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Commit 91616de2 authored by Andrey Filippov's avatar Andrey Filippov
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trying with actual kernels

parent be7e6c62
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Showing with 508 additions and 217 deletions
src/main/java/EyesisCorrectionParameters.java
View file @ 91616de2
......@@ -1666,7 +1666,15 @@ public class EyesisCorrectionParameters {
public double dbg_sigma =2.0;
public String dbg_mask = ".........:::::::::.........:::::::::......*..:::::*:::.........:::::::::.........";
public int dbg_mode = 1; // 0 - old LMA, 1 - new LMA
public int dbg_window_mode = 2; // 0 - none, 1 - square, 2 - sin
public int dbg_window_mode = 2; // 0 - none, 1 - square, 2 - sin 3 - sin^2
public boolean centerWindowToTarget = true;
// parameters to extract a kernel from the kernel image file
public int color_channel = 2; // green (<0 - use simulated kernel, also will use simulated if kernels are not set)
public int decimation = 2; // decimate original kernel this much in each direction
public double decimateSigma = 0.4; // what is the optimal value for each decimation?
public int tileX = 82; // number of kernel tile (0..163)
public int tileY = 62; // number of kernel tile (0..122)
public DCTParameters(
int dct_size,
......@@ -1697,7 +1705,6 @@ public class EyesisCorrectionParameters {
properties.setProperty(prefix+"asym_tax_free", this.asym_tax_free+"");
properties.setProperty(prefix+"seed_size", this.seed_size+"");
properties.setProperty(prefix+"asym_random", this.asym_random+"");
properties.setProperty(prefix+"LMA_steps", this.LMA_steps+"");
properties.setProperty(prefix+"dbg_x", this.dbg_x+"");
properties.setProperty(prefix+"dbg_y", this.dbg_y+"");
......@@ -1707,6 +1714,12 @@ public class EyesisCorrectionParameters {
properties.setProperty(prefix+"dbg_mask", this.dbg_mask+"");
properties.setProperty(prefix+"dbg_mode", this.dbg_mode+"");
properties.setProperty(prefix+"dbg_window_mode", this.dbg_window_mode+"");
properties.setProperty(prefix+"centerWindowToTarget", this.centerWindowToTarget+"");
properties.setProperty(prefix+"color_channel", this.color_channel+"");
properties.setProperty(prefix+"decimation", this.dbg_window_mode+"");
properties.setProperty(prefix+"decimateSigma", this.decimateSigma+"");
properties.setProperty(prefix+"tileX", this.tileX+"");
properties.setProperty(prefix+"tileY", this.tileY+"");
}
public void getProperties(String prefix,Properties properties){
......@@ -1728,32 +1741,46 @@ public class EyesisCorrectionParameters {
if (properties.getProperty(prefix+"dbg_sigma")!=null) this.dbg_sigma=Double.parseDouble(properties.getProperty(prefix+"dbg_sigma"));
if (properties.getProperty(prefix+"dbg_mask")!=null) this.dbg_mask=properties.getProperty(prefix+"dbg_mask");
if (properties.getProperty(prefix+"dbg_mode")!=null) this.dbg_mode=Integer.parseInt(properties.getProperty(prefix+"dbg_mode"));
if (properties.getProperty(prefix+"tileY")!=null) this.tileY=Integer.parseInt(properties.getProperty(prefix+"tileY"));
if (properties.getProperty(prefix+"centerWindowToTarget")!=null) this.centerWindowToTarget=Boolean.parseBoolean(properties.getProperty(prefix+"centerWindowToTarget"));
if (properties.getProperty(prefix+"color_channel")!=null) this.color_channel=Integer.parseInt(properties.getProperty(prefix+"color_channel"));
if (properties.getProperty(prefix+"decimation")!=null) this.decimation=Integer.parseInt(properties.getProperty(prefix+"decimation"));
if (properties.getProperty(prefix+"decimateSigma")!=null) this.decimateSigma=Double.parseDouble(properties.getProperty(prefix+"decimateSigma"));
if (properties.getProperty(prefix+"tileX")!=null) this.tileX=Integer.parseInt(properties.getProperty(prefix+"tileX"));
if (properties.getProperty(prefix+"dbg_window_mode")!=null) this.dbg_window_mode=Integer.parseInt(properties.getProperty(prefix+"dbg_window_mode"));
}
public boolean showDialog() {
GenericDialog gd = new GenericDialog("Set DCT parameters");
gd.addNumericField("DCT size", this.dct_size, 0); //32
gd.addNumericField("Size of asymmetrical (non-DCT) kernel", this.asym_size, 0); //6
gd.addNumericField("Maximal number of non-zero pixels in direct convolution kernel", this.asym_pixels, 0); //6
gd.addNumericField("How far to try a new asym kernel pixel from existing ones", this.asym_distance, 0); //6
gd.addNumericField("MDCT window type (0,1,2)", this.dct_window, 0); //0..2
gd.addNumericField("LMA_steps", this.LMA_steps, 0); //0..2
gd.addNumericField("Compactness (punish off-center asym_kernel pixels (proportional to r^2)", this.compactness, 2); //0..2
gd.addNumericField("Factorization target precision (stop if achieved)", this.fact_precision, 4); //0..2
gd.addNumericField("Do not punish pixels in the square around center", this.asym_tax_free, 0); //0..2
gd.addNumericField("DCT size", this.dct_size, 0);
gd.addNumericField("Size of asymmetrical (non-DCT) kernel", this.asym_size, 0);
gd.addNumericField("Maximal number of non-zero pixels in direct convolution kernel", this.asym_pixels, 0);
gd.addNumericField("How far to try a new asym kernel pixel from existing ones", this.asym_distance, 0);
gd.addNumericField("MDCT window type (0,1,2)", this.dct_window, 0);
gd.addNumericField("LMA_steps", this.LMA_steps, 0);
gd.addNumericField("Compactness (punish off-center asym_kernel pixels (proportional to r^2)", this.compactness,2);
gd.addNumericField("Factorization target precision (stop if achieved)", this.fact_precision, 4);
gd.addNumericField("Do not punish pixels in the square around center", this.asym_tax_free, 0);
gd.addNumericField("Start asym_kernel with this number of pixels (0 - single, 4n+0 (X between cells), 4*n+1 - x around center cell", this.seed_size, 0); //0..2
gd.addNumericField("Initialize asym_kernel with random numbers (amplitude)", this.asym_random, 2); //0..2
gd.addNumericField("dbg_x", this.dbg_x, 2); //0..2
gd.addNumericField("dbg_y", this.dbg_y, 2); //0..2
gd.addNumericField("dbg_x1", this.dbg_x1, 2); //0..2
gd.addNumericField("dbg_y1", this.dbg_y1, 2); //0..2
gd.addNumericField("dbg_sigma", this.dbg_sigma, 3); //0..2
gd.addStringField ("Debug mask (anything but * is false)", this.dbg_mask,100);
gd.addNumericField("LMA implementation: 0 - old, 1 - new", this.dbg_mode, 0); //32
gd.addNumericField("Convolution window: 0 - none, 1 - square, 2 - sin, 3 - sin^2", this.dbg_window_mode, 0); //32
// gd.addNumericField("Debug Level:", MASTER_DEBUG_LEVEL, 0);
gd.addNumericField("Initialize asym_kernel with random numbers (amplitude)", this.asym_random, 2);
gd.addNumericField("dbg_x", this.dbg_x, 2);
gd.addNumericField("dbg_y", this.dbg_y, 2);
gd.addNumericField("dbg_x1", this.dbg_x1, 2);
gd.addNumericField("dbg_y1", this.dbg_y1, 2);
gd.addNumericField("dbg_sigma", this.dbg_sigma, 3);
gd.addStringField ("Debug mask (anything but * is false)", this.dbg_mask, 100);
gd.addNumericField("LMA implementation: 0 - old, 1 - new", this.dbg_mode, 0);
gd.addNumericField("Convolution window: 0 - none, 1 - square, 2 - sin, 3 - sin^2", this.dbg_window_mode, 0);
gd.addCheckbox ("Center convolution window around target kernel center", this.centerWindowToTarget);
gd.addNumericField("Color channel to extract kernel (<0 - use synthetic)", this.color_channel, 0);
gd.addNumericField("Convolution kernel decimation (original is normally 2x)", this.decimation, 0);
gd.addNumericField("Smooth convolution kernel before decimation", this.decimateSigma, 3);
gd.addNumericField("Tile X to extract (0..163)", this.tileX, 0);
gd.addNumericField("Tile Y to extract (0..122)", this.tileY, 0);
gd.showDialog();
if (gd.wasCanceled()) return false;
this.dct_size= (int) gd.getNextNumber();
this.asym_size= (int) gd.getNextNumber();
......@@ -1774,6 +1801,12 @@ public class EyesisCorrectionParameters {
this.dbg_mask= gd.getNextString();
this.dbg_mode= (int) gd.getNextNumber();
this.dbg_window_mode= (int) gd.getNextNumber();
this.centerWindowToTarget= gd.getNextBoolean();
this.color_channel= (int) gd.getNextNumber();
this.decimation= (int) gd.getNextNumber();
this.decimateSigma= gd.getNextNumber();
this.tileX= (int) gd.getNextNumber();
this.tileY= (int) gd.getNextNumber();
// MASTER_DEBUG_LEVEL= (int) gd.getNextNumber();
return true;
......
src/main/java/EyesisDCT.java
View file @ 91616de2
This diff is collapsed.
src/main/java/Eyesis_Correction.java
View file @ 91616de2
This diff is collapsed.
src/main/java/FactorConvKernel.java
View file @ 91616de2
......@@ -78,7 +78,7 @@ public class FactorConvKernel {
public double currentRMS ;
public double firstRMS;
public double nextRMS ;
public double [] RMSes = {-1.0,-1.0};
public double currentRMSPure=-1.0; // calculated RMS for the currentVector->currentfX
public double nextRMSPure= -1.0; // calculated RMS for the nextVector->nextfX
public double firstRMSPure= -1.0; // RMS before current series of LMA started
......@@ -98,7 +98,8 @@ public class FactorConvKernel {
public double goal_rms_pure;
public LMAData lMAData = null;
public int numLMARuns = 0;
public int target_window_mode = 2; // 0 - none, 1 - square, 2 - sin
public int target_window_mode = 2; // 0 - none, 1 - square, 2 - sin, 3 - sin^2
public boolean centerWindowToTarget = true; // center convolution weights around target kernel center
public class LMAArrays {
public double [][] jTByJ= null; // jacobian multiplied by Jacobian transposed
......@@ -141,6 +142,7 @@ public class FactorConvKernel {
public double [] saved_rmses = null;
public double [] first_rmses = null;
public int target_window_mode = 2; // 0 - none, 1 - square, 2 - sin
public boolean centerWindowToTarget = true; // center convolution weights around target kernel center
public LMAData(){
......@@ -148,8 +150,9 @@ public class FactorConvKernel {
public LMAData( int debugLevel){
this.debugLevel = debugLevel;
}
public void setTargetWindowMode(int mode){
target_window_mode = mode;
public void setTargetWindowMode(int mode, boolean centerWindowToTarget){
this.target_window_mode = mode;
this.centerWindowToTarget = centerWindowToTarget;
}
public void initLMAData(){
......@@ -390,20 +393,36 @@ public class FactorConvKernel {
System.out.println("getWeight(), delete jacobian");
}
if ((weights[0] == null) || (weights[0].length != target_kernel.length)){
if (debugLevel > 2){
System.out.println("Convolution weight is null/outdated, regenerating default (only center part)");
int xc = 0;
int yc = 0;
int conv_size = asym_size + 2*sym_radius-2;
int cc = conv_size/2;
if (this.centerWindowToTarget) {
double s0=0.0,sx=0.0,sy=0.0;
for (int i = 0; i < conv_size; i++){
for (int j = 0; j < conv_size; j++){
double d = target_kernel[conv_size*i+j];
d *= d;
s0 += d;
sx += d* (j - cc);
sy += d* (i - cc);
}
}
xc = (int) Math.round(sx/s0);
yc = (int) Math.round(sy/s0);
}
double [] sins = new double [2*sym_radius-1];
for (int i = 1; i< 2*sym_radius; i++) sins[i-1] = Math.sin(Math.PI*i/(2.0 * sym_radius));
weights[0] = new double [target_kernel.length];
int conv_size = asym_size + 2*sym_radius-2;
int left_top_margin = ((asym_size-1)/2); // inclusive
int right_bottom_margin = left_top_margin + (2 * sym_radius - 1); // exclusive
int left_margin = ((asym_size-1)/2) +xc; // inclusive
int top_margin = ((asym_size-1)/2) + yc; // inclusive
int right_margin = left_margin + (2 * sym_radius - 1); // exclusive
int bottom_margin = top_margin + (2 * sym_radius - 1); // exclusive
for (int i = 0; i < conv_size; i++) {
for (int j = 0; j < conv_size; j++){
int cindx = i * conv_size + j;
if ((i >= left_top_margin) && (i < right_bottom_margin) && (j >= left_top_margin) && (j < right_bottom_margin)) {
weights[0][cindx] = (target_window_mode>=2)?(sins[i-left_top_margin]*sins[j-left_top_margin]):1.0;
if ((i >= top_margin) && (i < bottom_margin) && (j >= left_margin) && (j < right_margin)) {
weights[0][cindx] = (target_window_mode>=2)?(sins[i-top_margin]*sins[j-left_margin]):1.0;
if (target_window_mode == 3) {
weights[0][cindx]*=weights[0][cindx];
}
......@@ -413,6 +432,8 @@ public class FactorConvKernel {
}
}
}
// public boolean centerWindowToTarget = true; // center convolution weights around target kernel center
//target_window_mode
rebuildMapsPars(false); // only if it does not exist
double sw = 0.0;
......@@ -749,6 +770,7 @@ public class FactorConvKernel {
} // class LMAData
public FactorConvKernel(){
this.new_mode =true;
}
public FactorConvKernel(boolean new_mode){
......@@ -760,8 +782,17 @@ public class FactorConvKernel {
this.sym_radius = sym_radius;
}
public void setTargetWindowMode(int mode){
public void setTargetWindowMode(int mode, boolean centerWindowToTarget){
target_window_mode = mode;
this.centerWindowToTarget = centerWindowToTarget;
}
public double[] getRMSes(){
return this.RMSes; // lMAData.getRMSes();
}
public double getTargetRMS(){
return lMAData.getTargetRMSW();
}
public double [] generateAsymWeights(
......@@ -844,7 +875,9 @@ public class FactorConvKernel {
lMAData.setSymKernel(null, sym_mask_frozen);
levenbergMarquardt();
lMAData.setSymKernel(null, sym_mask);
return levenbergMarquardt();
boolean OK = levenbergMarquardt();
this.RMSes = lMAData.getRMSes().clone();
return OK;
} else{
initLevenbergMarquardt_old(fact_precision, seed_size, asym_random);
if (mask != null){
......@@ -1116,6 +1149,7 @@ public class FactorConvKernel {
System.out.println();
}
}
this.RMSes = RMSes.clone();
return numAsym;
}
......@@ -2148,16 +2182,7 @@ public class FactorConvKernel {
private void initLevenbergMarquardt(double fact_precision, int seed_size, double asym_random){
lMAData = new LMAData(debugLevel);
lMAData.setTarget(target_kernel);
lMAData.setTargetWindowMode(target_window_mode);
/* double s = 0.0;
for (int i = 0; i<target_kernel.length; i++){
s+= target_kernel[i]*target_kernel[i];
}
this.goal_rms_pure = Math.sqrt(s/target_kernel.length)*fact_precision;
*/
// this.currentVector = setInitialVector(target_kernel, null); // should be (asym_size + 2*sym_radius-1)**2
lMAData.setTargetWindowMode(target_window_mode, centerWindowToTarget);
double [][]kernels = setInitialVector(target_kernel, seed_size, asym_random); // should be (asym_size + 2*sym_radius-1)**2
sym_kernel_scale = kernels[0][0];
for (int i=0;i<kernels[0].length;i++) if (!Double.isNaN(kernels[0][i])) kernels[0][i] /=sym_kernel_scale;
......@@ -2166,13 +2191,9 @@ public class FactorConvKernel {
lMAData.setAsymKernel(kernels[1]);
this.goal_rms_pure = lMAData.getTargetRMSW()*fact_precision;
this.target_rms = lMAData.getTargetRMSW(); //Math.sqrt(s/target_kernel.length);
// lMAData.invalidateLMAArrays(); // should be in each run , not at init
resetLMARuns();
// this.currentVector = setVectorFromKernels(kernels[0], kernels[1]);
}
private boolean levenbergMarquardt(){
long startTime=System.nanoTime();
this.iterationStepNumber = 0;
......
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