Skip to content

I
imagej-elphel
Commit 8991226b authored by Andrey Filippov's avatar Andrey Filippov
Browse files
Options

Tweaking software to handle more precise disparity measurements

parent 957badd3
Hide whitespace changes
Inline Side-by-side
Showing with 2765 additions and 2811 deletions
src/main/java/CLTPass3d.java
View file @ 8991226b
......@@ -6,7 +6,7 @@
** Copyright (C) 2017 Elphel, Inc.
**
** -----------------------------------------------------------------------------**
**
**
** CLTPass3d.java is free software: you can redistribute it and/or modify
** it under the terms of the GNU General Public License as published by
** the Free Software Foundation, either version 3 of the License, or
......@@ -28,9 +28,9 @@ import java.util.concurrent.atomic.AtomicInteger;
public class CLTPass3d{
// static double max_overexposed = 0.8; // TODO: make parameter
public double [][] disparity; // per-tile disparity set for the pass[tileY][tileX]
public double [][] disparity; // per-tile disparity set for the pass[tileY][tileX]
public int [][] tile_op; // what was done in the current pass
private double [][] disparity_sav; // saved disaprity
private double [][] disparity_sav; // saved disaprity
private int [][] tile_op_sav; // saved tile_op
public double [][] disparity_map = null; // add 4 layers - worst difference for the port
double [] calc_disparity = null; // composite disparity, calculated from "disparity", and "disparity_map" fields
......@@ -45,7 +45,7 @@ public class CLTPass3d{
// Bg disparity & strength is calculated from the supertiles and used instead of the tile disparity if it is too weak. Assuming, that
// foreground features should have good correlation details, and if the tile does not nhave them it likely belongs to the background.
// calculate disparity and strength from the (lapped) supertiles, using lowest allowed (>= minBgDisparity) disparity histogram maximums
// of the supertiles this tile belongs to
// of the supertiles this tile belongs to
private double minBgDisparity = 0.0;
private double minBgFract = 0.0; // Use the lowest maximum if the strength strength (of all maximus >= minBgDisparity)
// exceeds minBgFract, otherwise proceed to the next one (and accumulate strength)
......@@ -61,14 +61,14 @@ public class CLTPass3d{
public Rectangle texture_bounds;
public int dbg_index;
public int disparity_index = ImageDtt.DISPARITY_INDEX_CM; // may also be ImageDtt.DISPARITY_INDEX_POLY
SuperTiles superTiles = null;
TileProcessor tileProcessor;
public CLTPass3d (TileProcessor tileProcessor)
{
this.tileProcessor = tileProcessor;
}
public CLTPass3d (TileProcessor tileProcessor, int mode)
{
this.tileProcessor = tileProcessor;
......@@ -77,7 +77,7 @@ public class CLTPass3d{
tile_op = new int [tileProcessor.getTilesY()][tileProcessor.getTilesX()];
disparity = new double [tileProcessor.getTilesY()][tileProcessor.getTilesX()];
break;
}
}
......@@ -85,7 +85,7 @@ public class CLTPass3d{
{
return this.tileProcessor;
}
public double [][][][] getTextureTiles()
{
return texture_tiles;
......@@ -121,7 +121,7 @@ public class CLTPass3d{
if (n < 3) scales[n] = 1.0/255.0; // R,B,G
else if (n == 3) scales[n] = 1.0; //alpha
else if (n < 8) scales[n] = 1.0; // ports 0..3
else scales[n] = 1.0/255.0; // RBG rms, in 1/255 units, but small
else scales[n] = 1.0/255.0; // RBG rms, in 1/255 units, but small
}
double [][] tileTones = new double [num_layers][numTiles];
for (int ty = 0; ty < tilesY; ty++ ) if (texture_tiles[ty] != null){
......@@ -140,7 +140,7 @@ public class CLTPass3d{
}
return tileTones;
}
public String getTextureName()
{
if (texture != null) {
......@@ -149,8 +149,8 @@ public class CLTPass3d{
return "null-texture-name";
}
}
// Will not work if texture is disabled
public void updateSelection(){ // add updating border tiles?
int tilesX = tileProcessor.getTilesX();
......@@ -165,34 +165,34 @@ public class CLTPass3d{
if (maxY < ty) maxY = ty;
if (minY > ty) minY = ty;
} else {
selected[ty * tilesX + tx] = false; // may be omitted
selected[ty * tilesX + tx] = false; // may be omitted
}
}
texture_bounds = new Rectangle(minX, minY, maxX - minX +1, maxY - minY +1 );
}
public Rectangle getTextureBounds(){
return texture_bounds;
}
public boolean isProcessed(){
return calc_disparity != null;
return calc_disparity != null;
}
public boolean isMeasured(){
return is_measured;
// return (disparity_map != null) && (disparity != null); // disparity == null for composite scans
}
public boolean isCombo(){
return is_combo;
return is_combo;
}
/**
* Called after each measurement
*/
public void resetProcessed(){
public void resetProcessed(){
if (disparity_map != null) fixNaNDisparity();
calc_disparity = null; // composite disparity, calculated from "disparity", and "disparity_map" fields
calc_disparity_hor = null; // composite disparity, calculated from "disparity", and "disparity_map" fields
......@@ -206,8 +206,8 @@ public class CLTPass3d{
// border_tiles = null; // these are border tiles, zero out alpha
// selected = null; // which tiles are selected for this layer
superTiles = null;
}
/**
* Get FPGA-calculated per-tile maximal differences between the particular image and the average one.
......@@ -220,24 +220,24 @@ public class CLTPass3d{
for (int i = 0; i< ImageDtt.QUAD; i++) these_diffs[i] = disparity_map[ImageDtt.IMG_DIFF0_INDEX + i];
return these_diffs;
}
public void resetCalc(){ // only needed if the same task was reused
calc_disparity = null;
strength = null;
strength_hor = null;
strength_vert = null;
superTiles = null;
}
public boolean [] getSelected(){
return selected;
}
public boolean [] getBorderTiles(){
return this.border_tiles;
}
public void setSelected (boolean [] selected) {
this.selected = selected;
}
......@@ -245,7 +245,7 @@ public class CLTPass3d{
this.border_tiles = border_tiles;
}
public void fixNaNDisparity()
{
fixNaNDisparity(
......@@ -261,8 +261,8 @@ public class CLTPass3d{
disparity_map[ImageDtt.DISPARITY_INDEX_VERT],
disparity_map[ImageDtt.DISPARITY_INDEX_VERT_STRENGTH]);
}
public void fixNaNDisparity(
boolean [] select, // which tiles to correct (null - all)
double [] disparity,
......@@ -316,7 +316,7 @@ public class CLTPass3d{
}
}
}
public double [] combineHorVertStrength(
boolean combineHor,
boolean combineVert)
......@@ -336,7 +336,7 @@ public class CLTPass3d{
}
return strength;
}
public double [] combineSuper(
boolean updateStrength, // use ST strength if true, keep original (update disparity only) if false
double stStrengthScale,
......@@ -347,7 +347,7 @@ public class CLTPass3d{
double [] strength = getStrength();
double [] disparity = getDisparity(0);
for (int i = 0; i < disparity.length; i++){
if (strength[i] < useSuper) {
disparity[i] = bgTileDisparity[i];
......@@ -360,12 +360,12 @@ public class CLTPass3d{
public double [] getOverexposedFraction(){
return (disparity_map != null)? disparity_map[ImageDtt.OVEREXPOSED] : null;
}
/**
* Returns per-tile correlation "strength". Initially - copy of the FPGA-generated data, but later may be replaced by a combination
* of the combined data from 4-sensor (4-pair) correlation and horizontal/vertical pairs only to improve detection of vertical/
* horizontal features
* horizontal features
* @return line-scan array of per-tile correlation strength by reference (not a copy), so it can be modified
*/
public double [] getStrength(){
......@@ -375,13 +375,13 @@ public class CLTPass3d{
strength = disparity_map[ImageDtt.DISPARITY_STRENGTH_INDEX].clone();
if (trustedCorrelation > 0.0){
for (int i = 0; i < strength.length; i++){
if (Math.abs(disparity_map[disparity_index][i]) > trustedCorrelation) strength[i] = 0.0; // too far
if (Math.abs(disparity_map[disparity_index][i]) > trustedCorrelation) strength[i] = 0.0; // too far
}
}
double [] overexposed = disparity_map[ImageDtt.OVEREXPOSED];
if ((max_overexposure > 0.0) && (overexposed != null)){
for (int i = 0; i < strength.length; i++){
if (overexposed[i] > max_overexposure) strength[i] = 0.0; // too overexposed
if (overexposed[i] > max_overexposure) strength[i] = 0.0; // too overexposed
}
}
}
......@@ -405,16 +405,16 @@ public class CLTPass3d{
strength_hor = disparity_map[ImageDtt.DISPARITY_INDEX_HOR_STRENGTH].clone();
if (trustedCorrelation > 0.0){
for (int i = 0; i < strength_hor.length; i++){
if (Math.abs(disparity_map[ImageDtt.DISPARITY_INDEX_HOR][i]) > trustedCorrelation) strength_hor[i] = 0.0; // too far
if (Math.abs(disparity_map[ImageDtt.DISPARITY_INDEX_HOR][i]) > trustedCorrelation) strength_hor[i] = 0.0; // too far
}
}
double [] overexposed = disparity_map[ImageDtt.OVEREXPOSED];
if ((max_overexposure > 0.0) && (overexposed != null)){
for (int i = 0; i < strength_hor.length; i++){
if (overexposed[i] > max_overexposure) strength_hor[i] = 0.0; // too overexposed
if (overexposed[i] > max_overexposure) strength_hor[i] = 0.0; // too overexposed
}
}
}
return strength_hor;
}
......@@ -429,25 +429,25 @@ public class CLTPass3d{
strength_vert = disparity_map[ImageDtt.DISPARITY_INDEX_VERT_STRENGTH].clone();
if (trustedCorrelation > 0.0){
for (int i = 0; i < strength_vert.length; i++){
if (Math.abs(disparity_map[ImageDtt.DISPARITY_INDEX_VERT][i]) > trustedCorrelation) strength_vert[i] = 0.0; // too far
if (Math.abs(disparity_map[ImageDtt.DISPARITY_INDEX_VERT][i]) > trustedCorrelation) strength_vert[i] = 0.0; // too far
}
}
double [] overexposed = disparity_map[ImageDtt.OVEREXPOSED];
if ((max_overexposure > 0.0) && (overexposed != null)){
for (int i = 0; i < strength_hor.length; i++){
if (overexposed[i] > max_overexposure) strength_vert[i] = 0.0; // too overexposed
if (overexposed[i] > max_overexposure) strength_vert[i] = 0.0; // too overexposed
}
}
}
return strength_vert;
}
/**
* Get Get combine per-tile disparity values from correlation combined with pre-programmed initial disparity shift.
* @return line-scan array of per-tile disparity by reference (not a copy), so it can be modified
*/
public double [] getDisparity() // get calculated combo disparity
{
return getDisparity(0);
......@@ -472,7 +472,7 @@ public class CLTPass3d{
return calc_disparity_combo;
}
}
// methods to "condition" measured disparity values
public void conditionDisparity()
{
......@@ -500,7 +500,7 @@ public class CLTPass3d{
}
calc_disparity_combo = calc_disparity.clone(); // for now - just clone, can be modified separately and combined with hor/vert
}
/**
* Replaces current combo disparity for tiles that are weak and do not have any neighbor within disparity range from this one
* @param selection optional boolean mask of tiles to use/update
......@@ -509,8 +509,8 @@ public class CLTPass3d{
* @param disparityFar minimal acceptable disparity for weak tiles
* @param disparityNear maximal acceptable disparity for weak tiles
* @return mask of weak (replaced) tiles
*
* Replace weak by a weighted average of non-weak. If there are none - use weak ones, including this one too.
*
* Replace weak by a weighted average of non-weak. If there are none - use weak ones, including this one too.
*/
public boolean[] replaceWeakOutlayers(
final boolean [] selection,
......@@ -524,14 +524,14 @@ public class CLTPass3d{
{
final int tilesX = tileProcessor.getTilesX();
final int tilesY = tileProcessor.getTilesY();
final int nTiles = tilesX*tilesY;
final boolean [] weakOutlayers = new boolean [nTiles];
int [] dirs8 = {-tilesX, -tilesX + 1, 1, tilesX +1, tilesX, tilesX - 1, -1, -tilesX - 1};
final int [] dirs = dirs8;
final double [] disparity = getDisparity(0);
final double [] strength = getStrength();
final double absMinDisparity = 0.5 * disparityFar; // adjust? below this is definitely wrong (weak)
final double absMinDisparity = 0.5 * disparityFar; // adjust? below this is definitely wrong (weak)
final double absMaxDisparity = 1.5 * disparityNear; // change?
final int dbg_nTile = (debugLevel > 0) ? 43493: -1; // x=77,y=134; // 42228; // x = 108, y = 130 46462; // 41545;
final Thread[] threads = ImageDtt.newThreadArray(tileProcessor.threadsMax);
......@@ -539,6 +539,7 @@ public class CLTPass3d{
final AtomicInteger ai = new AtomicInteger(0);
for (int ithread = 0; ithread < threads.length; ithread++) {
threads[ithread] = new Thread() {
@Override
public void run() {
for (int nTile = ai.getAndIncrement(); nTile < nTiles; nTile = ai.getAndIncrement()) {
if (((strength[nTile] < weakStrength) ||
......@@ -589,14 +590,15 @@ public class CLTPass3d{
}
}
};
}
}
ImageDtt.startAndJoin(threads);
// second pass - replace outliers
final double [] src_disparity = disparity.clone();
ai.set(0);
for (int ithread = 0; ithread < threads.length; ithread++) {
threads[ithread] = new Thread() {
@Override
public void run() {
for (int nTile = ai.getAndIncrement(); nTile < nTiles; nTile = ai.getAndIncrement()) {
if (nTile == dbg_nTile){
......@@ -609,7 +611,7 @@ public class CLTPass3d{
if (!weakOutlayers[nTile1] && ((selection == null) || selection[nTile1 ]) ) {
double w = strength[nTile1];
sw += w;
sd += w * src_disparity[nTile1];
sd += w * src_disparity[nTile1];
}
}
if (sw == 0) { // Nothing strong around - repeat with weak and this one too.
......@@ -624,7 +626,7 @@ public class CLTPass3d{
w = strength[nTile1];
if (!Double.isNaN( src_disparity[nTile1])) {
sw += w;
sd += w * src_disparity[nTile1];
sd += w * src_disparity[nTile1];
}
}
}
......@@ -636,11 +638,11 @@ public class CLTPass3d{
}
}
};
}
}
ImageDtt.startAndJoin(threads);
return weakOutlayers;
}
public boolean [] getUntestedBackgroundBorder (
final boolean [] known,
final double [] disparity,
......@@ -656,6 +658,7 @@ public class CLTPass3d{
final AtomicInteger ai = new AtomicInteger(0);
for (int ithread = 0; ithread < threads.length; ithread++) {
threads[ithread] = new Thread() {
@Override
public void run() {
for (int nTile = ai.getAndIncrement(); nTile < num_tiles; nTile = ai.getAndIncrement()) {
if (known[nTile]){
......@@ -673,11 +676,11 @@ public class CLTPass3d{
}
}
};
}
}
ImageDtt.startAndJoin(threads);
return untested_bgnd;
}
public boolean [] measuredTiles ()
{
final int tilesX = tileProcessor.getTilesX();
......@@ -688,6 +691,7 @@ public class CLTPass3d{
final AtomicInteger ai = new AtomicInteger(0);
for (int ithread = 0; ithread < threads.length; ithread++) {
threads[ithread] = new Thread() {
@Override
public void run() {
for (int nTile = ai.getAndIncrement(); nTile < num_tiles; nTile = ai.getAndIncrement()) {
int tX = nTile % tilesX;
......@@ -696,11 +700,11 @@ public class CLTPass3d{
}
}
};
}
}
ImageDtt.startAndJoin(threads);
return measured;
}
public void saveTileOpDisparity()
{
disparity_sav =disparity.clone();
......@@ -718,7 +722,7 @@ public class CLTPass3d{
restoreTileOpDisparity();
saveTileOpDisparity();
}
public int setTileOpDisparity(
boolean [] selection,
double [] disparity)
......@@ -731,7 +735,7 @@ public class CLTPass3d{
selection, // boolean [] selection,
disparity); // double [] disparity)
}
public int setTileOpDisparity(
int tile_op,
boolean [] selection,
......@@ -765,7 +769,7 @@ public class CLTPass3d{
}
return num_op_tiles;
}
/**
* Set next measurement disparity from last calculated
*/
......@@ -773,14 +777,14 @@ public class CLTPass3d{
{
setTileOpDisparity(null, getDisparity(0));
}
public double [] getSecondMaxDiff (
final boolean averaged)
{
final double [][] diffs = getDiffs();
if (diffs == null) return null;
final int tilesX = tileProcessor.getTilesX();
final int tilesY = tileProcessor.getTilesY();
final int num_tiles = tilesX * tilesY;
......@@ -790,6 +794,7 @@ public class CLTPass3d{
final AtomicInteger ai = new AtomicInteger(0);
for (int ithread = 0; ithread < threads.length; ithread++) {
threads[ithread] = new Thread() {
@Override
public void run() {
for (int nTile = ai.getAndIncrement(); nTile < num_tiles; nTile = ai.getAndIncrement()) {
int imax1 = 0;
......@@ -804,7 +809,7 @@ public class CLTPass3d{
}
}
};
}
}
ImageDtt.startAndJoin(threads);
if (!averaged) return second_max;
final TileNeibs tnImage = new TileNeibs(tilesX, tilesY); // num_tiles/tilesX);
......@@ -813,6 +818,7 @@ public class CLTPass3d{
ai.set(0);
for (int ithread = 0; ithread < threads.length; ithread++) {
threads[ithread] = new Thread() {
@Override
public void run() {
for (int nTile = ai.getAndIncrement(); nTile < num_tiles; nTile = ai.getAndIncrement()) if (measured[nTile]) {
double sw = 0.0;
......@@ -824,17 +830,17 @@ public class CLTPass3d{
swd += dir_weights[dir] * second_max[nTile1] ;
}
}
second_max_averaged[nTile] = swd/sw;
second_max_averaged[nTile] = swd/sw;
}
}
};
}
}
ImageDtt.startAndJoin(threads);
return second_max_averaged;
}
// same, but 2 steps around
public boolean [] getUntestedBackgroundBorder2 (
final boolean [] known,
......@@ -851,6 +857,7 @@ public class CLTPass3d{
final AtomicInteger ai = new AtomicInteger(0);
for (int ithread = 0; ithread < threads.length; ithread++) {
threads[ithread] = new Thread() {
@Override
public void run() {
for (int nTile = ai.getAndIncrement(); nTile < num_tiles; nTile = ai.getAndIncrement()) {
if (known[nTile]){
......@@ -868,21 +875,21 @@ public class CLTPass3d{
}
}
};
}
}
ImageDtt.startAndJoin(threads);
return untested_bgnd;
}
public SuperTiles getSuperTiles()
{
return this.superTiles;
}
public SuperTiles setSuperTiles(
double step_near,
double step_far,
......@@ -897,6 +904,15 @@ public class CLTPass3d{
int smplNum, // = 3; // Number after removing worst
double smplRms, // = 0.1; // Maximal RMS of the remaining tiles in a sample
boolean smplWnd, // use window functions for the samples
double max_abs_tilt, // 2.0; // pix per tile
double max_rel_tilt, // 0.2; // (pix / disparity) per tile
double damp_tilt, // 0.001; // Damp tilt to handle insufficient (co-linear)data
double min_tilt_disp, // 4.0; // Disparity switch between filtering modes - near objects use tilts, far - use max disparity
double transition, // 1.0; // Mode transition range (between tilted and maximal disparity)
int far_mode, // 1; // Far objects filtering mode (0 - off, 1 - power of disparity)
double far_power, // 3.0; // Raise disparity to this power before averaging for far objects
int measSel)
{
this.superTiles = new SuperTiles(
......@@ -914,18 +930,35 @@ public class CLTPass3d{
smplNum, // = 3; // Number after removing worst
smplRms, // = 0.1; // Maximal RMS of the remaining tiles in a sample
smplWnd, // final boolean smplWnd, // use window functions for the samples
max_abs_tilt, // 2.0; // Maximal absolute tilt in pixels/tile
max_rel_tilt, // 0.2; // Maximal relative tilt in pixels/tile/disparity
damp_tilt, // 0.001; // Damp tilt to handle insufficient (co-linear)data
min_tilt_disp, // 4.0; // Disparity switch between filtering modes - near objects use tilts, far - use max disparity
transition, // 1.0; // Mode transition range (between tilted and maximal disparity)
far_mode, // 1; // Far objects filtering mode (0 - off, 1 - power of disparity)
far_power, // 1.0; // Raise disparity to this power before averaging for far objects
// true, // boolean null_if_none,
measSel);
return this.superTiles;
}
public double [] showDisparityHistogram(
double [][][][] disparity_strength, // pre-calculated disparity/strength [per super-tile][per-measurement layer][2][tiles] or null
boolean [][] tile_sel, // null or per-measurement layer, per-tile selection. For each layer null - do not use, {} - use all
boolean smplMode, // = true; // Use sample mode (false - regular tile mode)
int smplSide, // = 2; // Sample size (side of a square)
int smplNum, // = 3; // Number after removing worst
double smplRms, // = 0.1; // Maximal RMS of the remaining tiles in a sample
boolean smplWnd, // use window functions for the samples
double max_abs_tilt, // 2.0; // pix per tile
double max_rel_tilt, // 0.2; // (pix / disparity) per tile
double damp_tilt, // 0.001; // Damp tilt to handle insufficient (co-linear)data
double min_tilt_disp, // 4.0; // Disparity switch between filtering modes - near objects use tilts, far - use max disparity
double transition, // 1.0; // Mode transition range (between tilted and maximal disparity)
int far_mode, // 1; // Far objects filtering mode (0 - off, 1 - power of disparity)
double far_power, // 3.0; // Raise disparity to this power before averaging for far objects
int measSel)
{
if (this.superTiles == null){
......@@ -940,6 +973,15 @@ public class CLTPass3d{
smplNum, // = 3; // Number after removing worst
smplRms, // = 0.1; // Maximal RMS of the remaining tiles in a sample
smplWnd, // use window functions for the samples
max_abs_tilt, // 2.0; // Maximal absolute tilt in pixels/tile
max_rel_tilt, // 0.2; // Maximal relative tilt in pixels/tile/disparity
damp_tilt, // 0.001; // Damp tilt to handle insufficient (co-linear)data
min_tilt_disp, // 4.0; // Disparity switch between filtering modes - near objects use tilts, far - use max disparity
transition, // 1.0; // Mode transition range (between tilted and maximal disparity)
far_mode, // 1; // Far objects filtering mode (0 - off, 1 - power of disparity)
far_power, // 1.0; // Raise disparity to this power before averaging for far objects
measSel);
}
......@@ -958,13 +1000,13 @@ public class CLTPass3d{
return rslt;
}
return getBgDispStrength(
this.minBgDisparity,
this.minBgDisparity,
this.minBgFract);
}
public double [][] getBgDispStrength(
final double minBgDisparity,
final double minBgDisparity,
final double minBgFract)
{
if (superTiles == null){
......@@ -972,7 +1014,7 @@ public class CLTPass3d{
}
if ((minBgDisparity != this.minBgDisparity) || (minBgFract != this.minBgFract)){
this.minBgDisparity = minBgDisparity;
this.minBgFract = minBgFract;
this.minBgFract = minBgFract;
superTiles.bgDisparity = null; // per super-tile
superTiles.bgStrength = null; // per super-tile
bgTileDisparity = null; // per tile
......@@ -980,7 +1022,7 @@ public class CLTPass3d{
}
if ((superTiles.bgDisparity == null) || (superTiles.bgStrength == null)){
if (superTiles.getBgDispStrength(
minBgDisparity,
minBgDisparity,
minBgFract) == null) {
superTiles.bgDisparity = null; // per super-tile
superTiles.bgStrength = null; // per super-tile
......@@ -989,7 +1031,7 @@ public class CLTPass3d{
return null; // failed
}
// now lap-combine supertiles, get this.* from superTiles.*
double [][] bgTileDispStrength = superTiles.getBgTileDispStrength();
bgTileDisparity = bgTileDispStrength[0];
bgTileStrength = bgTileDispStrength[1];
......@@ -997,7 +1039,7 @@ public class CLTPass3d{
double [][] rslt = {bgTileDisparity,bgTileStrength};
return rslt;
}
public double [] getBgDisparity(){
return bgTileDisparity;
}
......
src/main/java/EyesisCorrectionParameters.java
View file @ 8991226b
This source diff could not be displayed because it is too large. You can view the blob instead.
src/main/java/Eyesis_Correction.java
View file @ 8991226b
......@@ -572,6 +572,7 @@ private Panel panel1,
addButton("Infinity offset", panelClt3, color_configure);
addButton("Setup CLT Batch parameters", panelClt3, color_configure);
addButton("CLT batch process", panelClt3, color_process);
addButton("CM Test", panelClt3, color_stop);
// addButton("JTabbed", panelClt3, color_stop);
// addButton("Demo", panelClt3, color_process);
......@@ -3752,7 +3753,7 @@ private Panel panel1,
/* ======================================================================== */
} else if (label.equals("Setup CLT parameters")) {
CLT_PARAMETERS.showDialog();
CLT_PARAMETERS.showJDialog();
return;
/* ======================================================================== */
} else if (label.equals("Setup CLT")) {
......@@ -3769,7 +3770,7 @@ private Panel panel1,
} else if (label.equals("Select CLT image")) {
DEBUG_LEVEL=MASTER_DEBUG_LEVEL;
// IJ.showMessage("DCT test 1");
if (!CLT_PARAMETERS.showDialog()) return;
if (!CLT_PARAMETERS.showJDialog()) return;
// process selected image stack
ImagePlus imp_src = WindowManager.getCurrentImage();
if (imp_src==null){
......@@ -3802,7 +3803,7 @@ private Panel panel1,
} else if (label.equals("Select second CLT image")) {
DEBUG_LEVEL=MASTER_DEBUG_LEVEL;
// IJ.showMessage("DCT test 1");
if (!CLT_PARAMETERS.showDialog()) return;
if (!CLT_PARAMETERS.showJDialog()) return;
// process selected image stack
ImagePlus imp_src = WindowManager.getCurrentImage();
if (imp_src==null){
......@@ -3837,7 +3838,7 @@ private Panel panel1,
} else if (label.equals("CLT stack")) {
DEBUG_LEVEL=MASTER_DEBUG_LEVEL;
// IJ.showMessage("DCT test 1");
if (!CLT_PARAMETERS.showDialog()) return;
if (!CLT_PARAMETERS.showJDialog()) return;
// process selected image stack
if (DBG_IMP == null) {
ImagePlus imp_src = WindowManager.getCurrentImage();
......@@ -3937,7 +3938,7 @@ private Panel panel1,
System.out.println("--- Free memory="+runtime.freeMemory()+" (of "+runtime.totalMemory()+")");
// IJ.showMessage("DCT test 1");
if (!CLT_PARAMETERS.showDialog()) return;
if (!CLT_PARAMETERS.showJDialog()) return;
// process selected image stack
if (DBG_IMP == null) {
ImagePlus imp_src = WindowManager.getCurrentImage();
......@@ -4191,7 +4192,7 @@ private Panel panel1,
//==============================================================================
} else if (label.equals("Create CLT kernels")) {
if (!CLT_PARAMETERS.showDialog()) return;
if (!CLT_PARAMETERS.showJDialog()) return;
if (QUAD_CLT == null){
QUAD_CLT = new QuadCLT (
PROPERTIES,
......@@ -4250,7 +4251,7 @@ private Panel panel1,
}
} else if (label.equals("Read CLT kernels")) {
if (!CLT_PARAMETERS.showDialog()) return;
if (!CLT_PARAMETERS.showJDialog()) return;
if (QUAD_CLT == null){
QUAD_CLT = new QuadCLT (
PROPERTIES,
......@@ -5161,6 +5162,9 @@ private Panel panel1,
PROPERTIES);
}
return;
} else if (label.equals("CM Test")) {
cm_test();
return;
//JTabbedTest
// End of buttons code
......@@ -5185,7 +5189,136 @@ private Panel panel1,
return true;
}
public boolean cm_test() {
double hsize_x = 1.5;
double hsize_y = 1.5;
int steps = 20;
double sigma = 0.0;
boolean separable = true; // false;
double pwr = 1.0;
GenericJTabbedDialog gd = new GenericJTabbedDialog("Set CLT parameters",400,300);
gd.addNumericField("Half size X", hsize_x, 6, 8, "pix",
"Correlation maximum half width in disparity direction");
gd.addNumericField("Half size Y", hsize_y, 6, 8, "pix",
"Correlation maximum half width in orthogonal direction");
gd.addNumericField("Number of steps", steps, 0, 6, "",
"Number of steps to subdivide [0,1) half-interval");
gd.addNumericField("Low pass sigma", sigma, 3, 6, "pix",
"Correlation maximum half width in orthogonal direction");
gd.addCheckbox ("X/Y separable", separable);
gd.addNumericField("Value power", pwr, 6, 8, "",
"Raise values to this power before calculating CM");
gd.showDialog();
if (gd.wasCanceled()) return false;
DoubleGaussianBlur gb=new DoubleGaussianBlur();
hsize_x = gd.getNextNumber();
hsize_y = gd.getNextNumber();
steps = (int) gd.getNextNumber();
sigma = gd.getNextNumber();
separable = gd.getNextBoolean();
pwr = gd.getNextNumber();
int size_x = 2*((int) Math.round(hsize_x+ 2*sigma+1)) + 1;
int size_y = 2*((int) Math.round(hsize_y+ 2*sigma+1)) + 1;
System.out.println("size_x="+size_x+", size_y="+size_y+" sigma = "+sigma+" separable "+separable+" pwr=" + pwr);
String [] titles = new String[steps];
double [][] data = new double [steps][size_x*size_y];
for (int i = 0;i<steps; i++) {
double dx = 1.0*i/steps;
titles[i] = IJ.d2s(dx,3);
for (int iy = 0; iy < size_y; iy++) {
double y = (iy - (size_y - 1)/2)/hsize_y;
if ((y >= -1.0) && (y <= 1.0)) {
double ay = separable ? (0.5*(Math.cos(y * Math.PI) + 1.0)):1.0;
for (int ix = 0; ix < size_x; ix++) {
double x = (ix - (size_x - 1)/2 - dx)/hsize_x;
double r = separable? Math.abs(x) : Math.sqrt(x*x+y*y);
// if ((r >= -hsize_x) && (x <= hsize_x)) {
if (r <= 1.0) {
double ax = 0.5*(Math.cos(r * Math.PI) + 1.0);
data[i][iy*size_x+ix] = ax*ay;
}
}
}
}
}
(new showDoubleFloatArrays()) .showArrays(data, size_x, size_y, true, "pre-gauss", titles);
if (sigma > 0.0) {
for (int i = 0; i < steps; i++) {
gb.blurDouble(
data[i],
size_x,
size_y,
sigma,
sigma,
0.01);
}
(new showDoubleFloatArrays()) .showArrays(data, size_x, size_y, true, "blured", titles);
}
double [] cm_x = new double [steps];
for (int i = 0;i<steps; i++) {
double s0=0,sx=0;
for (int iy = 0; iy < size_y; iy++ ) {
for (int ix = 0; ix < size_x; ix++ ) {
double d = Math.pow(data[i][iy*size_y+ix], pwr);
s0+=d;
sx+=ix*d;
}
}
cm_x[i] = sx/s0 - (size_x - 1)/2;
}
for (int i = 0;i <= steps/2; i++) {
double dx = 1.0*i/steps;
System.out.println(String.format("%3d %8.5f %8.5f %8.5f %8.5f %8.5f", i, dx, cm_x[i],cm_x[i]-dx, cm_x[i]/(dx+0.00000001), dx/(cm_x[i]+0.00000001)));
}
return true;
/*
double s0 = 0, sx=0,sy = 0;
for (int y = - iradius ; y <= iradius; y++){
int dataY = icenter[1] +y;
if ((dataY >= 0) && (dataY < data_size)){
int y2 = y*y;
for (int x = - iradius ; x <= iradius; x++){
int dataX = icenter[0] +x;
double r2 = y2 + x * x;
// if ((dataX >= 0) && (dataX < data_size) && (square || ((y2 + x * x) <= ir2))){
if ((dataX >= 0) && (dataX < data_size) && (square || (r2 <= ir2))){
// double w = max_corr_double? (1.0 - r2/ir2):1.0;
// double d = w* data[dataY * data_size + dataX];
double d = data[dataY * data_size + dataX];
s0 += d;
sx += d * dataX;
sy += d * dataY;
}
}
}
}
double [] rslt = {sx / s0, sy / s0};
*
* showDoubleFloatArrays sdfa_instance = new showDoubleFloatArrays(); // just for debugging?
sdfa_instance.showArrays(double_stack, imp_src.getWidth(), imp_src.getHeight(), true, "BEFORE_CLT_PROC", rbg_titles);
*
gb.blurDouble(
results[indexVar],
size,
size,
blurVarianceSigma,
blurVarianceSigma,
0.01);
*/
}
private boolean loadCorrelations(){
String []patterns={".corr-tiff",".tiff",".tif"};
......
src/main/java/GenericJTabbedDialog.java
View file @ 8991226b
......@@ -5,6 +5,7 @@
import java.awt.BorderLayout;
import java.awt.Color;
import java.awt.Component;
import java.awt.FlowLayout;
import java.awt.Font;
import java.awt.GridBagConstraints;
......@@ -109,7 +110,13 @@ public class GenericJTabbedDialog implements ActionListener {
}
if (tooltip != null) {
label.setToolTipText(tooltip);
if (component != null) component.setToolTipText(tooltip);
if (component != null) {
component.setToolTipText(tooltip);
Component [] comps = component.getComponents();
if ((comps != null) && (comps.length >0)) {
((JComponent) comps[0]).setToolTipText(tooltip);
}
}
}
labels.get(labels.size()-1).add(label);
components.get(components.size()-1).add(component);
......@@ -148,6 +155,7 @@ public class GenericJTabbedDialog implements ActionListener {
inp_units.putClientProperty("type", "String");
inp_units.setLayout(new FlowLayout(FlowLayout.LEFT));
addLine(label, inp_units, tooltip);
}
public void addNumericField(String label, double defaultValue, int digits) { // as in IJ
......
src/main/java/ImageDtt.java
View file @ 8991226b
......@@ -67,12 +67,18 @@ public class ImageDtt {
static int DISPARITY_VARIATIONS_INDEX = 11; // index of strength data in disparity map ==6
static int IMG_DIFF0_INDEX = 12; // index of noise- normalized image difference for port 0 in disparity map
static int OVEREXPOSED = 16; // index of overexposed fraction of all pixels
// remove when not needed
static int DBG0_INDEX = 17; // index of dbg0 data (copy of CM)
static int DBG1_INDEX = 18; // index of dbg1 data (poly 1)
static int DBG2_INDEX = 19; // index of dbg2 data (poly 2)
static int DBG3_INDEX = 20; // index of dbg3 data (poly 3)
static String [] DISPARITY_TITLES = {
"int_disp","int_y_disp","cm_disp","cm_y_disp","hor_disp","hor_strength","vert_disp","vert_strength",
"poly_disp", "poly_y_disp", "strength_disp", "vary_disp","diff0","diff1","diff2","diff3","overexp"};
"poly_disp", "poly_y_disp", "strength_disp", "vary_disp","diff0","diff1","diff2","diff3","overexp",
"dbg0","dbg1","dbg2","dbg3"};
static int TCORR_COMBO_RSLT = 0; // normal combined correlation from all selected pairs (mult/sum)
static int TCORR_COMBO_SUM = 1; // sum of channle correlations from all selected pairs
static int TCORR_COMBO_SUM = 1; // sum of channel correlations from all selected pairs
static int TCORR_COMBO_HOR = 2; // combined correlation from 2 horizontal pairs (0,1). Used to detect vertical features
static int TCORR_COMBO_VERT = 3; // combined correlation from 2 vertical pairs (0,1). Used to detect horizontal features
static String [] TCORR_TITLES = {"combo","sum","hor","vert"};
......@@ -1365,6 +1371,7 @@ public class ImageDtt {
public double [][][][][][] clt_aberrations_quad_corr(
final ImageDttParameters imgdtt_params, // Now just extra correlation parameters, later will include, most others
final int macro_scale, // to correlate tile data instead of the pixel data: 1 - pixels, 8 - tiles
final int [][] tile_op, // [tilesY][tilesX] - what to do - 0 - nothing for this tile
final double [][] disparity_array, // [tilesY][tilesX] - individual per-tile expected disparity
......@@ -1539,6 +1546,7 @@ public class ImageDtt {
}
// add optional initialization of debug layers here
if (disparity_map != null){
for (int i = 0; i<disparity_map.length;i++){
if ((i != OVEREXPOSED) || (saturation_imp!= null)){
......@@ -2138,6 +2146,11 @@ public class ImageDtt {
clt_mismatch[3*pair + 2 ][tIndex] = Double.NaN;
}
}
if (disparity_map[DBG0_INDEX] != null) disparity_map[DBG0_INDEX][tIndex] = Double.NaN;
if (disparity_map[DBG1_INDEX] != null) disparity_map[DBG1_INDEX][tIndex] = Double.NaN;
if (disparity_map[DBG2_INDEX] != null) disparity_map[DBG2_INDEX][tIndex] = Double.NaN;
if (disparity_map[DBG3_INDEX] != null) disparity_map[DBG3_INDEX][tIndex] = Double.NaN;
} else {
double [] corr_max_XYi = {icorr_max[0],icorr_max[1]};
disparity_map[DISPARITY_INDEX_INT][tIndex] = transform_size - 1 -corr_max_XYi[0];
......@@ -2149,7 +2162,7 @@ public class ImageDtt {
// disparity_map[DISPARITY_VARIATIONS_INDEX][tIndex] = (rms[1]*tcorr_combo[1][max_index])/(rms[0]*tcorr_combo[0][max_index]); // correlation combo value at the integer maximum
disparity_map[DISPARITY_VARIATIONS_INDEX][tIndex] = (tcorr_combo[TCORR_COMBO_SUM][max_index])/(tcorr_combo[TCORR_COMBO_RSLT][max_index]); // correlation combo value at the integer maximum
// Calculate "center of mass" coordinates
double [] corr_max_XYm = getMaxXYCm( // get fractiona center as a "center of mass" inside circle/square from the integer max
double [] corr_max_XYm = getMaxXYCm( // get fractional center as a "center of mass" inside circle/square from the integer max
tcorr_combo[TCORR_COMBO_RSLT], // [data_size * data_size]
corr_size,
icorr_max, // integer center coordinates (relative to top left)
......@@ -2159,7 +2172,7 @@ public class ImageDtt {
disparity_map[DISPARITY_INDEX_CM][tIndex] = transform_size - 1 -corr_max_XYm[0];
disparity_map[DISPARITY_INDEX_CM+1][tIndex] = transform_size - 1 -corr_max_XYm[1];
// returns x and strength, not x,y
double [] corr_max_XS_hor = getMaxXSOrtho( // get fractiona center as a "center of mass" inside circle/square from the integer max
double [] corr_max_XS_hor = getMaxXSOrtho( // get fractional center as a "center of mass" inside circle/square from the integer max
tcorr_combo[TCORR_COMBO_HOR], // [data_size * data_size]
enh_ortho_scale, // [data_size]
corr_size,
......@@ -2168,7 +2181,7 @@ public class ImageDtt {
(globalDebugLevel > 0) && (tileX == debug_tileX) && (tileY == debug_tileY)); // debugMax);
disparity_map[DISPARITY_INDEX_HOR][tIndex] = transform_size - 1 - corr_max_XS_hor[0];
disparity_map[DISPARITY_INDEX_HOR_STRENGTH][tIndex] = corr_max_XS_hor[1];
double [] corr_max_XS_vert = getMaxXSOrtho( // get fractiona center as a "center of mass" inside circle/square from the integer max
double [] corr_max_XS_vert = getMaxXSOrtho( // get fractional center as a "center of mass" inside circle/square from the integer max
tcorr_combo[TCORR_COMBO_VERT], // [data_size * data_size]
enh_ortho_scale, // [data_size]
corr_size,
......@@ -2180,12 +2193,25 @@ public class ImageDtt {
// Calculate polynomial interpolated maximum coordinates
double [] corr_max_XY = getMaxXYPoly( // get interpolated maximum coordinates using 2-nd degree polynomial
pa,
tcorr_combo[TCORR_COMBO_RSLT], // [data_size * data_size]
tcorr_combo[TCORR_COMBO_RSLT], // [data_size * data_size]
corr_size,
icorr_max, // integer center coordinates (relative to top left)
corr_max_weights_poly, // [(radius+1) * (radius+1)]
max_search_radius_poly, // max_search_radius, for polynomial - always use 1
icorr_max, // integer center coordinates (relative to top left)
corr_max_weights_poly, // [(radius+1) * (radius+1)]
max_search_radius_poly, // max_search_radius, for polynomial - always use 1
imgdtt_params.poly_pwr, // double value_pwr, // raise value to this power (trying to compensate sticking to integer values)
imgdtt_params.poly_value_to_weight, //boolean poly_value_to_weight, // multiply weight by value
debugMax);
//double
if (corr_max_XY != null){
corr_max_XY[0] = transform_size - 1 -corr_max_XY[0];
corr_max_XY[1] = transform_size - 1 -corr_max_XY[1];
} else {
corr_max_XY = new double[2];
corr_max_XY[0] = Double.NaN;
corr_max_XY[1] = Double.NaN;
}
/*
if (corr_max_XY != null){
disparity_map[DISPARITY_INDEX_POLY][tIndex] = transform_size - 1 -corr_max_XY[0];
disparity_map[DISPARITY_INDEX_POLY+1][tIndex] = transform_size - 1 -corr_max_XY[1];
......@@ -2193,6 +2219,42 @@ public class ImageDtt {
disparity_map[DISPARITY_INDEX_POLY][tIndex] = Double.NaN;
disparity_map[DISPARITY_INDEX_POLY+1][tIndex] = Double.NaN;
}
*/
disparity_map[DISPARITY_INDEX_POLY][tIndex] = corr_max_XY[0];
disparity_map[DISPARITY_INDEX_POLY+1][tIndex] = corr_max_XY[1];
// just debug (up to 4 layers)
if (disparity_map[DBG0_INDEX] != null) {
disparity_map[DBG0_INDEX][tIndex] = transform_size - 1 -corr_max_XYm[0];
}
if (disparity_map[DBG2_INDEX] != null) {
disparity_map[DBG2_INDEX][tIndex] = corr_max_XY[0];
}
if (disparity_map[DBG1_INDEX] != null) {
disparity_map[DBG1_INDEX][tIndex] = disparity_map[DBG0_INDEX][tIndex];
if (!Double.isNaN(corr_max_XY[0]) &&
(Math.abs(disparity_map[DISPARITY_INDEX_CM][tIndex] - corr_max_XY[0]) < imgdtt_params.max_poly_diff) &&
(disparity_map[DISPARITY_STRENGTH_INDEX][tIndex] > imgdtt_params.min_poly_strength)) { // debug threshold
disparity_map[DBG1_INDEX][tIndex] = corr_max_XY[0];
disparity_map[DBG3_INDEX][tIndex] = Double.NaN;
} else { // show only "bad" and strong poly
if (disparity_map[DISPARITY_STRENGTH_INDEX][tIndex] > imgdtt_params.min_poly_strength) {
disparity_map[DBG3_INDEX][tIndex] = disparity_map[DBG2_INDEX][tIndex];
} else {
disparity_map[DBG3_INDEX][tIndex] = Double.NaN;
}
}
// if (disparity_map[DBG3_INDEX] != null) {
// disparity_map[DBG3_INDEX][tIndex] = disparity_map[DBG2_INDEX][tIndex] - disparity_map[DBG0_INDEX][tIndex];
// }
}
if (imgdtt_params.mix_corr_poly) {
// apply
disparity_map[DISPARITY_INDEX_CM][tIndex] = disparity_map[DBG1_INDEX][tIndex];
// TODO: add Y for correction !!!!
}
//
if (corr_mode == 0) extra_disparity = disparity_map[DISPARITY_INDEX_INT][tIndex];
else if (corr_mode == 1) extra_disparity = disparity_map[DISPARITY_INDEX_CM][tIndex];
else if (corr_mode == 2) extra_disparity = disparity_map[DISPARITY_INDEX_POLY][tIndex];
......@@ -2912,6 +2974,8 @@ public class ImageDtt {
int [] icenter, // integer center coordinates (relative to top left)
double [] weights, // [(radius+1) * (radius+1)]
int radius,
double value_pwr, // raise value to this power (trying to compensate sticking to integer values)
boolean poly_value_to_weight, // multiply weight by value
boolean debug)
{
// TODO: make sure it is within 1pxx1px square from the integer maximum? If not - return null and use center of mass instead?
......@@ -2935,8 +2999,16 @@ public class ImageDtt {
mdata[indx][0][1] = dataY;
mdata[indx][1] = new double [1];
mdata[indx][1][0] = data[dataY * data_size + dataX];
if (value_pwr != 1.0) {
if (mdata[indx][1][0] > 0) {
mdata[indx][1][0] = Math.pow(mdata[indx][1][0], value_pwr);
} else {
mdata[indx][1][0] = 0.0;
}
}
mdata[indx][2] = new double [1];
mdata[indx][2][0] = weights[ay * (radius + 1) + ax];
if (poly_value_to_weight) mdata[indx][2][0] *= mdata[indx][1][0];
indx++;
}
}
......
src/main/java/MacroCorrelation.java
View file @ 8991226b
......@@ -6,7 +6,7 @@
** Copyright (C) 2017 Elphel, Inc.
**
** -----------------------------------------------------------------------------**
**
**
** MacroCorrelation.java is free software: you can redistribute it and/or modify
** it under the terms of the GNU General Public License as published by
** the Free Software Foundation, either version 3 of the License, or
......@@ -38,13 +38,13 @@ public class MacroCorrelation {
this.tp = tp;
final int pTilesX = tp.getTilesX();
final int pTilesY = tp.getTilesY();
final int tileSize = tp.getTileSize(); //
final int tileSize = tp.getTileSize(); //
final int mTilesX = (pTilesX + tileSize - 1) / tileSize; // clt_aberrations_quad_corr truncates
final int mTilesY = (pTilesY + tileSize - 1) / tileSize;
this.mtp = new TileProcessor(
mTilesX, // int tilesX,
mTilesY, // int tilesY,
tileSize, // int tileSize,
tileSize, // int tileSize,
tp.superTileSize, // int superTileSize,
tp.getMagicScale(), // double scale,
trusted_correlation, // double trustedCorrelation,
......@@ -55,7 +55,7 @@ public class MacroCorrelation {
final CLTPass3d src_scan, // results of the normal correlations (now expecting infinity)
// final double [][][] other_channels, // other channels to correlate, such as average RGB (first index - subcamera, 2-nd - channel, 3-rd - pixel)
EyesisCorrectionParameters.CLTParameters clt_parameters,
GeometryCorrection geometryCorrection,
GeometryCorrection geometryCorrection,
final double macro_disparity_low,
final double macro_disparity_high,
final double macro_disparity_step,
......@@ -64,7 +64,7 @@ public class MacroCorrelation {
double [][][] input_data = CLTMacroSetData( // perform single pass according to prepared tiles operations and disparity
src_scan, // final CLTPass3d src_scan, // results of the normal correlations (now expecting infinity)
null); // final double [][][] other_channels, // other channels to correlate, such as average RGB (first index - subcamera, 2-nd - channel, 3-rd - pixel)
mtp.resetCLTPasses();
for (double mdisp = macro_disparity_low; mdisp < (macro_disparity_high - macro_disparity_step); mdisp +=macro_disparity_step){
final CLTPass3d macro_scan = new CLTPass3d(mtp);
......@@ -72,28 +72,28 @@ public class MacroCorrelation {
CLTMacroSetMeasure( // perform single pass according to prepared tiles operations and disparity
macro_scan, // final CLTPass3d macro_scan, // new, will be filled out
clt_parameters, // EyesisCorrectionParameters.CLTParameters clt_parameters,
geometryCorrection, // GeometryCorrection geometryCorrection,
geometryCorrection, // GeometryCorrection geometryCorrection,
mdisp, // final double macro_disparity,
false, // final boolean show_corr_partial,
false, // final boolean show_corr_combo,
debugLevel); // final int debugLevel)
CLTMacroMeasure( // perform single pass according to prepared tiles operations and disparity
macro_scan, // final CLTPass3d macro_scan, //
macro_scan, // final CLTPass3d macro_scan, //
input_data, // final double [][][] input_data,
clt_parameters, // EyesisCorrectionParameters.CLTParameters clt_parameters,
geometryCorrection, // GeometryCorrection geometryCorrection,
geometryCorrection, // GeometryCorrection geometryCorrection,
""+mdisp, // final String suffix,
false, // final boolean show_corr_partial,
false, // final boolean show_corr_combo,
debugLevel); // final int debugLevel)
mtp.clt_3d_passes.add(macro_scan);
}
return mtp;
}
public double [][][] CLTMacroSetData( // perform single pass according to prepared tiles operations and disparity
final CLTPass3d src_scan, // results of the normal correlations (now expecting infinity)
final double [][][] other_channels // other channels to correlate, such as average RGB (first index - subcamera, 2-nd - channel, 3-rd - pixel)
......@@ -105,14 +105,14 @@ public class MacroCorrelation {
// final int dbg_y = 160;
final int pTilesX = tp.getTilesX();
final int pTilesY = tp.getTilesY();
final int tileSize = tp.getTileSize(); //
final int tileSize = tp.getTileSize(); //
final int mTilesX = (pTilesX + tileSize - 1) / tileSize; // clt_aberrations_quad_corr truncates
final int mTilesY = (pTilesY + tileSize - 1) / tileSize;
final int mTiles = mTilesX * mTilesY;
final int mTiles = mTilesX * mTilesY;
final int num_chn = tmp_input? 3: (1 + ((other_channels == null) ? 0 : (other_channels[0].length)));
final double [][][] input_data = new double [ImageDtt.QUAD][num_chn][mTiles*tileSize*tileSize];
// double [][] tiles_tone = src_scan.getTileRBGA( No, we need individual subcameras
// 4); // int num_layers);
// 4); // int num_layers);
for (int sub_cam =0; sub_cam < input_data.length; sub_cam++){
for (int pty = 0; pty < pTilesY; pty++){
for (int ptx = 0; ptx < pTilesX; ptx++){
......@@ -122,7 +122,7 @@ public class MacroCorrelation {
if (tmp_input) {
input_data[sub_cam][1][mTile]= input_data[sub_cam][0][mTile];
input_data[sub_cam][2][mTile]= input_data[sub_cam][0][mTile];
} else {
} else {
for (int other_chn = 1; other_chn < num_chn; other_chn++){
input_data[sub_cam][other_chn][mTile] = other_channels[sub_cam][other_chn-1][pTile];
}
......@@ -133,13 +133,13 @@ public class MacroCorrelation {
}
return input_data;
}
public CLTPass3d CLTMacroSetMeasure( // perform single pass according to prepared tiles operations and disparity
final CLTPass3d macro_scan, // new, will be filled out
EyesisCorrectionParameters.CLTParameters clt_parameters,
GeometryCorrection geometryCorrection,
GeometryCorrection geometryCorrection,
final double macro_disparity,
final boolean show_corr_partial,
final boolean show_corr_combo,
......@@ -147,10 +147,10 @@ public class MacroCorrelation {
{
final int pTilesX = tp.getTilesX();
final int pTilesY = tp.getTilesY();
final int tileSize = tp.getTileSize(); //
final int tileSize = tp.getTileSize(); //
final int mTilesX = (pTilesX + tileSize - 1) / tileSize; // clt_aberrations_quad_corr truncates
final int mTilesY = (pTilesY + tileSize - 1) / tileSize;
int op = ImageDtt.setImgMask(0, 0xf);
op = ImageDtt.setPairMask(op,0xf);
op = ImageDtt.setForcedDisparity(op,true);
......@@ -170,10 +170,10 @@ public class MacroCorrelation {
}
public CLTPass3d CLTMacroMeasure( // perform single pass according to prepared tiles operations and disparity
final CLTPass3d macro_scan, //
final CLTPass3d macro_scan, //
final double [][][] input_data,
EyesisCorrectionParameters.CLTParameters clt_parameters,
GeometryCorrection geometryCorrection,
GeometryCorrection geometryCorrection,
final String suffix,
final boolean show_corr_partial,
final boolean show_corr_combo,
......@@ -181,7 +181,7 @@ public class MacroCorrelation {
{
int mTilesY = macro_scan.tile_op.length;
int mTilesX = macro_scan.tile_op[0].length;
// undecided, so 2 modes of combining alpha - same as rgb, or use center tile only
if (debugLevel > -1){
int numTiles = 0;
......@@ -222,18 +222,19 @@ public class MacroCorrelation {
// double [][][][] texture_tiles = save_textures ? new double [tilesY][tilesX][][] : null; // ["RGBA".length()][];
ImageDtt image_dtt = new ImageDtt();
image_dtt.clt_aberrations_quad_corr(
clt_parameters.img_dtt, // final ImageDttParameters imgdtt_params, // Now just extra correlation parameters, later will include, most others
8, // final int macro_scale, // to correlate tile data instead of the pixel data: 1 - pixels, 8 - tiles
macro_scan.tile_op, // per-tile operation bit codes
macro_scan.disparity, // clt_parameters.disparity, // final double disparity,
input_data, // final double [][][] imade_data, // first index - number of image in a quad
null, // boolean [][] saturation_imp, // (near) saturated pixels or null
// correlation results - final and partial
// correlation results - final and partial
clt_corr_combo, // [tp.tilesY][tp.tilesX][(2*transform_size-1)*(2*transform_size-1)] // if null - will not calculate
clt_corr_partial, // clt_corr_partial, // [tp.tilesY][tp.tilesX][quad]color][(2*transform_size-1)*(2*transform_size-1)] // if null - will not calculate
null, // [tp.tilesY][tp.tilesX][pair]{dx,dy,weight}[(2*transform_size-1)*(2*transform_size-1)] // transpose unapplied. null - do not calculate
// Use it with disparity_maps[scan_step]? clt_mismatch, // [tp.tilesY][tp.tilesX][pair]{dx,dy,weight}[(2*transform_size-1)*(2*transform_size-1)] // transpose unapplied. null - do not calculate
disparity_map, // [12][tp.tilesY * tp.tilesX]
null, // [tp.tilesY][tp.tilesX]["RGBA".length()][];
null, // [tp.tilesY][tp.tilesX]["RGBA".length()][];
mTilesX * clt_parameters.transform_size, // imp_quad[0].getWidth(), // final int width,
clt_parameters.fat_zero, // add to denominator to modify phase correlation (same units as data1, data2). <0 - pure sum
clt_parameters.corr_sym,
......@@ -241,8 +242,8 @@ public class MacroCorrelation {
clt_parameters.corr_red,
clt_parameters.corr_blue,
clt_parameters.corr_sigma,
clt_parameters.corr_normalize, // normalize correlation results by rms
min_corr_selected, // 0.0001; // minimal correlation value to consider valid
clt_parameters.corr_normalize, // normalize correlation results by rms
min_corr_selected, // 0.0001; // minimal correlation value to consider valid
clt_parameters.max_corr_sigma,// 1.5; // weights of points around global max to find fractional
clt_parameters.max_corr_radius,
clt_parameters.enhortho_width, // 2; // reduce weight of center correlation pixels from center (0 - none, 1 - center, 2 +/-1 from center)
......@@ -262,10 +263,10 @@ public class MacroCorrelation {
clt_parameters.kernel_step,
clt_parameters.transform_size,
clt_parameters.clt_window,
shiftXY, //
shiftXY, //
0.0, // disparity_corr, // final double disparity_corr, // disparity at infinity
null, // (clt_parameters.fcorr_ignore? null: this.fine_corr),
clt_parameters.corr_magic_scale, // still not understood coefficient that reduces reported disparity value. Seems to be around 0.85
clt_parameters.corr_magic_scale, // still not understood coefficient that reduces reported disparity value. Seems to be around 0.85
clt_parameters.shift_x, // final int shiftX, // shift image horizontally (positive - right) - just for testing
clt_parameters.shift_y, // final int shiftY, // shift image vertically (positive - down)
31, // clt_parameters.tileX, // final int debug_tileX,
......@@ -341,11 +342,11 @@ public class MacroCorrelation {
}
return macro_scan;
}
public CLTPass3d refineMacro(
final double [][][] input_data,
EyesisCorrectionParameters.CLTParameters clt_parameters,
GeometryCorrection geometryCorrection,
GeometryCorrection geometryCorrection,
final double trustedCorrelation,
final double disp_far, // limit results to the disparity range, far - start with 1 step above 0 (was valid for all)
final double disp_near,
......@@ -367,18 +368,18 @@ public class MacroCorrelation {
false, // final boolean usePoly, // use polynomial method to find max), valid if useCombo == false
1); // final int debugLevel)
if (refined_macro == null) return null;
CLTMacroMeasure( // perform single pass according to prepared tiles operations and disparity
refined_macro, // final CLTPass3d macro_scan, //
refined_macro, // final CLTPass3d macro_scan, //
input_data, // final double [][][] input_data,
clt_parameters, // EyesisCorrectionParameters.CLTParameters clt_parameters,
geometryCorrection, // GeometryCorrection geometryCorrection,
geometryCorrection, // GeometryCorrection geometryCorrection,
""+mtp.clt_3d_passes, // final String suffix,
false, // final boolean show_corr_partial,
false, // final boolean show_corr_combo,
0); // final int debugLevel)
return refined_macro;
}
public ArrayList <CLTPass3d> prepareMeasurementsFromMacro(
......@@ -397,7 +398,7 @@ public class MacroCorrelation {
final int dbg_x,
final int dbg_y,
final int debugLevel)
{
class DispStrength{
double disparity;
......@@ -410,13 +411,14 @@ public class MacroCorrelation {
double [] arr = {disparity, strength};
return arr;
}
@Override
public String toString(){
return String.format("disparity=%7.3f strength=%7.4f",disparity, strength);
}
}
final int mTilesX = mtp.getTilesX();
final int mTilesY = mtp.getTilesY();
final int mTiles = mTilesX * mTilesY;
final int mTiles = mTilesX * mTilesY;
final ArrayList <CLTPass3d> measurements = new ArrayList <CLTPass3d>();
final TileNeibs tnSurface = new TileNeibs(mtp.getTilesX(), mtp.getTilesY());
final Thread[] threads = ImageDtt.newThreadArray(tp.threadsMax);
......@@ -433,7 +435,7 @@ public class MacroCorrelation {
final double disp_near8 = disp_near/tp.getTileSize(); // here tp, not mtp
final double corr_magic_scale = mtp.getMagicScale();
//mtp.clt_3d_passes
final double [] neib_weights = {
mc_ortho_weight,
mc_diag_weight,
......@@ -447,6 +449,7 @@ public class MacroCorrelation {
final double kexp = (mc_trust_sigma == 0.0) ? 0.0: (0.5/mc_trust_sigma/mc_trust_sigma);
for (int ithread = 0; ithread < threads.length; ithread++) {
threads[ithread] = new Thread() {
@Override
public void run() {
int this_thread = ai_thread.getAndIncrement();
......@@ -462,7 +465,7 @@ public class MacroCorrelation {
for (int dir = 0; dir < neib_weights.length; dir++){ // 8 - center
int mTile = tnSurface.getNeibIndex(mTile0, dir);
if ((mTile >= 0) && (neib_weights[dir] != 0.0)) {
int mty = mTile / mTilesX;
int mty = mTile / mTilesX;
int mtx = mTile % mTilesX;
if (pass.tile_op[mty][mtx] != 0 ) { // current tile has valid data
double mdisp = pass.disparity_map[disparity_index][mTile];
......@@ -516,7 +519,7 @@ public class MacroCorrelation {
macro_ds[mTile0] = new double[ds_list_keep.size()][];
int indx=0;
for (DispStrength ds:ds_list_keep){
macro_ds[mTile0][indx++] = ds.toArray();
macro_ds[mTile0][indx++] = ds.toArray();
}
if (max_meas[this_thread] < ds_list_keep.size()){
max_meas[this_thread] = ds_list_keep.size();
......@@ -544,7 +547,7 @@ public class MacroCorrelation {
if (debugLevel > -1){
System.out.println("prepareMeasurementsFromMacro(): longest="+longest+" total_meas="+total_meas);
}
int op = ImageDtt.setImgMask(0, 0xf);
op = ImageDtt.setPairMask(op,0xf);
op = ImageDtt.setForcedDisparity(op,true);
......@@ -554,22 +557,23 @@ public class MacroCorrelation {
for (int i = 0; i < longest; i++){
measurements.add(new CLTPass3d(tp, 0 )); // mode 0 - initialize tile_op and disparity arrays
}
for (int ithread = 0; ithread < threads.length; ithread++) {
threads[ithread] = new Thread() {
@Override
public void run() {
// int this_thread = ai_thread.getAndIncrement();
int tileSize = tp.getTileSize();
int tilesX = tp.getTilesX();
int tilesY = tp.getTilesY();
for (int mTile = ai.getAndIncrement(); mTile < mTiles; mTile = ai.getAndIncrement()) {
int dl = (mTile == dbg_tile) ? debugLevel : -1;
if (dl > 0){
System.out.println("prepareMeasurementsFromMacro().1 mTile0="+mTile);
}
if (macro_ds[mTile] != null){
int mty = mTile / mTilesX;
int mty = mTile / mTilesX;
int mtx = mTile % mTilesX;
int ty0 = mty * tileSize;
int tx0 = mtx * tileSize;
......@@ -592,6 +596,6 @@ public class MacroCorrelation {
ImageDtt.startAndJoin(threads);
return measurements;
}
}
src/main/java/MeasuredLayers.java
View file @ 8991226b
/**
** MeasuredLayer - per-tile measured disparity/strength pairs,
** multiple layers can be used for 4-disparity and 2 (hor/vert) pairs
** separately
** separately
**
** Copyright (C) 2017 Elphel, Inc.
**
** -----------------------------------------------------------------------------**
**
**
** MeasuredLayer.java is free software: you can redistribute it and/or modify
** it under the terms of the GNU General Public License as published by
** the Free Software Foundation, either version 3 of the License, or
......@@ -87,7 +87,7 @@ public class MeasuredLayers {
this.superTileSize = superTileSize;
this.lapWeight = getLapWeights();
}
/**
* Get number of tiles in the image horizontally
* @return tilesX
......@@ -114,22 +114,22 @@ public class MeasuredLayers {
{
return superTileSize;
}
/**
* Set measured layer
* Set measured layer
* @param num_layer number of the layer to set
* @param disparity array of per-tile disparity values (linescan order),
* NaN deletes the tile
* NaN deletes the tile
* @param strength array of per-tile disparity values (linescan order),
* 0.0 strength is OK - does not delete the tile
* @param selection optional tile selection (or null). If unselected, tile is deleted
* @param selection optional tile selection (or null). If unselected, tile is deleted
*/
public void setLayer (
int num_layer,
double [] disparity,
double [] strength,
boolean [] selection) // may be null
{
{
if (layers[num_layer] == null) {
int llen = disparity.length;
if (layers[num_layer] == null) {
......@@ -153,17 +153,17 @@ public class MeasuredLayers {
}
}
}
/**
* Set disparity values for selected measurement layer
* Set disparity values for selected measurement layer
* @param num_layer number of the layer to set
* @param disparity array of per-tile disparity values (linescan order),
* NaN deletes the tile. New tile set strength = 0.0
* NaN deletes the tile. New tile set strength = 0.0
*/
public void setDisparity (
int num_layer,
double [] disparity)
{
{
if (layers[num_layer] == null) {
int llen = disparity.length;
if (layers[num_layer] == null) {
......@@ -185,14 +185,14 @@ public class MeasuredLayers {
/**
* Set strength values for selected measurement layer. Does not allocate new tiles
* if that element was null
* if that element was null
* @param num_layer number of the layer to set
* @param strength array of per-tile strength values (linescan order)
*/
public void setStrength (
int num_layer,
double [] strength)
{
{
if (layers[num_layer] != null) {
for (int i = 0; i < strength.length; i++){
if (layers[num_layer][i] != null){
......@@ -201,7 +201,7 @@ public class MeasuredLayers {
}
}
}
/**
* Change tile selection for the layer. Can only unselect existing tiles, not add new ones
* @param num_layer number of the layer to set
......@@ -211,19 +211,19 @@ public class MeasuredLayers {
public void setSelection (
int num_layer,
boolean [] selection)
{
{
for (int i = 0; i < selection.length; i++){
if (!selection[i]){
layers[num_layer][i] = null;
}
}
}
/**
* Get total number of the measurement layers in this object
* @return number of layers (some may be uninitialized
*/
public int getNumLayers()
{
if (layers == null){
......@@ -237,7 +237,7 @@ public class MeasuredLayers {
* Get array of disparity values for the selected layer
* @param num_layer number of the layer to read
* @return array of per-tile disparity values (in linescan order),
* Double.NaN for missing tiles
* Double.NaN for missing tiles
*/
public double [] getDisparity(
int num_layer)
......@@ -252,12 +252,12 @@ public class MeasuredLayers {
}
return disparity;
}
/**
* Get array of correlation strength values for the selected layer
* @param num_layer number of the layer to read
* @return array of per-tile strength values (in linescan order),
* 0.0 for missing tiles
* 0.0 for missing tiles
*/
public double [] getStrength(
......@@ -273,7 +273,7 @@ public class MeasuredLayers {
}
return strength;
}
/**
* Get array of existing tiles for the selected layer
* @param num_layer number of the layer to read
......@@ -284,11 +284,11 @@ public class MeasuredLayers {
{
boolean [] selection = new boolean [layers[num_layer].length];
for (int i = 0; i < selection.length; i++){
selection[i] = layers[num_layer][i] != null;
selection[i] = layers[num_layer][i] != null;
}
return selection;
}
/**
* Calculate weights for overlapping supertiles to multiply correlation strengths
* @return square 2-d array of weights 0.0 ... 1.0, each dimension twice the
......@@ -303,10 +303,10 @@ public class MeasuredLayers {
}
for (int i = 0; i < superTileSize; i++){
for (int j = 0; j < superTileSize; j++){
lapWeight[i] [ j] = lapWeight1d[i]*lapWeight1d[j];
lapWeight[i] [ j] = lapWeight1d[i]*lapWeight1d[j];
lapWeight[superTileSize2 - 1 - i][ j] = lapWeight[i][j];
lapWeight[i] [superTileSize2 - 1 - j] = lapWeight[i][j];
lapWeight[superTileSize2 - 1 - i][superTileSize2 - 1 - j] = lapWeight[i][j];
lapWeight[i] [superTileSize2 - 1 - j] = lapWeight[i][j];
lapWeight[superTileSize2 - 1 - i][superTileSize2 - 1 - j] = lapWeight[i][j];
}
}
double s = 0.0;
......@@ -318,7 +318,7 @@ public class MeasuredLayers {
System.out.println("getLapWeights: sum = "+s);
return lapWeight;
}
public double [] getLapWeights1d(){
int indx = 0;
final int superTileSize2 = 2 * superTileSize;
......@@ -330,13 +330,13 @@ public class MeasuredLayers {
}
return weights;
}
/**
* Get window function for tile samples (currently just 3x3) in a line-scan order
* @param smplSide square sample side
* @return [smplSide * smplSide]array of weights, 1.0 in the center
*/
static double [] getSampleWindow(int smplSide, boolean all1){
double [] weights = new double [smplSide * smplSide];
for (int sy = 0; sy < smplSide; sy++){
......@@ -346,9 +346,9 @@ public class MeasuredLayers {
}
return weights;
}
/**
* Get selection for the specific measurement layer and supertile X,Y coordinates
* in the image. Combined with input selection
......@@ -384,7 +384,7 @@ public class MeasuredLayers {
if ((x >= 0) && (x < tilesX)) {
int indx = y * tilesX + x;
int indx_st = dy * st2 + dx;
if (((sel_in == null) || sel_in[indx_st]) &&
if (((sel_in == null) || sel_in[indx_st]) &&
(layers[num_layer][indx] != null) &&
(layers[num_layer][indx].getStrength() >= strength_floor)){
selection[indx_st] = true;
......@@ -398,7 +398,7 @@ public class MeasuredLayers {
if (null_if_none && (num_selected == 0)) return null;
return selection;
}
/**
* Get selection for the specific measurement layer and supertile X,Y coordinates
......@@ -456,12 +456,12 @@ public class MeasuredLayers {
if (null_if_none && (num_selected == 0)) return null;
return selection;
}
/**
* Get selection when disparity/strength is already calculated. Useful when
* disparity/strength are not just measured values, by sampled over an area
* @param disparityStrength array of {disparity, strength} where each is
* a linescan data of the (2 * superTileSize) * (2 * superTileSize)
* a linescan data of the (2 * superTileSize) * (2 * superTileSize)
* @param sel_in optional input selection array or null - use all
* @param null_if_none return null if selection has no tiles enabled
* @return boolean array of per-tile enabled/disabled values in linescan
......@@ -483,17 +483,17 @@ public class MeasuredLayers {
num_selected ++;
}
}
if (null_if_none && (num_selected == 0)) return null;
return selection;
}
/**
* Get selection when disparity/strength is already calculated. Useful when
* disparity/strength are not just measured values, by sampled over an area
* Includes low/high limits for disparity values
* @param disparityStrength array of {disparity, strength} where each is
* a linescan data of the (2 * superTileSize) * (2 * superTileSize)
* a linescan data of the (2 * superTileSize) * (2 * superTileSize)
* @param sel_in optional input selection array or null - use all
* @param disp_far low limit for disparity, Double.NaN - do not check
* @param disp_near high limit for disparity, Double.NaN - do not check
......@@ -517,20 +517,20 @@ public class MeasuredLayers {
((sel_in == null) || (sel_in[i]))){
if ( (Double.isNaN(disp_far) || (disparityStrength[0][i] >= disp_far)) &&
(Double.isNaN(disp_near) || (disparityStrength[0][i] <= disp_near))) {
}
selection[i] = true;
num_selected ++;
}
}
if (null_if_none && (num_selected == 0)) return null;
return selection;
}
/**
* Get number of "true" elements in a boolean array. Null is OK, it results in 0
* @param selected boolean array to count set elements in
......@@ -570,7 +570,7 @@ public class MeasuredLayers {
}
return sw;
}
/**
* Get disparity and correlation strength for the specific measurement layer and
* supertile X,Y coordinates in the image. Combined with input selection
......@@ -659,10 +659,10 @@ public class MeasuredLayers {
return ds;
}
/**
* Get double-size (for overlapping) array of disparities and strengths for the supertile
* Using best (producing lowest disparity variance) subset of neighbor tiles
......@@ -675,8 +675,8 @@ public class MeasuredLayers {
* sample weight
* @param strength_pow raise correlation strength (after subtracting strength_floor) to this power
* to use as a sample weight
* @param smplSide size of the square sample side
* @param smplNum number of averaged samples (should be <= smplSide * smplSide and > 1)
* @param smplSide size of the square sample side
* @param smplNum number of averaged samples (should be <= smplSide * smplSide and > 1)
* @param smplRms maximal square root of variance (in disparity pixels) to accept the result
* @param null_if_none return null if there are no usable tiles in the result
* @param smplWnd multiply samples weights by a window function
......@@ -704,19 +704,19 @@ public class MeasuredLayers {
int st_half = superTileSize/2;
double [][] ds = new double [2][st2*st2];
final int dbg_tile = ((stX == 22) && (stY == 19)) ? (5 + 7*16) : -1;// 50397;
int num_selected = 0;
int smpl_center = smplSide /2;
int st2e = st2 + smplSide;
int smplLen = smplSide*smplSide;
final double [] smpl_weights = getSampleWindow(smplSide, !smplWnd);
double [] disp = new double [st2e * st2e];
double [] weight = new double [st2e * st2e];
double [] disp = new double [st2e * st2e];
double [] weight = new double [st2e * st2e];
int st_halfe = st_half + smpl_center;
double smplVar = smplRms * smplRms; // maximal variance (weighted average of the squared difference from the mean)
if (layers[num_layer] != null) {
for (int dy = 0; dy < st2e; dy ++){
int y = superTileSize * stY -st_halfe + dy;
......@@ -726,7 +726,7 @@ public class MeasuredLayers {
if ((x >= 0) && (x < tilesX)) {
int indx = y * tilesX + x;
int indx_ste = dy * st2e + dx;
if (layers[num_layer][indx] != null){ // apply sel_in later
disp[indx_ste] = layers[num_layer][indx].getDisparity();
double w = layers[num_layer][indx].getStrength() - strength_floor;
......@@ -766,15 +766,15 @@ public class MeasuredLayers {
if (weight[indxe] > 0.0){
int indxs = sy * smplSide + sx;
smpl_sel[indxs] = true;
smpl_d[indxs] = disp[indxe];
smpl_w[indxs] = weight[indxe] * smpl_weights[indxs];
smpl_d[indxs] = disp[indxe];
smpl_w[indxs] = weight[indxe] * smpl_weights[indxs];
sum_wnd += smpl_weights[indxs];
num_in_sample ++;
}
}
}
if (num_in_sample >= smplNum){ // try, remove worst
// calculate
// calculate
double sd=0.0, sd2 = 0.0, sw = 0.0;
for (int i = 0; i < smplLen; i++) if (smpl_sel[i]) {
double dw = smpl_d[i] * smpl_w[i];
......@@ -796,13 +796,13 @@ public class MeasuredLayers {
}
}
if (iworst < 0){
System.out.println("**** this is a BUG in getDisparityStrengthML() ****");
System.out.println("**** this is a BUG1 in getDisparityStrengthML() ****");
break;
}
// remove worst sample
smpl_sel[iworst] = false;
double dw = smpl_d[iworst] * smpl_w[iworst];
sd -= dw;
sd -= dw;
sd2 -= dw * smpl_d[iworst];
sw -= smpl_w[iworst];
sum_wnd -= smpl_weights[iworst];
......@@ -823,14 +823,14 @@ public class MeasuredLayers {
System.out.println("**** this is a BUG in getDisparityStrengthML(), shoud not happen ? ****");
}
}
}
}
}
}
return ds;
}
/**
* Verify that selected points are not all on the same line
* Verify that selected points are not all on the same line
* @param sel 2-d sample selection in linescan order
* @param side square samples side
* @return true if there are enough samples for plane extraction, false otherwise
......@@ -862,7 +862,7 @@ public class MeasuredLayers {
}
/**
* Verify that selected points are not all on the same line, even if the specified one is removed
* Verify that selected points are not all on the same line, even if the specified one is removed
* @param indx index of the point to be removed
* @param sel 2-d sample selection in linescan order
* @param side square samples side
......@@ -882,7 +882,7 @@ public class MeasuredLayers {
sel[indx] = true;
return rslt;
}
// testing - redirecting all existing requests to this one with floating planes
public double[][] getDisparityStrengthMLTilted (
int num_layer,
......@@ -895,28 +895,40 @@ public class MeasuredLayers {
int smplNum, // = 3; // Number after removing worst (should be >1)
double smplRms, // = 0.1; // Maximal RMS of the remaining tiles in a sample
boolean smplWnd, //
double damp_tilt, //
double max_abs_tilt, // 2.0; // pix per tile
double max_rel_tilt, // 0.2; // (pix / disparity) per tile
double damp_tilt, // 0.001; // Damp tilt to handle insufficient (co-linear)data
double min_tilt_disp, // 4.0; // Disparity switch between filtering modes - near objects use tilts, far - use max disparity
double transition, // 1.0; // Mode transition range (between tilted and maximal disparity)
int far_mode, // 1; // Far objects filtering mode (0 - off, 1 - power of disparity)
double far_power, // 3.0; // Raise disparity to this power before averaging for far objects
boolean null_if_none,
int debugLevel)
{
boolean use_new = true; // false;
if (use_new) {
return getDisparityStrengthMLTilted (
num_layer, // int num_layer,
stX, // int stX,
stY, // int stY,
sel_in, // boolean [] sel_in,
null, // double [] tiltXY, // null - free with limit on both absolute (2.0?) and relative (0.2) values
null, // double [] tiltXY, // null - free with limit on both absolute (2.0?) and relative (0.2) values
strength_floor, // double strength_floor,
strength_pow, // double strength_pow,
smplSide, // int smplSide, // = 2; // Sample size (side of a square)
smplNum, // int smplNum, // = 3; // Number after removing worst (should be >1)
smplRms, // double smplRms, // = 0.1; // Maximal RMS of the remaining tiles in a sample
smplWnd, // boolean smplWnd, //
2.0, // double max_abs_tilt, // = 2.0; // pix per tile
0.2, // double max_rel_tilt, // = 0.2; // (pix / disparity) per tile
damp_tilt, // double damp_tilt, //
max_abs_tilt, // double max_abs_tilt, // = 2.0; // pix per tile
max_rel_tilt, // double max_rel_tilt, // = 0.2; // (pix / disparity) per tile
damp_tilt, // 0.001; // Damp tilt to handle insufficient (co-linear)data
min_tilt_disp, // 4.0; // Disparity switch between filtering modes - near objects use tilts, far - use max disparity
transition, // 1.0; // Mode transition range (between tilted and maximal disparity)
far_mode, // 1; // Far objects filtering mode (0 - off, 1 - power of disparity)
far_power, // 1.0; // Raise disparity to this power before averaging for far objects
null_if_none, // boolean null_if_none,
debugLevel); // int debugLevel)
} else {
......@@ -925,7 +937,7 @@ public class MeasuredLayers {
stX, // int stX,
stY, // int stY,
sel_in, // boolean [] sel_in,
// null, // double [] tiltXY, // null - free with limit on both absolute (2.0?) and relative (0.2) values
// null, // double [] tiltXY, // null - free with limit on both absolute (2.0?) and relative (0.2) values
strength_floor, // double strength_floor,
strength_pow, // double strength_pow,
smplSide, // int smplSide, // = 2; // Sample size (side of a square)
......@@ -936,10 +948,15 @@ public class MeasuredLayers {
// 0.2, // double max_rel_tilt, // = 0.2; // (pix / disparity) per tile
null_if_none, // boolean null_if_none,
debugLevel); // int debugLevel)
}
}
// Try two modes of operation: Far tiles (disparity <~4?) use power of disparity, no tilts. Near tiles - current.
// For far tiles power can use closest (lowest disparity) - either power or just census or smth.
// Detect strong background?
public double[][] getDisparityStrengthMLTilted (
int num_layer,
int stX,
......@@ -950,43 +967,62 @@ public class MeasuredLayers {
// to be per-tile of a supertile array
double strength_floor,
double strength_pow,
int smplSide, // = 2; // Sample size (side of a square)
int smplNum, // = 3; // Number after removing worst (should be >1)
double smplRms, // = 0.1; // Maximal RMS of the remaining tiles in a sample
int smplSide, // = 3; // Sample size (side of a square)
int smplNum, // = 5; // Number after removing worst (should be >1)
double smplRms, // = 0.3; // Maximal RMS of the remaining tiles in a sample
boolean smplWnd, //
double max_abs_tilt, // = 2.0; // pix per tile
double max_rel_tilt, // = 0.2; // (pix / disparity) per tile
double damp_tilt, //
double max_abs_tilt, // 2.0; // pix per tile
double max_rel_tilt, // 0.2; // (pix / disparity) per tile
double damp_tilt, // 0.001; // Damp tilt to handle insufficient (co-linear)data
double min_tilt_disp, // 4.0; // Disparity switch between filtering modes - near objects use tilts, far - use max disparity
double transition, // 1.0; // Mode transition range (between tilted and maximal disparity)
int far_mode, // 1; // Far objects filtering mode (0 - off, 1 - power of disparity)
double far_power, // 3.0; // Raise disparity to this power before averaging for far objects
boolean null_if_none,
int debugLevel)
{
if ((layers[num_layer] == null) && null_if_none){
return null;
}
final double [] damping = {damp_tilt, damp_tilt, 0.0}; // 0.0 will be applied to average value, tilt_cost - to both tilts
int st2 = 2 * superTileSize;
int st_half = superTileSize/2;
double [][] ds = new double [2][st2*st2];
final int dbg_tile = ((stX == 22) && (stY == 19)) ? (5 + 7*16) : -1;// 50397;
int num_selected = 0;
int smpl_center = smplSide /2;
double smpl_dcenter = (smplSide -1.0) /2;
int st2e = st2 + smplSide;
int smplLen = smplSide*smplSide;
final double [] smpl_weights = getSampleWindow(smplSide, !smplWnd);
double [] disp = new double [st2e * st2e];
double [] weight = new double [st2e * st2e];
double [] disp = new double [st2e * st2e];
double [] weight = new double [st2e * st2e];
int st_halfe = st_half + smpl_center;
double smplVar = smplRms * smplRms; // maximal variance (weighted average of the squared difference from the mean)
PolynomialApproximation pa = new PolynomialApproximation();
double thresholdLin = 1.0E-20; // threshold ratio of matrix determinant to norm for linear approximation (det too low - fail)
double thresholdQuad = 1.0E-30; // threshold ratio of matrix determinant to norm for quadratic approximation (det too low - fail)
double disp_pwr_far = min_tilt_disp - transition/2.0;
double disp_pwr_near = min_tilt_disp + transition/2.0;
double disp_pwr_near2 = disp_pwr_near + smplRms;
double [] disp_pwr = null;
boolean far_mode_en = (far_mode == 1) || (far_mode == 2);
boolean remove_far_only = (far_mode == 2);
if (far_mode_en) {
disp_pwr = new double [st2e * st2e];
}
int num_far = 0;
boolean [] smpl_far_sel = null;
double [] smpl_pwr_d = null;
double [] smpl_far_d = null;
double [] smpl_far_w = null;
int num_in_sample_far = 0;
if (layers[num_layer] != null) {
for (int dy = 0; dy < st2e; dy ++){
int y = superTileSize * stY -st_halfe + dy;
......@@ -996,16 +1032,20 @@ public class MeasuredLayers {
if ((x >= 0) && (x < tilesX)) {
int indx = y * tilesX + x;
int indx_ste = dy * st2e + dx;
if (layers[num_layer][indx] != null){ // apply sel_in later
disp[indx_ste] = layers[num_layer][indx].getDisparity();
double w = layers[num_layer][indx].getStrength() - strength_floor;
if (w > 0) {
if (strength_pow != 1.0) w = Math.pow(w, strength_pow);
// w *= lapWeight[dy][dx];
disp[indx_ste] = layers[num_layer][indx].getDisparity();
disp[indx_ste] = layers[num_layer][indx].getDisparity(); // same?
weight[indx_ste] = w;
num_selected ++;
if (far_mode_en && (disp[indx_ste] < disp_pwr_near2) && (disp[indx_ste] > 0)) {
disp_pwr[indx_ste] = Math.pow(disp[indx_ste], far_power);
num_far++;
}
}
}
}
......@@ -1029,6 +1069,12 @@ public class MeasuredLayers {
double [] smpl_d = new double [smplLen];
double [] smpl_p = new double [smplLen];
double [] smpl_w = new double [smplLen];
if (far_mode_en ) {
smpl_far_sel = new boolean [smplLen];
smpl_pwr_d = new double [smplLen];
smpl_far_w = new double [smplLen];
num_in_sample_far = 0;
}
for (int sy = 0; sy < smplSide; sy++){
int y = dy + sy; // - smpl_center;
for (int sx = 0; sx < smplSide; sx++){
......@@ -1037,13 +1083,22 @@ public class MeasuredLayers {
if (weight[indxe] > 0.0){
int indxs = sy * smplSide + sx;
smpl_sel[indxs] = true;
smpl_d[indxs] = disp[indxe];
smpl_w[indxs] = weight[indxe] * smpl_weights[indxs];
smpl_d[indxs] = disp[indxe];
smpl_w[indxs] = weight[indxe] * smpl_weights[indxs];
sum_wnd += smpl_weights[indxs];
num_in_sample ++;
if (far_mode_en && (disp_pwr[indxe]>0.0)) {
smpl_far_sel[indxs] = true;
smpl_pwr_d[indxs] = disp_pwr[indxe];
smpl_far_w[indxs] = smpl_w[indxs];
num_in_sample_far++;
}
}
}
}
if (far_mode_en ) {
smpl_far_d = smpl_d.clone();
}
if (num_in_sample >= smplNum){ // try, remove worst
sample_loop:
{
......@@ -1098,21 +1153,21 @@ public class MeasuredLayers {
double max_tilt = Math.min(max_abs_tilt, max_rel_tilt * approx2d[0][2]);
boolean overlimit = (Math.abs(approx2d[0][0]) > max_tilt) || (Math.abs(approx2d[0][1]) > max_tilt);
if (overlimit) {
approx2d[0][0] = Math.min(approx2d[0][0], max_tilt);
approx2d[0][1] = Math.min(approx2d[0][1], max_tilt);
approx2d[0][0] = Math.max(approx2d[0][0], -max_tilt);
approx2d[0][0] = Math.min(approx2d[0][0], max_tilt);
approx2d[0][1] = Math.min(approx2d[0][1], max_tilt);
approx2d[0][0] = Math.max(approx2d[0][0], -max_tilt);
approx2d[0][1] = Math.max(approx2d[0][1], -max_tilt);
}
// subtract tilt from disparity
for (int sy = 0; sy < smplSide; sy++){
for (int sx = 0; sx < smplSide; sx++){
int indxs = sy * smplSide + sx;
if (smpl_sel[indxs]) {
if (smpl_sel[indxs]) {
smpl_p[indxs] = approx2d[0][0] * (sx - smpl_dcenter) + approx2d[0][1] * (sy - smpl_dcenter) + approx2d[0][2];
}
}
}
if (overlimit){ // re-calculate disparity average (in the center)
double sd=0.0;
for (int indxs = 0; indxs < smplLen;indxs++) if (smpl_sel[indxs]) {
......@@ -1136,15 +1191,15 @@ public class MeasuredLayers {
sd2 += dw * smpl_d[indxs];
sw += smpl_w[indxs];
}
// remove worst - it should not make remaining set
// remove worst - it should not make remaining set
if (num_in_sample > smplNum) { // remove worst if it is not the last run where only calculations are needed
// double d_mean = sd/sw;
// double d_mean = sd/sw;
int iworst = -1;
double dworst2 = 0.0;
for (int indxs = 0; indxs < smplLen; indxs++) if (smpl_sel[indxs]) {
// double d2 = (smpl_d[i] - d_mean);
// double d2 = (smpl_d[i] - d_mean);
double d2 = smpl_d[indxs] - smpl_p[indxs];
d2 *=d2;
if (d2 > dworst2) {
......@@ -1166,21 +1221,21 @@ public class MeasuredLayers {
}
// remove worst sample
smpl_sel[iworst] = false;
// double dw = smpl_d[iworst] * smpl_w[iworst];
// sd -= dw;
// sd2 -= dw * smpl_d[iworst];
// sw -= smpl_w[iworst];
// double dw = smpl_d[iworst] * smpl_w[iworst];
// sd -= dw;
// sd2 -= dw * smpl_d[iworst];
// sw -= smpl_w[iworst];
sum_wnd -= smpl_weights[iworst];
num_in_sample --;
} else {
break;
}
} // removing worst tiles, all done,
} // removing worst tiles, all done,
// calculate variance of the remaining set
if (sw > 0.0) {
// sd /= sw;
// sd2 /= sw;
// sd /= sw;
// sd2 /= sw;
double var = sd2/sw; // - sd * sd;
if (var < smplVar) { // good, save in the result array
ds[0][indx] = d_center;
......@@ -1188,7 +1243,7 @@ public class MeasuredLayers {
ds[1][indx] = sw * lapWeight[dy][dx] /sum_wnd; // average weights, multiply by window //** TODO: change
}
}
} else { // fixed tilt
// tilt around center
double [] tiltXY= {0.0,0.0};
......@@ -1199,7 +1254,7 @@ public class MeasuredLayers {
tiltXY = atiltXY[indx];
}
}
if ((tiltXY != null) && (tiltXY[0] != 0.0) && (tiltXY[1] != 0.0)){
for (int sy = 0; sy < smplSide; sy++){
for (int sx = 0; sx < smplSide; sx++){
......@@ -1212,7 +1267,7 @@ public class MeasuredLayers {
}
// calculate
// calculate
double sd=0.0, sd2 = 0.0, sw = 0.0;
for (int i = 0; i < smplLen; i++) if (smpl_sel[i]) {
double dw = smpl_d[i] * smpl_w[i];
......@@ -1232,15 +1287,16 @@ public class MeasuredLayers {
iworst = i;
dworst2 = d2;
}
//remove_far_only
}
if (iworst < 0){
System.out.println("**** this is a BUG in getDisparityStrengthML() ****");
System.out.println("**** this is a BUG2 in getDisparityStrengthML() ****");
break;
}
// remove worst sample
smpl_sel[iworst] = false;
double dw = smpl_d[iworst] * smpl_w[iworst];
sd -= dw;
sd -= dw;
sd2 -= dw * smpl_d[iworst];
sw -= smpl_w[iworst];
sum_wnd -= smpl_weights[iworst];
......@@ -1263,20 +1319,93 @@ public class MeasuredLayers {
}
}
}
}
// now apply far if needed
if (num_in_sample_far > 0) { // calculate small far disparity, then merge with normal one
// remove extra
// smpl_pwr_d - disparity to power
// smpl_far_d - just disparity
if (num_in_sample_far >= smplNum){ // try, remove worst
double sd=0.0, sd2 = 0.0, sw = 0.0;
double sdp =0.0; // , sdp2 = 0.0;
for (int i = 0; i < smplLen; i++) if (smpl_far_sel[i]) {
double dw = smpl_far_d[i] * smpl_far_w[i];
sd += dw;
sd2 += dw * smpl_far_d[i];
sw += smpl_far_w[i];
double dpw = smpl_pwr_d[i] * smpl_far_w[i];
sdp += dpw;
// sdp2 += dpw * smpl_pwr_d[i];
}
// remove worst (before power), update sd2, sd and sw
while ((num_in_sample_far > smplNum) && (sw > 0)){ // try, remove worst
double d_mean = sd/sw;
int iworst = -1;
double dworst2 = 0.0;
for (int i = 0; i < smplLen; i++) if (smpl_far_sel[i]) {
double d2 = (smpl_far_d[i] - d_mean);
d2 *=d2;
if ((d2 > dworst2) && (!remove_far_only ||(smpl_far_d[i] < d_mean))) {
iworst = i;
dworst2 = d2;
}
}
if (iworst < 0){
System.out.println("**** this is a BUG3 in getDisparityStrengthML() ****");
break;
}
// remove worst sample
smpl_far_sel[iworst] = false;
double dw = smpl_far_d[iworst] * smpl_far_w[iworst];
sd -= dw;
sd2 -= dw * smpl_far_d[iworst];
sw -= smpl_far_w[iworst];
sum_wnd -= smpl_weights[iworst];
num_in_sample_far --;
// Remove from the power average too
sdp -= smpl_pwr_d[iworst] * smpl_far_w[iworst];
}
// calculate variance of the remaining set
if (sw > 0.0) {
sd /= sw;
sd2 /= sw;
double var = sd2 - sd * sd;
if (var < smplVar) { // good, save in the result array (here use linear disparity
// here need to combine two filtering modes - "tilted" and "far"
sdp = Math.pow(sdp/sw, 1.0/far_power);
if (sdp < disp_pwr_near) { // otherwise keep tilted mode result
double far_w = sw * lapWeight[dy][dx] /sum_wnd; // average weights, multiply by window //** TODO: change
if (sdp < disp_pwr_far) {
ds[0][indx] = sdp;
ds[1][indx] = far_w;
} else { // interpolate
double k = (sdp - disp_pwr_far) / transition;
ds[0][indx] = (1.0 - k) * sdp + k * ds[0][indx];
ds[1][indx] = (1.0 - k) * far_w + k * ds[1][indx];
}
}
ds[0][indx] = sd;
ds[1][indx] = sw * lapWeight[dy][dx] /sum_wnd; // average weights, multiply by window //** TODO: change
}
} else {
num_in_sample = 0;
System.out.println("**** this is a BUG4 in getDisparityStrengthML(), shoud not happen ? ****");
}
}
}
}
}
}
return ds;
}
public void growSelection(
int grow, // grow tile selection by 1 over non-background tiles 1: 4 directions, 2 - 8 directions, 3 - 8 by 1, 4 by 1 more
boolean [] tiles,
......@@ -1293,7 +1422,7 @@ public class MeasuredLayers {
for (int tileX = 0; tileX < (tilesX - 1); tileX++){
int tindx = tileY * tilesX + tileX;
if ((prohibit == null) || (!prohibit[tindx] && !prohibit[tindx + 1])) {
tiles[tindx + 1] |= src_tiles[tindx];
tiles[tindx + 1] |= src_tiles[tindx];
}
}
......@@ -1325,5 +1454,5 @@ public class MeasuredLayers {
hor = !hor;
}
}
}
src/main/java/QuadCLT.java
View file @ 8991226b
......@@ -3572,7 +3572,7 @@ public class QuadCLT {
showDoubleFloatArrays sdfa_instance = new showDoubleFloatArrays(); // just for debugging?
// may use this.StartTime to report intermediate steps execution times
String name=(String) imp_quad[0].getProperty("name");
String name=this.correctionsParameters.getModelName((String) imp_quad[0].getProperty("name"));
// int channel= Integer.parseInt((String) imp_src.getProperty("channel"));
// int channel= (Integer) imp_quad[0].getProperty("channel");
String path= (String) imp_quad[0].getProperty("path");
......@@ -3666,6 +3666,7 @@ public class QuadCLT {
}
final double disparity_corr = (z_correction == 0) ? 0.0 : geometryCorrection.getDisparityFromZ(1.0/z_correction);
double [][][][][][] clt_data = image_dtt.clt_aberrations_quad_corr(
clt_parameters.img_dtt, // final ImageDttParameters imgdtt_params, // Now just extra correlation parameters, later will include, most others
1, // final int macro_scale, // to correlate tile data instead of the pixel data: 1 - pixels, 8 - tiles
tile_op, // per-tile operation bit codes
disparity_array, // final double disparity,
......@@ -4740,6 +4741,7 @@ public class QuadCLT {
final double disparity_corr = (z_correction == 0) ? 0.0 : geometryCorrection.getDisparityFromZ(1.0/z_correction);
image_dtt.clt_aberrations_quad_corr(
clt_parameters.img_dtt, // final ImageDttParameters imgdtt_params, // Now just extra correlation parameters, later will include, most others
1, // final int macro_scale, // to correlate tile data instead of the pixel data: 1 - pixels, 8 - tiles
tile_op, // per-tile operation bit codes
disparity_array, // clt_parameters.disparity, // final double disparity,
......@@ -5632,13 +5634,13 @@ public class QuadCLT {
debugLevel);
tp.clt_3d_passes.add(bgnd_data);
// if (show_init_refine)
if (debugLevel > -1) {
if ((debugLevel > -2) && clt_parameters.show_first_bg) {
tp.showScan(
tp.clt_3d_passes.get(0), // CLTPass3d scan,
"bgnd_data-"+tp.clt_3d_passes.size());
}
//TODO: Move away form here?
//TODO: Move away from here?
ImagePlus imp_bgnd = getBackgroundImage(
clt_parameters,
colorProcParameters,
......@@ -5827,7 +5829,8 @@ public class QuadCLT {
tp.clt_3d_passes.add(refined);
/// if (debugLevel > 1)
if (debugLevel > 0)
// if (debugLevel > 0)
if ((debugLevel > -2) && clt_parameters.show_first_bg)
tp.showScan(
tp.clt_3d_passes.get(refine_pass), // CLTPass3d scan,
"before_makeUnique-"+refine_pass);
......@@ -5973,8 +5976,9 @@ public class QuadCLT {
threadsMax, // maximal number of threads to launch
updateStatus,
debugLevel);
if (debugLevel > -1){
System.out.println("CLTMeasure("+refine_pass+")");
// if (debugLevel > -1){
if (debugLevel > -2){
System.out.println("?.CLTMeasure("+refine_pass+")");
}
if (show_init_refine) tp.showScan(
tp.clt_3d_passes.get(refine_pass), // CLTPass3d scan,
......@@ -7041,7 +7045,7 @@ public class QuadCLT {
"after_pass3-"+(next_pass-1)); //String title)
}
String x3d_path= correctionsParameters.selectX3dDirectory( // for x3d and obj
this.image_name, // quad timestamp. Will be ignored if correctionsParameters.use_x3d_subdirs is false
correctionsParameters.getModelName(this.image_name), // quad timestamp. Will be ignored if correctionsParameters.use_x3d_subdirs is false
correctionsParameters.x3dModelVersion,
true, // smart,
true); //newAllowed, // save
......@@ -7058,7 +7062,7 @@ public class QuadCLT {
try {
wfOutput = new WavefrontExport(
x3d_path,
this.image_name,
correctionsParameters.getModelName(this.image_name),
clt_parameters,
correctionsParameters,
geometryCorrection,
......@@ -7117,7 +7121,7 @@ public class QuadCLT {
clt_parameters,
colorProcParameters,
rgbParameters,
this.image_name+"-img_infinity", // +scanIndex,
correctionsParameters.getModelName(this.image_name)+"-img_infinity", // +scanIndex,
bgndIndex,
threadsMax, // maximal number of threads to launch
updateStatus,
......@@ -7198,7 +7202,7 @@ public class QuadCLT {
clt_parameters,
colorProcParameters,
rgbParameters,
this.image_name+"-img"+scanIndex,
correctionsParameters.getModelName(this.image_name)+"-img"+scanIndex,
scanIndex,
threadsMax, // maximal number of threads to launch
updateStatus,
......@@ -7275,9 +7279,9 @@ public class QuadCLT {
if ((x3d_path != null) && (x3dOutput != null)){
// x3d_path+=Prefs.getFileSeparator()+this.image_name+".x3d";
// x3d_path+=Prefs.getFileSeparator()+correctionsParameters.getModelName(this.image_name)+".x3d";
// x3dOutput.generateX3D(x3d_path);
x3dOutput.generateX3D(x3d_path+Prefs.getFileSeparator()+this.image_name+".x3d");
x3dOutput.generateX3D(x3d_path+Prefs.getFileSeparator()+correctionsParameters.getModelName(this.image_name)+".x3d");
}
if (wfOutput != null){
wfOutput.close();
......@@ -7562,7 +7566,7 @@ public class QuadCLT {
debugLevel);
String path= correctionsParameters.selectX3dDirectory(
//TODO: Which one to use - name or this.image_name ?
this.image_name, // quad timestamp. Will be ignored if correctionsParameters.use_x3d_subdirs is false
correctionsParameters.getModelName(this.image_name), // quad timestamp. Will be ignored if correctionsParameters.use_x3d_subdirs is false
correctionsParameters.x3dModelVersion,
// name, // quad timestamp. Will be ignored if correctionsParameters.use_x3d_subdirs is false
true, // smart,
......@@ -7711,7 +7715,7 @@ public class QuadCLT {
String path= correctionsParameters.selectX3dDirectory(
//TODO: Which one to use - name or this.image_name ?
this.image_name, // quad timestamp. Will be ignored if correctionsParameters.use_x3d_subdirs is false
correctionsParameters.getModelName(this.image_name), // quad timestamp. Will be ignored if correctionsParameters.use_x3d_subdirs is false
correctionsParameters.x3dModelVersion,
// name, // quad timestamp. Will be ignored if correctionsParameters.use_x3d_subdirs is false
true, // smart,
......@@ -7841,6 +7845,7 @@ public class QuadCLT {
final double disparity_corr = (z_correction == 0) ? 0.0 : geometryCorrection.getDisparityFromZ(1.0/z_correction);
image_dtt.clt_aberrations_quad_corr(
clt_parameters.img_dtt, // final ImageDttParameters imgdtt_params, // Now just extra correlation parameters, later will include, most others
1, // final int macro_scale, // to correlate tile data instead of the pixel data: 1 - pixels, 8 - tiles
tile_op, // per-tile operation bit codes
disparity_array, // clt_parameters.disparity, // final double disparity,
......@@ -8054,6 +8059,7 @@ public class QuadCLT {
final double disparity_corr = (z_correction == 0) ? 0.0 : geometryCorrection.getDisparityFromZ(1.0/z_correction);
image_dtt.clt_aberrations_quad_corr(
clt_parameters.img_dtt, // final ImageDttParameters imgdtt_params, // Now just extra correlation parameters, later will include, most others
1, // final int macro_scale, // to correlate tile data instead of the pixel data: 1 - pixels, 8 - tiles
tile_op, // per-tile operation bit codes
disparity_array, // clt_parameters.disparity, // final double disparity,
......
src/main/java/SuperTiles.java
View file @ 8991226b
This source diff could not be displayed because it is too large. You can view the blob instead.
src/main/java/TilePlanes.java
View file @ 8991226b
This source diff could not be displayed because it is too large. You can view the blob instead.
src/main/java/TileProcessor.java
View file @ 8991226b
......@@ -3518,7 +3518,7 @@ public class TileProcessor {
final boolean show_scan = show_filter_scan || (debugLevel > 1);
showDoubleFloatArrays sdfa_instance = null;
if ((debugLevel > -2) && ((debugLevel > -1) || show_scan)) sdfa_instance = new showDoubleFloatArrays(); // just for debugging?
if (debugLevel > 0){
if (debugLevel > -2){
System.out.println("FilterScan(,,"+disparity_far+", " +disparity_near+", "+ sure_smth);
}
final int tlen = tilesY * tilesX;
......@@ -3747,7 +3747,8 @@ public class TileProcessor {
return these_tiles;
}
// Next runs before filter, maybe should be after or combined otherwise (i.e filter strengths, but keep original disparities. Or use disparity
// to some power when averaging here)
public int [] combineOrthoDisparity(
final CLTPass3d scan, // scan data
final boolean or_hor, // true; // Apply ortho correction to horizontal correlation (vertical features)
......@@ -3760,6 +3761,8 @@ public class TileProcessor {
final double or_threshold, // 1.5; // Minimal scaled offsetg ortho strength to normal strength needed for replacement
final double or_absHor, // 0.15; // Minimal horizontal absolute scaled offset ortho strength needed for replacement
final double or_absVert, // 0.19; // Minimal vertical absolute scaled offset ortho strength needed for replacement
final double or_maxDisp, // 5.0; // Maximal disparity to apply ortho correction
final boolean show_ortho, // show replacement of disparity/strength by those of hor/vert
final int debugLevel)
{
double [] disparity = scan.getDisparity(0); // calculated, to be modified
......@@ -3769,6 +3772,31 @@ public class TileProcessor {
double [] strength_hor = scan.getHorStrength(); // .clone();
double [] strength_vert = scan.getVertStrength(); // .clone();
int [] replaced = new int[strength.length];
double [][] dbg_img = null;
String [] dbg_titles = {"disparity", // 0
"orig_disparity", // 1
"hor_disparity", // 2
"hor_disparity_mod", // 3
"vert_disparity", // 4
"vert_disparity_mod",// 5
"strength", // 6
"orig_strength", // 7
"hor_strength", // 8
"hor_strength_mod", // 9
"vert_strength", // 10
"vert_strength_mod", // 11
"replaced"}; // 12
if (show_ortho) {
dbg_img=new double [dbg_titles.length][];
dbg_img[1] = disparity.clone();
dbg_img[2] = disparity_hor.clone();
dbg_img[4] = disparity_vert.clone();
dbg_img[7] = strength.clone();
dbg_img[8] = strength_hor.clone();
dbg_img[10] = strength_vert.clone();
}
if (or_hor){
for (int i = 0; i < strength_hor.length; i++){
strength_hor[i] *= or_scale;
......@@ -3780,6 +3808,11 @@ public class TileProcessor {
or_sharp, // double k, // sharpen in orthogonal direction with (-k,2*k-1,-k). 0 - no sharpening
or_offset, // double offset, // subtract from strength, limit by 0.0
false); // boolean vert) // true - sharpen vertically, blur horizontally. False - sharpen horizontally, blur vertically
if (show_ortho) {
dbg_img[3] = disparity_hor.clone();
dbg_img[9] = strength_hor.clone();
}
}
if (or_vert){
for (int i = 0; i < strength_vert.length; i++){
......@@ -3792,12 +3825,16 @@ public class TileProcessor {
or_sharp, // double k, // sharpen in orthogonal direction with (-k,2*k-1,-k). 0 - no sharpening
or_offset, // double offset, // subtract from strength, limit by 0.0
true); // boolean vert) // true - sharpen vertically, blur horizontally. False - sharpen horizontally, blur vertically
if (show_ortho) {
dbg_img[5] = disparity_vert.clone();
dbg_img[11] = strength_vert.clone();
}
}
double ko = (or_threshold - 1) * or_offset;
double ao = (or_asym - 1) * or_offset;
if (or_hor){
for (int i = 0; i < strength_hor.length; i++){
if (
if ( (disparity_hor[i] < or_maxDisp) &&
(strength_hor[i] > or_absHor) &&
(strength_hor[i] > or_threshold * strength[i] - ko) &&
(!or_vert || (strength_hor[i] > or_asym * strength_vert[i] - ao))){
......@@ -3809,7 +3846,7 @@ public class TileProcessor {
}
if (or_vert){
for (int i = 0; i < strength_vert.length; i++){
if (
if ( (disparity_vert[i] < or_maxDisp) &&
(strength_vert[i] > or_absVert) &&
(strength_vert[i] > or_threshold * strength[i] - ko) &&
(!or_hor || (strength_vert[i] > or_asym * strength_hor[i] - ao))){
......@@ -3819,6 +3856,15 @@ public class TileProcessor {
}
}
}
if (show_ortho) {
dbg_img[0] = disparity.clone();
dbg_img[6] = strength.clone();
dbg_img[12] = new double [replaced.length];
for (int i = 0; i < replaced.length; i++) {
dbg_img[12][i] = replaced[i];
}
(new showDoubleFloatArrays()).showArrays(dbg_img, tilesX, tilesY, true, "ortho_internal",dbg_titles);
}
return replaced;
}
......@@ -4192,6 +4238,8 @@ public class TileProcessor {
clt_parameters.or_threshold, // 1.5; // Minimal scaled offsetg ortho strength to normal strength needed for replacement
clt_parameters.or_absHor, // 0.15; // Minimal horizontal absolute scaled offset ortho strength needed for replacement
clt_parameters.or_absVert, // 0.19; // Minimal vertical absolute scaled offset ortho strength needed for replacement
clt_parameters.or_maxDisp, // 5.0; // Maximal disparity to apply ortho correction
show_ortho, // show replacement of disparity/strength by those of hor/vert
debugLevel);
if (clt_parameters.poles_fix) {
......@@ -4311,6 +4359,13 @@ public class TileProcessor {
clt_parameters.stSmplNum, // Number after removing worst
clt_parameters.stSmplRms, // Maximal RMS of the remaining tiles in a sample
clt_parameters.stSmplWnd, // boolean smplWnd, // use window functions for the samples
clt_parameters.fs_max_abs_tilt, // 2.0; // Maximal absolute tilt in pixels/tile
clt_parameters.fs_max_rel_tilt, // 0.2; // Maximal relative tilt in pixels/tile/disparity
clt_parameters.fs_damp_tilt, // 0.001; // Damp tilt to handle insufficient (co-linear)data
clt_parameters.fs_min_tilt_disp, // 4.0; // Disparity switch between filtering modes - near objects use tilts, far - use max disparity
clt_parameters.fs_transition, // 1.0; // Mode transition range (between tilted and maximal disparity)
clt_parameters.fs_far_mode, // 1; // Far objects filtering mode (0 - off, 1 - power of disparity)
clt_parameters.fs_far_power, // 1.0; // Raise disparity to this power before averaging for far objects
clt_parameters.stMeasSel); // bitmask of the selected measurements for supertiles : +1 - combo, +2 - quad +4 - hor +8 - vert
dbg_hist[0] = scan_prev.getSuperTiles().showDisparityHistogram();
......@@ -4328,6 +4383,13 @@ public class TileProcessor {
clt_parameters.stSmplNum, // Number after removing worst
clt_parameters.stSmplRms, // Maximal RMS of the remaining tiles in a sample
clt_parameters.stSmplWnd, // boolean smplWnd, // use window functions for the samples
clt_parameters.fs_max_abs_tilt, // 2.0; // Maximal absolute tilt in pixels/tile
clt_parameters.fs_max_rel_tilt, // 0.2; // Maximal relative tilt in pixels/tile/disparity
clt_parameters.fs_damp_tilt, // 0.001; // Damp tilt to handle insufficient (co-linear)data
clt_parameters.fs_min_tilt_disp, // 4.0; // Disparity switch between filtering modes - near objects use tilts, far - use max disparity
clt_parameters.fs_transition, // 1.0; // Mode transition range (between tilted and maximal disparity)
clt_parameters.fs_far_mode, // 1; // Far objects filtering mode (0 - off, 1 - power of disparity)
clt_parameters.fs_far_power, // 1.0; // Raise disparity to this power before averaging for far objects
clt_parameters.stMeasSel); // bitmask of the selected measurements for supertiles : +1 - combo, +2 - quad +4 - hor +8 - vert
dbg_hist[1] = scan_prev.getSuperTiles().showDisparityHistogram();
......@@ -4457,7 +4519,7 @@ public class TileProcessor {
for (int i = 0; i < masked_filtered.length; i++){
if (!grown[i]) masked_filtered[i] = Double.NaN;
}
if (show_super){
if (show_super && false){ // something is broken, java.lang.NullPointerException at TileProcessor.refinePassSetup(TileProcessor.java:4488)
String [] dbg_disp_tiltes={"masked", "filtered", "disp_combo", "disparity","st_disparity", "strength",
"st_strength","outlayers","these","border","border_tiles"}; // ,"before","after","after1","after2","after3","neib"};
double [][] dbg_disp = new double [dbg_disp_tiltes.length][];
......@@ -5083,7 +5145,7 @@ public class TileProcessor {
// if (use_supertiles || show_st) {
String [] dbg_st_titles = {"raw", "sampled", "blurred"+clt_parameters.stSigma,"max-min-max"};
double [][] dbg_hist = new double[dbg_st_titles.length][];
if (show_st) { // otherwise only blured version is needed
if (show_st) { // otherwise only blurred version is needed
scan_prev.setSuperTiles(
clt_parameters.stStepNear, // double step_disparity,
clt_parameters.stStepFar, // double step_near,
......@@ -5098,6 +5160,13 @@ public class TileProcessor {
clt_parameters.stSmplNum, // Number after removing worst
clt_parameters.stSmplRms, // Maximal RMS of the remaining tiles in a sample
clt_parameters.stSmplWnd, // boolean smplWnd, // use window functions for the samples
clt_parameters.fs_max_abs_tilt, // 2.0; // Maximal absolute tilt in pixels/tile
clt_parameters.fs_max_rel_tilt, // 0.2; // Maximal relative tilt in pixels/tile/disparity
clt_parameters.fs_damp_tilt, // 0.001; // Damp tilt to handle insufficient (co-linear)data
clt_parameters.fs_min_tilt_disp, // 4.0; // Disparity switch between filtering modes - near objects use tilts, far - use max disparity
clt_parameters.fs_transition, // 1.0; // Mode transition range (between tilted and maximal disparity)
clt_parameters.fs_far_mode, // 1; // Far objects filtering mode (0 - off, 1 - power of disparity)
clt_parameters.fs_far_power, // 1.0; // Raise disparity to this power before averaging for far objects
clt_parameters.stMeasSel); // bitmask of the selected measurements for supertiles : +1 - combo, +2 - quad +4 - hor +8 - vert
dbg_hist[0] = scan_prev.getSuperTiles().showDisparityHistogram();
scan_prev.setSuperTiles(
......@@ -5114,6 +5183,13 @@ public class TileProcessor {
clt_parameters.stSmplNum, // Number after removing worst
clt_parameters.stSmplRms, // Maximal RMS of the remaining tiles in a sample
clt_parameters.stSmplWnd, // boolean smplWnd, // use window functions for the samples
clt_parameters.fs_max_abs_tilt, // 2.0; // Maximal absolute tilt in pixels/tile
clt_parameters.fs_max_rel_tilt, // 0.2; // Maximal relative tilt in pixels/tile/disparity
clt_parameters.fs_damp_tilt, // 0.001; // Damp tilt to handle insufficient (co-linear)data
clt_parameters.fs_min_tilt_disp, // 4.0; // Disparity switch between filtering modes - near objects use tilts, far - use max disparity
clt_parameters.fs_transition, // 1.0; // Mode transition range (between tilted and maximal disparity)
clt_parameters.fs_far_mode, // 1; // Far objects filtering mode (0 - off, 1 - power of disparity)
clt_parameters.fs_far_power, // 1.0; // Raise disparity to this power before averaging for far objects
clt_parameters.stMeasSel); // bitmask of the selected measurements for supertiles : +1 - combo, +2 - quad +4 - hor +8 - vert
dbg_hist[1] = scan_prev.getSuperTiles().showDisparityHistogram();
}
......@@ -5133,6 +5209,13 @@ public class TileProcessor {
clt_parameters.stSmplNum, // Number after removing worst
clt_parameters.stSmplRms, // Maximal RMS of the remaining tiles in a sample
clt_parameters.stSmplWnd, // boolean smplWnd, // use window functions for the samples
clt_parameters.fs_max_abs_tilt, // 2.0; // Maximal absolute tilt in pixels/tile
clt_parameters.fs_max_rel_tilt, // 0.2; // Maximal relative tilt in pixels/tile/disparity
clt_parameters.fs_damp_tilt, // 0.001; // Damp tilt to handle insufficient (co-linear)data
clt_parameters.fs_min_tilt_disp, // 4.0; // Disparity switch between filtering modes - near objects use tilts, far - use max disparity
clt_parameters.fs_transition, // 1.0; // Mode transition range (between tilted and maximal disparity)
clt_parameters.fs_far_mode, // 1; // Far objects filtering mode (0 - off, 1 - power of disparity)
clt_parameters.fs_far_power, // 1.0; // Raise disparity to this power before averaging for far objects
clt_parameters.stMeasSel); // bitmask of the selected measurements for supertiles : +1 - combo, +2 - quad +4 - hor +8 - vert
if (show_st) { // otherwise only blured version is needed
dbg_hist[2] = scan_prev.getSuperTiles().showDisparityHistogram();
......@@ -5162,6 +5245,13 @@ public class TileProcessor {
clt_parameters.stSmplNum, // Number after removing worst
clt_parameters.stSmplRms, // Maximal RMS of the remaining tiles in a sample
clt_parameters.stSmplWnd, // boolean smplWnd, // use window functions for the samples
clt_parameters.fs_max_abs_tilt, // 2.0; // Maximal absolute tilt in pixels/tile
clt_parameters.fs_max_rel_tilt, // 0.2; // Maximal relative tilt in pixels/tile/disparity
clt_parameters.fs_damp_tilt, // 0.001; // Damp tilt to handle insufficient (co-linear)data
clt_parameters.fs_min_tilt_disp, // 4.0; // Disparity switch between filtering modes - near objects use tilts, far - use max disparity
clt_parameters.fs_transition, // 1.0; // Mode transition range (between tilted and maximal disparity)
clt_parameters.fs_far_mode, // 1; // Far objects filtering mode (0 - off, 1 - power of disparity)
clt_parameters.fs_far_power, // 1.0; // Raise disparity to this power before averaging for far objects
clt_parameters.stMeasSel); // bitmask of the selected measurements for supertiles : +1 - combo, +2 - quad +4 - hor +8 - vert
}
......@@ -5187,6 +5277,14 @@ public class TileProcessor {
clt_parameters.stSmplRms , // final double smplRms, // = 0.1; // Maximal RMS of the remaining tiles in a sample
clt_parameters.stSmplWnd, // boolean smplWnd, // use window functions for the samples
clt_parameters.fs_max_abs_tilt, // 2.0; // Maximal absolute tilt in pixels/tile
clt_parameters.fs_max_rel_tilt, // 0.2; // Maximal relative tilt in pixels/tile/disparity
clt_parameters.fs_damp_tilt, // 0.001; // Damp tilt to handle insufficient (co-linear)data
clt_parameters.fs_min_tilt_disp, // 4.0; // Disparity switch between filtering modes - near objects use tilts, far - use max disparity
clt_parameters.fs_transition, // 1.0; // Mode transition range (between tilted and maximal disparity)
clt_parameters.fs_far_mode, // 1; // Far objects filtering mode (0 - off, 1 - power of disparity)
clt_parameters.fs_far_power, // 1.0; // Raise disparity to this power before averaging for far objects
clt_parameters.plBlurBinHor, // final double bin_blur_hor, // Blur disparity histograms for horizontal clusters by this sigma (in bins)
clt_parameters.plBlurBinVert, // final double bin_blur_vert, // Blur disparity histograms for constant disparity clusters by this sigma (in bins)
clt_parameters.plMaxDiffHor, // final double max_diff_hor, // maximal disparity difference (to assign to a cluster (of Double.NaN) at first run for horizontal planes
......@@ -5261,6 +5359,14 @@ public class TileProcessor {
clt_parameters.stSmplRms, // final double smplRms, // = 0.1; // Maximal RMS of the remaining tiles in a sample
clt_parameters.stSmplWnd, // final boolean smplWnd, // use window functions for the samples
clt_parameters.fs_max_abs_tilt, // 2.0; // Maximal absolute tilt in pixels/tile
clt_parameters.fs_max_rel_tilt, // 0.2; // Maximal relative tilt in pixels/tile/disparity
clt_parameters.fs_damp_tilt, // 0.001; // Damp tilt to handle insufficient (co-linear)data
clt_parameters.fs_min_tilt_disp, // 4.0; // Disparity switch between filtering modes - near objects use tilts, far - use max disparity
clt_parameters.fs_transition, // 1.0; // Mode transition range (between tilted and maximal disparity)
clt_parameters.fs_far_mode, // 1; // Far objects filtering mode (0 - off, 1 - power of disparity)
clt_parameters.fs_far_power, // 1.0; // Raise disparity to this power before averaging for far objects
clt_parameters.plDiscrTolerance, // final double plDiscrTolerance, // = 0.4; // Maximal disparity difference from the plane to consider tile
clt_parameters.plDiscrDispRange, // final double plDiscrDispRange, // = 0.6; // Parallel move known planes around original know value for the best overall fit
clt_parameters.plDiscrSteps, // final int plDiscrSteps, // = 3; // Number of steps (each direction) for each plane to search for the best fit (0 - single, 1 - 1 each side)
......@@ -5375,6 +5481,15 @@ public class TileProcessor {
clt_parameters.stSmplNum , // final int smplNum, // = 3; // Number after removing worst
clt_parameters.stSmplRms , // final double smplRms, // = 0.1; // Maximal RMS of the remaining tiles in a sample
clt_parameters.stSmplWnd, // boolean smplWnd, // use window functions for the samples
clt_parameters.fs_max_abs_tilt, // 2.0; // Maximal absolute tilt in pixels/tile
clt_parameters.fs_max_rel_tilt, // 0.2; // Maximal relative tilt in pixels/tile/disparity
clt_parameters.fs_damp_tilt, // 0.001; // Damp tilt to handle insufficient (co-linear)data
clt_parameters.fs_min_tilt_disp, // 4.0; // Disparity switch between filtering modes - near objects use tilts, far - use max disparity
clt_parameters.fs_transition, // 1.0; // Mode transition range (between tilted and maximal disparity)
clt_parameters.fs_far_mode, // 1; // Far objects filtering mode (0 - off, 1 - power of disparity)
clt_parameters.fs_far_power, // 1.0; // Raise disparity to this power before averaging for far objects
debugLevel, // 1, // final int debugLevel)
clt_parameters.tileX,
clt_parameters.tileY);
......@@ -5967,6 +6082,9 @@ public class TileProcessor {
clt_parameters.or_threshold, // 1.5; // Minimal scaled offsetg ortho strength to normal strength needed for replacement
clt_parameters.or_absHor, // 0.15; // Minimal horizontal absolute scaled offset ortho strength needed for replacement
clt_parameters.or_absVert, // 0.19; // Minimal vertical absolute scaled offset ortho strength needed for replacement
clt_parameters.or_maxDisp, // 5.0; // Maximal disparity to apply ortho correction
clt_parameters.show_ortho_combine, // show replacement of disparity/strength by those of hor/vert
debugLevelInner);
if (clt_parameters.poles_fix) {
......@@ -6026,7 +6144,7 @@ public class TileProcessor {
// final int threadsMax, // maximal number of threads to launch
// final boolean updateStatus,
batch_mode ? -5: 2); //debugLevel);
} else {
} else { //!ortho_old
these_tiles= combineHorVertDisparity_old(
scan_prev, // final CLTPass3d scan,
scan_bg.selected, // clt_3d_passes.get(0).selected, // final boolean [] bg_tiles, // get from selected in clt_3d_passes.get(0);
......@@ -6091,6 +6209,15 @@ public class TileProcessor {
clt_parameters.stSmplNum, // Number after removing worst
clt_parameters.stSmplRms, // Maximal RMS of the remaining tiles in a sample
clt_parameters.stSmplWnd, // Use window functions for the samples
clt_parameters.fs_max_abs_tilt, // 2.0; // Maximal absolute tilt in pixels/tile
clt_parameters.fs_max_rel_tilt, // 0.2; // Maximal relative tilt in pixels/tile/disparity
clt_parameters.fs_damp_tilt, // 0.001; // Damp tilt to handle insufficient (co-linear)data
clt_parameters.fs_min_tilt_disp, // 4.0; // Disparity switch between filtering modes - near objects use tilts, far - use max disparity
clt_parameters.fs_transition, // 1.0; // Mode transition range (between tilted and maximal disparity)
clt_parameters.fs_far_mode, // 1; // Far objects filtering mode (0 - off, 1 - power of disparity)
clt_parameters.fs_far_power, // 1.0; // Raise disparity to this power before averaging for far objects
clt_parameters.stMeasSel); // bitmask of the selected measurements for supertiles : +1 - combo, +2 - quad +4 - hor +8 - vert
dbg_hist[0] = scan_prev.getSuperTiles().showDisparityHistogram();
......@@ -6108,6 +6235,15 @@ public class TileProcessor {
clt_parameters.stSmplNum, // Number after removing worst
clt_parameters.stSmplRms, // Maximal RMS of the remaining tiles in a sample
clt_parameters.stSmplWnd, // boolean smplWnd, // use window functions for the samples
clt_parameters.fs_max_abs_tilt, // 2.0; // Maximal absolute tilt in pixels/tile
clt_parameters.fs_max_rel_tilt, // 0.2; // Maximal relative tilt in pixels/tile/disparity
clt_parameters.fs_damp_tilt, // 0.001; // Damp tilt to handle insufficient (co-linear)data
clt_parameters.fs_min_tilt_disp, // 4.0; // Disparity switch between filtering modes - near objects use tilts, far - use max disparity
clt_parameters.fs_transition, // 1.0; // Mode transition range (between tilted and maximal disparity)
clt_parameters.fs_far_mode, // 1; // Far objects filtering mode (0 - off, 1 - power of disparity)
clt_parameters.fs_far_power, // 1.0; // Raise disparity to this power before averaging for far objects
clt_parameters.stMeasSel); // bitmask of the selected measurements for supertiles : +1 - combo, +2 - quad +4 - hor +8 - vert
dbg_hist[1] = scan_prev.getSuperTiles().showDisparityHistogram();
......
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment