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Update PersonRecognizer.java #29

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304 changes: 98 additions & 206 deletions facerecognition/src/main/java/cultoftheunicorn/marvel/PersonRecognizer.java
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Original file line number Diff line number Diff line change
@@ -1,9 +1,8 @@
package cultoftheunicorn.marvel;

import static com.googlecode.javacv.cpp.opencv_highgui.*;
import static com.googlecode.javacv.cpp.opencv_core.*;

import static com.googlecode.javacv.cpp.opencv_imgproc.*;
import static com.googlecode.javacv.cpp.opencv_highgui.*;
import static com.googlecode.javacv.cpp.opencv_core.*;
import static com.googlecode.javacv.cpp.opencv_imgproc.*;

import java.io.File;
import java.io.FileOutputStream;
Expand All @@ -12,212 +11,105 @@
import org.opencv.android.Utils;
import org.opencv.core.Mat;

import com.googlecode.javacv.cpp.opencv_imgproc;
import com.googlecode.javacv.cpp.opencv_contrib.FaceRecognizer;
import com.googlecode.javacv.cpp.opencv_core.IplImage;
import com.googlecode.javacv.cpp.opencv_core.MatVector;

import android.graphics.Bitmap;
import android.util.Log;

public class PersonRecognizer {

FaceRecognizer faceRecognizer;
String mPath;
int count=0;
Labels labelsFile;

static final int WIDTH= 128;
static final int HEIGHT= 128;;
private int mProb=999;


PersonRecognizer(String path) {
faceRecognizer = com.googlecode.javacv.cpp.opencv_contrib.createLBPHFaceRecognizer(2,8,8,8,200);
// path=Environment.getExternalStorageDirectory()+"/facerecog/faces/";
mPath=path;
labelsFile= new Labels(mPath);


}

void add(Mat m, String description) {
Bitmap bmp= Bitmap.createBitmap(m.width(), m.height(), Bitmap.Config.ARGB_8888);

Utils.matToBitmap(m,bmp);
bmp= Bitmap.createScaledBitmap(bmp, WIDTH, HEIGHT, false);

FileOutputStream f;
try {
f = new FileOutputStream(mPath+description+"-"+count+".jpg",true);
count++;
bmp.compress(Bitmap.CompressFormat.JPEG, 100, f);
f.close();

} catch (Exception e) {
Log.e("error",e.getCause()+" "+e.getMessage());
e.printStackTrace();

}
}

public boolean train() {

File root = new File(mPath);

FilenameFilter pngFilter = new FilenameFilter() {
public boolean accept(File dir, String name) {
return name.toLowerCase().endsWith(".jpg");

};
};

File[] imageFiles = root.listFiles(pngFilter);

MatVector images = new MatVector(imageFiles.length);

int[] labels = new int[imageFiles.length];

int counter = 0;
int label;

IplImage img;
IplImage grayImg;

int i1=mPath.length();


for (File image : imageFiles) {
String p = image.getAbsolutePath();
img = cvLoadImage(p);

if (img==null)
Log.e("Error","Error cVLoadImage");
Log.i("image",p);

int i2=p.lastIndexOf("-");
int i3=p.lastIndexOf(".");
int icount=Integer.parseInt(p.substring(i2+1,i3));
if (count<icount) count++;

String description=p.substring(i1,i2);

if (labelsFile.get(description)<0)
labelsFile.add(description, labelsFile.max()+1);

label = labelsFile.get(description);

grayImg = IplImage.create(img.width(), img.height(), IPL_DEPTH_8U, 1);

cvCvtColor(img, grayImg, CV_BGR2GRAY);

images.put(counter, grayImg);

labels[counter] = label;

counter++;
}
if (counter>0)
if (labelsFile.max()>1)
faceRecognizer.train(images, labels);
labelsFile.Save();
return true;
}

public boolean canPredict()
{
if (labelsFile.max()>1)
return true;
else
return false;

}

public String predict(Mat m) {
if (!canPredict())
return "";
int n[] = new int[1];
double p[] = new double[1];
IplImage ipl = MatToIplImage(m,WIDTH, HEIGHT);
// IplImage ipl = MatToIplImage(m,-1, -1);

faceRecognizer.predict(ipl, n, p);

if (n[0]!=-1)
mProb=(int)p[0];
else
mProb=-1;
// if ((n[0] != -1)&&(p[0]<95))
if (n[0] != -1)
return labelsFile.get(n[0]);
else
return "Unknown";
}




IplImage MatToIplImage(Mat m,int width,int heigth)
{


Bitmap bmp=Bitmap.createBitmap(m.width(), m.height(), Bitmap.Config.ARGB_8888);


Utils.matToBitmap(m, bmp);
return BitmapToIplImage(bmp,width, heigth);

}

IplImage BitmapToIplImage(Bitmap bmp, int width, int height) {

if ((width != -1) || (height != -1)) {
Bitmap bmp2 = Bitmap.createScaledBitmap(bmp, width, height, false);
bmp = bmp2;
}

IplImage image = IplImage.create(bmp.getWidth(), bmp.getHeight(),
IPL_DEPTH_8U, 4);

bmp.copyPixelsToBuffer(image.getByteBuffer());

IplImage grayImg = IplImage.create(image.width(), image.height(),
IPL_DEPTH_8U, 1);

cvCvtColor(image, grayImg, opencv_imgproc.CV_BGR2GRAY);

return grayImg;
}



protected void SaveBmp(Bitmap bmp,String path)
{
FileOutputStream file;
try {
file = new FileOutputStream(path , true);

bmp.compress(Bitmap.CompressFormat.JPEG,100,file);
file.close();
}
catch (Exception e) {
// TODO Auto-generated catch block
Log.e("",e.getMessage()+e.getCause());
e.printStackTrace();
}

}


public void load() {
train();

}

public int getProb() {
// TODO Auto-generated method stub
return mProb;
}


}
public class PersonRecognizer {

private static final int WIDTH = 128;
private static final int HEIGHT = 128;
private static final String TAG = "PersonRecognizer";

private FaceRecognizer faceRecognizer;
private String mPath;
private int count = 0;
private Labels labelsFile;
private int mProb = 999;

public PersonRecognizer(String path) {
faceRecognizer = com.googlecode.javacv.cpp.opencv_contrib.createLBPHFaceRecognizer(2, 8, 8, 8, 200);
mPath = path;
labelsFile = new Labels(mPath);
}

public void add(Mat m, String description) {
Bitmap bmp = Bitmap.createBitmap(m.width(), m.height(), Bitmap.Config.ARGB_8888);
Utils.matToBitmap(m, bmp);
bmp = Bitmap.createScaledBitmap(bmp, WIDTH, HEIGHT, false);

try (FileOutputStream f = new FileOutputStream(mPath + description + "-" + count + ".jpg", true)) {
count++;
bmp.compress(Bitmap.CompressFormat.JPEG, 100, f);
} catch (Exception e) {
Log.e(TAG, "Error saving image: " + e.getMessage(), e);
}
}

public boolean train() {
File root = new File(mPath);
File[] imageFiles = root.listFiles(new FilenameFilter() {
@Override
public boolean accept(File dir, String name) {
return name.toLowerCase().endsWith(".jpg");
}
});

if (imageFiles == null || imageFiles.length == 0) {
Log.e(TAG, "No images found for training.");
return false;
}

MatVector images = new MatVector(imageFiles.length);
int[] labels = new int[imageFiles.length];

int counter = 0;

for (File image : imageFiles) {
String p = image.getAbsolutePath();
IplImage img = cvLoadImage(p);

if (img == null) {
Log.e(TAG, "Error loading image: " + p);
continue;
}

Log.i(TAG, "Processing image: " + p);
String description = extractDescription(p);
int label = getOrCreateLabel(description);

IplImage grayImg = IplImage.create(img.width(), img.height(), IPL_DEPTH_8U, 1);
cvCvtColor(img, grayImg, CV_BGR2GRAY);

images.put(counter, grayImg);
labels[counter] = label;
counter++;
}

if (counter > 0 && labelsFile.max() > 1) {
faceRecognizer.train(images, labels);
labelsFile.Save();
return true;
}
return false;
}

public boolean canPredict() {
return labelsFile.max() > 1;
}

public String predict(Mat m) {
if (!canPredict()) {
return "";
}

int[] n = new int[1];
double[] p = new double[1];
IplImage ipl = matToIplImage(m, WIDTH, HEIGHT);
faceRecognizer.predict(ipl, n, p);

mProb = (n[0] != -1) ? (int) p[0] : -1;
return (n[0] != -1) ? labelsFile.get(n