i have to write a java program that recognizes all the letters in a picture taken with android camera .I tried KNN method but i could only recognize a single letter in the picture and i want to recognize all the letters .Can someonr help me. This is my code
public void train (){
//Creating Training Data
Mat trainData = new Mat();
Mat train_labels = new Mat();
for (int i =1; i <15; i++) {
String path = Environment.getExternalStorageDirectory().toString() + "/Pictures/New Folder/" + i + ".png";
Mat img =Imgcodecs.imread(path);
Log.i(TAG,"error debug: "+i+img.empty());
img.convertTo(img, CvType.CV_32FC1); // Convert to float
Size dsize = new Size(25,25);
Imgproc.resize(img, img, dsize);
img.convertTo(img, CvType.CV_32FC1);
Mat imgResized = img.reshape(1, 1); //make continuous
trainData.push_back(imgResized);
train_labels.push_back(new Mat (1,1,CvType.CV_32FC1,new Scalar(i)));// add 1 item
}
Mat response=new Mat();
Mat tmp;
tmp= train_labels.reshape(1,1); //make continuous
tmp.convertTo(response,CvType.CV_32FC1); // Convert to float*/
KNearest knn = KNearest.create();
knn.train(trainData,Ml.ROW_SAMPLE, train_labels);
//For Storing training data
String path = Environment.getExternalStoragePublicDirectory(Environment.DIRECTORY_DOWNLOADS).toString() ;
Bitmap bmpOut1 = Bitmap.createBitmap(trainData.cols(), trainData.rows(), Bitmap.Config.ARGB_8888);
Bitmap bmpOut2 = Bitmap.createBitmap(response.cols(), response.rows(), Bitmap.Config.ARGB_8888);
response.convertTo(response,CvType.CV_8UC1);
trainData.convertTo(trainData,CvType.CV_8UC1);
Utils.matToBitmap(trainData, bmpOut1);
Utils.matToBitmap(response, bmpOut2);
//File file = new File(path);
// file.mkdirs();
File file = new File(path, "train.png");
File file2 = new File(path, "response.png");
OutputStream fout = null;
OutputStream fout2 = null;
try {
fout = new FileOutputStream(file);
fout2 = new FileOutputStream(file2);
BufferedOutputStream bos = new BufferedOutputStream(fout);
BufferedOutputStream bos2 = new BufferedOutputStream(fout2);
bmpOut1.compress(Bitmap.CompressFormat.PNG, 100, bos);
bos.flush();
bos.close();
bmpOut1.recycle();
bmpOut2.compress(Bitmap.CompressFormat.PNG, 100, bos2);
bos2.flush();
bos2.close();
bmpOut2.recycle();
} catch (FileNotFoundException e) {
e.printStackTrace();
}
catch (IOException e) {
e.printStackTrace();
}
//For Accessing training data in BMP file
BitmapFactory.Options o = new BitmapFactory.Options();
o.inScaled = false;
Bitmap blankBitmap = BitmapFactory.decodeResource(getResources(), R.drawable.train,o);
int trainWidth = blankBitmap.getWidth();
int trainHeight = blankBitmap.getHeight();
Mat trainData2 = new Mat();
Utils.bitmapToMat(blankBitmap,trainData2);
Bitmap blankBitmap2 = BitmapFactory.decodeResource(getResources(), R.drawable.response,o);
int resWidth = blankBitmap2.getWidth();
int resHeight = blankBitmap2.getHeight();
Log.i(TAG,"res width "+ resWidth +" res Height"+ resHeight);
Mat response2 = new Mat();
Utils.bitmapToMat(blankBitmap2,response2);
Log.i(TAG,"response2 width "+ response2.cols() +" res Height"+ response2.rows());
Mat response3 = new Mat();
Mat trainData3 = new Mat();
Imgproc.cvtColor(response2,response2,Imgproc.COLOR_BGRA2GRAY); // 1. change the number of channels
Imgproc.cvtColor(trainData2,trainData2,Imgproc.COLOR_BGRA2GRAY);
response2.convertTo(response3,CvType.CV_32FC1);
trainData2.convertTo(trainData3,CvType.CV_32FC1);
KNearest knn2 = KNearest.create();
knn2.train(trainData3,Ml.ROW_SAMPLE, response3);
Mat img = Imgcodecs.imread("/storage/emulated/0/DCIM/Camera/IMG.png");
Log.i(TAG,"error1 img: "+img.empty());
Mat test = new Mat();
Imgproc.resize(img,test, new Size(25,25) );
test.convertTo(test, CvType.CV_32FC1);
Mat results = new Mat();
Mat responses = new Mat();
Mat dists = new Mat();
float label = knn.findNearest(test.reshape(1,1), 1,results,responses,dists);
Log.i(TAG,"valeur "+label);
if (1.0<=label && label <=8.0)
{
reply.setText("N");
}
else if (9.0<=label && label <=14.0){
reply.setText("E");
}
else
reply.setText("rien");
}
}
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