public void run() {
-
ImageReader imageReader=new ImageReader();
-// int[] input = getInput(false);
int[] input=imageReader.readImage("1.bmp");
-// for(int i = 0; i <input.length; i++) {
- // System.out.println(input[i]);
- // }
+ // TASK: blur & mergeBP
int pnum = 32; // 60;
setBPNum(pnum);
int range = (input[0]) / pnum;
- //System.out.println(range + " " + input[0]);
for (int i = 0; i < pnum; i++) {
BlurPiece bp = new BlurPiece(i, range, input, pnum);
bp.blur();
addBP(bp);
}
- // TODO
- /*for(int i = 0; i < this.m_image.length; i++) {
- System.out.println( this.m_image[i]);
- }*/
postBlur();
float[] Icur = getImage();
- // TODO
- /*for(int i = 0; i < Icur.length; i++) {
- System.out.println(Icur[i]);
- }*/
-
pnum = 16; // 30;
range = getRows() / pnum;
int rows = getRows();
}
imageXM.calcSobel_dX();
-
// create ImageY to calc Sobel_dY
ImageYM imageYM = new ImageYM(pnum, rows, cols);
for (int i = 0; i < pnum; i++) {
// create a Lambda to aggregate results from the ImageXs
Lambda lda = new Lambda(WINSZ, N_FEA, pnum, getNumP());
lda.calcGoodFeature(imageXM, imageYM);
-// lda.calcGoodFeature(eom_imageXM, eom_imageYM);
// validation
//lda.printImage();
lda.reshape();
// validation
// lda.printImage();
- // TASK: calcInd
+ // TASK: calculates indicies
int r = lda.getR();
float[] data = lda.getImage();
int c_rows = lda.getRows();
int c_pnum = lda.getNumP();
int c_range = c_rows / c_pnum;
+ // TASK: processIDX
IDX IDXarray[]=new IDX[c_pnum];
for (int i = 0; i < c_pnum; i++) {
sese parallel_IDX{
resize();
+ // TASK: merge IDX
for (int i = 0; i < c_pnum; i++) {
addIDX(IDXarray[i]);
}
- //print3f();
-
- // TASK:calcFeatures
+ // TASK: calcFeatures
calcFeatures();
- // TASK:startTrackingLoop
-// do{
+ // TASK: startTrackingLoop
for(int count=1;count<=m_counter; count++){
int prevSize=getRows()*getCols();
prevSize=getRowsR()*getColsR();
float[] prevImageR=new float[prevSize];
System.arraycopy(getImageR(), 0, prevImageR, 0, prevSize);
-
+
+ //TASK: processIXL, mergeIXL , processIYL, mergeIYL
int pnum1 = 8; // 15; // * 2;
data = getImage();
rows = getRows();
cols = getCols();
range = rows / pnum1;
-
+
IXLM ixlm = new IXLM(pnum1, data, rows, cols);
IYLM iylm = new IYLM(pnum1, data, rows, cols);
for (int i = 0; i < pnum1; i++) {
iyl.calcSobel_dY();
iylm.addCalcSobelResult(iyl);
}
+
ixlm.calcSobel_dX();
iylm.calcSobel_dY();
+ //TASK: processIXLR, mergeIXLR , processIYLR, mergeIYLR
data = getImageR();
rows = getRowsR();
cols = getColsR();
System.out.println("read image: "+count+".bmp");
input = imageReader.readImage(count+".bmp");
this.m_count++;
-// input = getInput(true);
-// input = imageReader.readImage((m_count+1)+".bmp");
-// this.m_count++;
-
-
-// float ip1[]=new float[getRows()*getCols()];
-// for(int ip1idx=0;ip1idx<getRows()*getCols();ip1idx++){
-// ip1[ip1idx]=(float)input[ip1idx+4];
-// }
-// float[] ip2=resize(ip1);
-//
range = (input[0]) / pnum2;
BlurPieceL bplArray[]=new BlurPieceL[pnum2];
setBPLNum(pnum2);
startTrackingLoop();
- //task addBPL
+ //TASK: blurL, addBPL
for(int i=0;i<pnum2;i++){
addBPL( bplArray[i]);
}
resize();
- //task calcTrack
-
+ //TASK: calcTrack
calcTrack(prevImage, prevImageR, ixlm, iylm, ixlmr, iylmr);
}
-// }while(!isFinish());
printFeatures();
}