio entre las cuatro aristas que determinan y se localizan los cuatro mejores puntos para realizar una homografía y así enderezar el tablero en caso de estar inclinado. A su vez
se recorta para solo tener la región del tablero en la imagen para procesar y colocarlo en una posición conocida. Con este proceso también se obtiene el tamaño de los escaques y de todo el tablero.</p>
<p>Luego de acondicionar la imagen se utiliza un proceso de supresión de fondo para detectar cuando se esta haciendo el movimiento de las fichas, para esto se utilizan los métodos de BackgroundSubtractorMOG2 de la librería OpenCV, se realiza además un erode y un threshold de la máscara producida para determinar si se encuentra en un estado de oclusión.</p>
<p>Para la detección de fichas se obtienen de cada frame la sub imagen correspondiente al área central de cada escaque, se le hace un filtro de Sobel para la detección de bordes, a su vez se binariza una imagen a partir de cierto umbral. Luego para eliminar ruido se hace un erode, y un dilate para acrecentar los pixeles donde hay fichas. Si la cantidad de pixeles blancos pasan cierto umbral se puede decir que se encuentra una ficha en el escaque.</p>
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<h4>Consideraciones sobre la Solución</h4>
<p><strong class="clr">A continuación se detallan aspectos relacionados a la solución.</strong><br>
La solución que se llegó fue más acotada de lo que se planteó en un inicio, dado que se hizo énfasis en el procesamiento de imágenes y no tanto en el problema, es que actualmente (Julio 2014) la aplicación solo detecta donde hay fichas y luego de cada movimiento de un jugador manda una matriz 8x8 binaria indicando donde hay o no fichas si hubo un movimiento efectivo.</p>
<p>Otra consideración importante para el uso de la aplicación es la iluminación, la misma debe de ser uniforme. Dado que era una de las precondiciones del proyecto, no se tuvo en cuenta en ninguno de los algoritmos de procesamiento de imágenes para tratar temas de iluminación no uniforme.</p>
<p>Otro hecho a tener en cuenta para el uso de la aplicación es el tamaño del tablero y la altura donde debe de estar el dispositivo para poder ver todo el tablero.</p>
<p>La calibración no es automática, se debe de decirle a la aplicación que debe de calibrar para detectar el tablero, luego de detectarlo emite un pitido y el dispositivo no puede ser movido de esa posición, así como tampoco se permite la re-calibración luego de iniciada la partida. Es importante apreciar que el plano de la cámara debe de ser paralelo al plano del tablero y que éste más una margen de un escaque han de aparecer en la imagen de la aplicación. No importa de qué lado van a estar las fichas con respecto al dispositivo, pero si la rotación del tablero con respecto al mismo, lo ideal es que las líneas del tablero sean paralelas a los bordes de la imagen, aunque la aplicación puede soportar una pequeña rotación del mismo con respecto a esta alineación, siempre que se consideren los márgenes antes mencionados.</p>
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<p>Para el envío de la partida a un servidor externo, como ya se comentó, solamente se envía un tablero con unos y ceros, los cuales representan el tablero y las fichas. Dicho servidor es dedicado a esta aplicación y se encuentra dentro del repositorio del proyecto. Para usarlo se debe de levantar el mismo en un pc con java, y luego antes de calibrar, configurar la ip y el puerto (actualmente es el 5556) en la aplicación.</p>
<p>Igualmente la aplicación permite una jugabilidad importante (siempre dentro de partidas lentas), luego de calibrar, la misma aplicación detecta cuando esta todo el tablero armado y emite un pitido, de ahí en más, espera a que se hagan movimientos y detecta cambios de fichas.</p>
<p>Es importante tener en cuenta cómo se debe de armar el tablero, dado que la detección es automática. Se ha de poner una ficha en el medio del tablero (no importa de qué jugador) y colocar el resto de las piezas en su lugar, cuando esté todo pronto para empezar la partida, se coloca la pieza que se encuentra en el medio del tablero en su lugar, y se espera a que el dispositivo emite un pitido, indicando que se puede comenzar a jugar.
Esto último es para evitar que durante el armado se dé un caso de borde que es cuando se detecta la mano como una o varias piezas y si se dá que están cubiertas las filas 1, 2, 7 y 8 debido a esta situación, la aplicación entenderá que se está pronto para jugar.</p>
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<p>Para visualizar imágenes ver la <a href="galeria_de_imagenes.html">Galería de Imágenes</a> y <a href="videos.html">Videos</a></p>
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<h1 class="brand"><a href="index.html"><img src="img/logo.png" alt=""></a><span>Seguimiento de una Partida de Ajedrez.</span></h1>
<span class="contacts">Integrantes:<br>
<span>&nbsp;&nbsp;&nbsp;Aylen Ricca (<a href="mailto:aricca@fing.edu.uy">aricca@fing.edu.uy</a>)<br>&nbsp;&nbsp;&nbsp;Nicolás Furquez (<a href="mailto:nfurquez@fing.edu.uy">nfurquez@fing.edu.uy</a>)</span>
<br>Tutor:<br>
<span>&nbsp;&nbsp;&nbsp;Álvaro Gómez (<a href="mailto:agomez@fing.edu.uy">agomez@fing.edu.uy</a>)</span>
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<p>Como antecedentes se cuenta con un proyecto de la asignatura llevado a cabo en 2013, 8x8CAM, el cual es similar en características pero desarrollado para PC y sólo se tomaban fotogramas del tablero antes y después del movimiento, en nuestro caso el procesamiento es en tiempo real y es de sumo interés poder identificar cuándo obtener frames con tableros válidos.</p>
<p>El tablero utilizado será uno profesional como los de la figura, proporcionado por el tutor; se utilizará un ambiente donde la iluminación será controlada y la partida será “lenta”, con esto se quiere decir que se dará tiempo al dispositivo a procesar la partida entre movimiento y movimiento.</p>
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<img src="galeria/img_desc_03.png" class="img-radius" alt="Tablero Profesional" style="width: 250px">
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<img src="galeria/img_desc_04.png" class="img-radius" alt="Tablero Profesional" style="width: 250px">
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<p>Como objetivo opcional, se plantea la posibilidad de transcribir la partida a voz para jugadores no videntes.</p>
<p>Dado que una partida normal de ajedrez es muy rica en movimientos, en un principio se plantea la detección de una partida con movimientos básicos, en la segunda iteración se incluirá la detección de jake y jake mate, valiéndose de las <a href="http://es.wikipedia.org/wiki/Reglamento_del_ajedrez">reglas</a> oficiales de ajedrez, si el tiempo lo permite se tratará de detectar enroques, coronaciones (promociones) y captura al paso, igualmente se tendrá en cuenta en el diseño de la arquitectura estos casos especiales para una futura extensión.</p>
<p>Para procesar las capturas de una forma más eficiente se usará la biblioteca <a href="http://docs.opencv.org/doc/tutorials/introduction/android_binary_package/O4A_SDK.html">OpenCV4Android</a> dado que cuenta con una gran cantidad de utilitarios para el procesamiento de imágenes.</p>
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<h4>Descripción del Proyecto.</h4>
<p><strong class="clr">En los siguientes párrafos se describen los lineamientos del proyecto.</strong><br>
El trabajo que se aborda es el procesamiento en tiempo real de una partida lenta de ajedrez desde un dipositivo móvil mediante tratamiento de imágenes. A su vez, contar con la persistencia y/o transmisión de la partida en <a href="http://es.wikipedia.org/wiki/Notaci%C3%B3n_algebraica">notación algebraica</a>.</p>
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<a href="https://www.youtube.com/v/GdQmgzBK0Jo"><img src="galeria/img_desc_01.png" class="img-radius" alt="Reproducción de partida" style="width: 300px"></a>
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<img src="galeria/img_desc_02.png" class="img-radius" alt="Notación algebraica" style="height: 300px">
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<p>Las restricciones que se plantean para esta realidad son la utilización de un tablero profesional, su ubicación en una posicion fija, iluminación controlada y el dispositivo móvil colocado de tal manera que pueda captar con su cámara la totalidad del tablero.</p>
<p>EL proyecto se en marca dentro del proyecto final la asignatura <a href="https://eva.fing.edu.uy/course/view.php?id=520">Tratamiendo de Imágenes por Computador</a> del <a href="http://iie.fing.edu.uy/">Instituto de Ingeniería Eléctrica</a> de la Facultad de Ingeniería de la Universidad de la República. El mismo, como se mencionó anteriormente consiste en reconocer el movimiento de las piezas dentro de una partida de ajedrez. El problema es interesante desde el punto de vista del tratamiento de imágenes, dado que posee una complejidad rica en problemas comunes en el proceso de racionalizar una imagen, desde detectar dónde se ubica cada ficha en todo momento y reconocer su recorrido, hasta saber cuando no se debe de procesar una imagen ya que el jugador está moviendo las piezas en ese momento.</p>
<p>El problema planteado se presenta en el marco de una partida de ajedrez clásica, en donde interesa transcribir a notación algebraica la partida, en tiempo real, para ser enviada a un servidor o un jugador remoto. Como hoy en día es muy accesible tener un celular con la potencia para procesar imágenes, el proyecto se llava a cabo con la tecnología <a href="http://developer.android.com/index.html">Android</a>.</p>
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Proyecto de fin de curso 2014 de Tratamiento de Imágenes por Computadora dictado en la Facultad de Ingeniería de la Universidad de la República, Uruguay
<br>Sitio web del curso: <a href="https://eva.fing.edu.uy/course/view.php?id=520">Tratamiento de Imágenes por Computadora</a>
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