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Commit c475ffe4 authored by Andrey Filippov's avatar Andrey Filippov
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debugging histograms for tilted disparity

parent 3b27965b
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Showing with 231 additions and 540 deletions
src/main/java/SuperTiles.java
View file @ c475ffe4
......@@ -347,6 +347,10 @@ public class SuperTiles{
System.out.println("getLapWeights: sum = "+s);
return lapWeight;
}
public void resetDisparityHistograms()
{
this.disparityHistograms = null;
}
public double [][] getDisparityHistograms(
final double [][][][] disparity_strength, // pre-calculated disparity/strength [per super-tile][per-measurement layer][2][tiles] or null
......@@ -357,6 +361,9 @@ public class SuperTiles{
final double smplRms, // = 0.1; // Maximal RMS of the remaining tiles in a sample
final int measSel) //
{
if (disparity_strength != null) {
System.out.println("getDisparityHistograms() with non-null disparity_strength");
}
if ((this.disparityHistograms != null) &&
(smplMode == this.smplMode) &&
(smplSide == this.smplSide) &&
......@@ -422,7 +429,7 @@ public class SuperTiles{
true); // boolean null_if_none);
}
} else {
disp_strength = disparity_strength[nsTile][nl];
disp_strength = (disparity_strength[nsTile] != null) ? disparity_strength[nsTile][nl] : null;
}
if (disp_strength != null) {
for (int indx = 0; indx < disp_strength[1].length; indx++) {
......@@ -492,7 +499,6 @@ public class SuperTiles{
// returns odd-length array of max/min (x, strength) pairs
public double [][][] getMaxMinMax(
// final double [] world_plane, // tilt equi-disparity planes to match real world planes (usually horizontal (or null)
final double [][][][] disparity_strength, // pre-calculated disparity/strength [per super-tile][per-measurement layer][2][tiles] or null
final boolean [][] tile_sel // null or per-measurement layer, per-tile selection. For each layer null - do not use, {} - use all
){
......@@ -1120,180 +1126,6 @@ public class SuperTiles{
ImageDtt.startAndJoin(threads);
}
public void processPlanes1(
final boolean [] selected, // or null
final double min_disp,
final boolean invert_disp, // use 1/disparity
final double plDispNorm,
final int debugLevel)
{
if (maxMinMax == null) getMaxMinMax(null, null);
final int np_min = 5; // minimal number of points to consider
final int tilesX = tileProcessor.getTilesX();
final int tilesY = tileProcessor.getTilesY();
final int superTileSize = tileProcessor.getSuperTileSize();
final int tileSize = tileProcessor.getTileSize();
final double [] disparity = cltPass3d.getDisparity();
final double [] strength = cltPass3d.getStrength();
final int stilesX = (tilesX + superTileSize -1)/superTileSize;
final int stilesY = (tilesY + superTileSize -1)/superTileSize;
final int nStiles = stilesX * stilesY;
final Thread[] threads = ImageDtt.newThreadArray(tileProcessor.threadsMax);
final AtomicInteger ai = new AtomicInteger(0);
final int st_start = -superTileSize/2;
final int superTileSize2 = 2 * superTileSize;
final double [][] lapWeight = getLapWeights();
final int len2 = superTileSize2*superTileSize2;
final double [] double_zero = new double [len2];
final boolean [] boolean_zero = new boolean [len2];
final int debug_stile = 18 * stilesX + 25;
for (int ithread = 0; ithread < threads.length; ithread++) {
threads[ithread] = new Thread() {
public void run() {
TilePlanes tpl = new TilePlanes(tileSize,superTileSize);
double [] stDisparity = new double [superTileSize2*superTileSize2];
double [] stStrength = new double [superTileSize2*superTileSize2];
boolean [] stSel = new boolean [superTileSize2*superTileSize2];
for (int nsTile = ai.getAndIncrement(); nsTile < nStiles; nsTile = ai.getAndIncrement()) {
int stileY = nsTile / stilesX;
int stileX = nsTile % stilesX;
double sw = 0.0; // sum weights
double [] hist = new double [numBins];
int tY0 = stileY * superTileSize + st_start;
int tX0 = stileX * superTileSize + st_start;
System.arraycopy(double_zero, 0, stDisparity, 0, len2);
System.arraycopy(double_zero, 0, stStrength, 0, len2);
System.arraycopy(boolean_zero, 0, stSel, 0, len2);
for (int tY = 0; tY < superTileSize2; tY++){
int tileY = tY0 +tY;
if ((tileY >= 0) && (tileY < tilesY)) {
for (int tX = 0; tX < superTileSize2; tX++){
int tileX = tX0 +tX;
if ((tileX >= 0) && (tileX < tilesX)) {
int indx = tileY*tilesX + tileX;
double d = disparity[indx];
if (!Double.isNaN(d) && (d >= min_disp) &&((selected == null) || selected[indx])){
if (invert_disp){
d = 1.0/d;
}
double w = strength[indx] - strength_floor;
if (w > 0.0){
if (strength_pow != 1.0) w = Math.pow(w, strength_pow);
w *= lapWeight[tY][tX];
int indx_out = tY * superTileSize2 + tX;
stDisparity[indx_out] = d;
stStrength[indx_out] = w;
stSel[indx_out] = true;
sw +=w;
}
}
}
}
}
}
if (sw >0){
// int dl = ((nsTile >= debug_stile-1) && (nsTile <= debug_stile+1) ) ? 1 : 0;
// int dl = (stileY == 17) ? 1 : 0;
int dl = (stileY >= 0) ? 1 : 0;
double [][][] rslt = tpl.getCovar(
stDisparity,
stStrength,
stSel,
plDispNorm,
0); // dl); // debugLevel);
double swc_common = 0.0;
if (dl > 0) {
int numPoints = (int) rslt[2][0][2];
double kz = rslt[2][0][1];
double swc = rslt[2][0][0];
double [] szxy = rslt[2][1];
double [][] eig_val = rslt[0];
double [][] eig_vect = rslt[1];
swc_common = swc;
if (swc > 1.0) {
System.out.println("Processing planes, nsTile="+nsTile+", stileX="+stileX+", stileY="+stileY+", numPoints="+numPoints+
", kz = "+kz+", sw = "+sw+ ", swc = "+swc+ ", center=["+szxy[0]+","+szxy[1]+","+szxy[2]+"]"+
", eig_val = {"+eig_val[0][0]+","+eig_val[1][1]+","+eig_val[2][2]+"}"+
", eig_vect[0] = {"+eig_vect[0][0]+","+eig_vect[1][0]+","+eig_vect[2][0]+"}");
}
}
double [][] mm = maxMinMax[nsTile];
if (mm.length > 1) { // multiple maximums - separate into multiple selections
boolean [][] stSels = new boolean[(mm.length +1)/2][stSel.length];
for (int i = 0; i< stSel.length; i++) if (stSel[i]){
double d = stDisparity[i];
loop:{
for (int m = 0; m < (stSels.length-1); m++){
if (d < mm[2 * m + 1][0]){
stSels[m][i] = true;
break loop;
}
}
stSels[stSels.length-1][i] = true;
}
}
double [][][][] rslts = new double [stSels.length][][][];
int [] np = new int[stSels.length];
String dbg_str = "";
for (int m = 0; m < stSels.length; m++){
for (int i =0; i < stSels[m].length; i++){
if (stSels[m][i]) np[m]++;
}
dbg_str +=" "+np[m];
if (m < stSels.length -1){
dbg_str +="("+mm[2*m+1][0]+")";
}
}
if (swc_common > 1.0) {
System.out.println("Processing subplanes:"+dbg_str+", nsTile="+nsTile);
}
for (int m = 0; m < stSels.length; m++) if (np[m] > np_min) {
rslts[m] = tpl.getCovar(
stDisparity,
stStrength,
stSels[m],
plDispNorm,
0); // dl); // debugLevel);
if (dl > 0) {
if (rslts[m] != null) {
int numPoints = (int) rslts[m][2][0][2];
double kz = rslts[m][2][0][1];
double swc = rslts[m][2][0][0];
double [] szxy = rslts[m][2][1];
double [][] eig_val = rslts[m][0];
double [][] eig_vect = rslts[m][1];
if (swc_common > 1.0) { // reduce output
System.out.println("Processing subplane["+m+"], nsTile="+nsTile+", stileX="+stileX+", stileY="+stileY+", numPoints="+numPoints+
", kz = "+kz+", sw = "+sw+ ", swc = "+swc+ ", center=["+szxy[0]+","+szxy[1]+","+szxy[2]+"]"+
", eig_val = {"+eig_val[0][0]+","+eig_val[1][1]+","+eig_val[2][2]+"}"+
", eig_vect[0] = {"+eig_vect[0][0]+","+eig_vect[1][0]+","+eig_vect[2][0]+"}");
}
} else {
System.out.println("Processing subplane["+m+"], nsTile="+nsTile+", stileX="+stileX+", stileY="+stileY+" RETURNED NULL");
}
}
}
}
}
}
}
};
}
ImageDtt.startAndJoin(threads);
}
public double corrMaxEigen(
double maxEigen,
......@@ -1322,325 +1154,6 @@ public class SuperTiles{
}
public void processPlanes2(
final boolean [] selected, // or null
final double min_disp,
final boolean invert_disp, // use 1/disparity
final double plDispNorm,
final int plMinPoints, // = 5; // Minimal number of points for plane detection
final double plTargetEigen, // = 0.1; // Remove outliers until main axis eigenvalue (possibly scaled by plDispNorm) gets below
final double plFractOutliers, // = 0.3; // Maximal fraction of outliers to remove
final int plMaxOutliers, // = 20; // Maximal number of outliers to remove
final boolean plPreferDisparity, // Always start with disparity-most axis (false - lowest eigenvalue)
final GeometryCorrection geometryCorrection,
final boolean correct_distortions,
final int debugLevel,
final int dbg_X,
final int dbg_Y)
{
if (maxMinMax == null) getMaxMinMax(null, null);
// final int np_min = 5; // minimal number of points to consider
final int tilesX = tileProcessor.getTilesX();
final int tilesY = tileProcessor.getTilesY();
final int superTileSize = tileProcessor.getSuperTileSize();
final int tileSize = tileProcessor.getTileSize();
final double [] disparity = cltPass3d.getDisparity();
final double [] strength = cltPass3d.getStrength();
final int stilesX = (tilesX + superTileSize -1)/superTileSize;
final int stilesY = (tilesY + superTileSize -1)/superTileSize;
final int nStiles = stilesX * stilesY;
final Thread[] threads = ImageDtt.newThreadArray(tileProcessor.threadsMax);
final AtomicInteger ai = new AtomicInteger(0);
final int st_start = -superTileSize/2;
final int superTileSize2 = 2 * superTileSize;
final double [][] lapWeight = getLapWeights();
final int len2 = superTileSize2*superTileSize2;
final double [] double_zero = new double [len2];
final boolean [] boolean_zero = new boolean [len2];
//ArrayList<Individual>[] group = (ArrayList<Individual>[])new ArrayList[4];
// this.planes = (ArrayList<TilePlanes.PlaneData>[]) new ArrayList[nStiles];
this.planes = new TilePlanes.PlaneData[nStiles][];
if (debugLevel > -1){
String [] titles = {"disp","strength","selection"};
double [][] dbg_img = new double [titles.length][];
dbg_img[0] = disparity;
dbg_img[1] = strength;
dbg_img[2] = strength.clone();
for (int i = 0; i < strength.length; i++) if (strength[i] != 0) dbg_img[2][i] = 1.0;
showDoubleFloatArrays sdfa_instance = new showDoubleFloatArrays();
sdfa_instance.showArrays(dbg_img, tileProcessor.getTilesX(), tileProcessor.getTilesY(), true, "disp_strength_sel",titles);
}
// final int debug_stile = 18 * stilesX + 25;
// final int debug_stile = 20 * stilesX + 24;
// final int debug_stile = 16 * stilesX + 27; // 10;
final int debug_stile = (debugLevel > -1)? (dbg_Y * stilesX + dbg_X):-1;
for (int ithread = 0; ithread < threads.length; ithread++) {
threads[ithread] = new Thread() {
public void run() {
TilePlanes tpl = new TilePlanes(tileSize,superTileSize, geometryCorrection);
double [] stDisparity = new double [superTileSize2*superTileSize2];
double [] stStrength = new double [superTileSize2*superTileSize2];
boolean [] stSel = new boolean [superTileSize2*superTileSize2];
for (int nsTile = ai.getAndIncrement(); nsTile < nStiles; nsTile = ai.getAndIncrement()) {
if (nsTile == debug_stile){
System.out.println("processPlanes2(): nsTile="+nsTile);
}
int stileY = nsTile / stilesX;
int stileX = nsTile % stilesX;
int [] sTiles = {stileX, stileY};
double sw = 0.0; // sum weights
/// double [] hist = new double [numBins];
int tY0 = stileY * superTileSize + st_start;
int tX0 = stileX * superTileSize + st_start;
System.arraycopy(double_zero, 0, stDisparity, 0, len2);
System.arraycopy(double_zero, 0, stStrength, 0, len2);
System.arraycopy(boolean_zero, 0, stSel, 0, len2);
for (int tY = 0; tY < superTileSize2; tY++){
int tileY = tY0 +tY;
if ((tileY >= 0) && (tileY < tilesY)) {
for (int tX = 0; tX < superTileSize2; tX++){
int tileX = tX0 +tX;
if ((tileX >= 0) && (tileX < tilesX)) {
int indx = tileY*tilesX + tileX;
double d = disparity[indx];
if (!Double.isNaN(d) && (d >= min_disp) &&((selected == null) || selected[indx])){
if (invert_disp){
d = 1.0/d;
}
double w = strength[indx] - strength_floor;
if (w > 0.0){
if (strength_pow != 1.0) w = Math.pow(w, strength_pow);
w *= lapWeight[tY][tX];
int indx_out = tY * superTileSize2 + tX;
stDisparity[indx_out] = d;
stStrength[indx_out] = w;
stSel[indx_out] = true;
sw +=w;
}
}
}
}
}
}
planes[nsTile] = null;
if (sw >0){ // there are some non-zero tiles, process them (all points, not clustered by disparity value)
ArrayList<TilePlanes.PlaneData> st_planes = new ArrayList<TilePlanes.PlaneData>();
int dl1 = (nsTile == debug_stile) ? 3 : 0;
int dl = (nsTile == debug_stile) ? 3 : 0;
boolean [] sel_all = stSel.clone();
TilePlanes.PlaneData pd = tpl.getPlane(
sTiles,
stDisparity,
stStrength,
sel_all,
plPreferDisparity,
dl); // 0); // debugLevel);
if (pd != null) { // not too few points, probably
//correct_distortions
double swc_common = pd.getWeight();
if (dl > 0) {
if (swc_common > 0.1) { // 1.0) {
System.out.println("Processing planes["+nsTile+"]"+
", stileX="+stileX+
", stileY="+stileY+
", numPoints="+ pd.getNumPoints()+
", sw = "+swc_common+
", swc = "+pd.getWeight()+
", center=["+pd.getZxy()[0]+","+pd.getZxy()[1]+","+pd.getZxy()[2]+"]"+
", eig_val = {"+pd.getValues()[0]+","+pd.getValues()[1]+","+pd.getValues()[2]+"}"+
", eig_vect[0] = {"+pd.getVector()[0]+","+pd.getVector()[1]+","+pd.getVector()[2]+"}");
}
if (debugLevel > -1){
showDoubleFloatArrays sdfa_instance = new showDoubleFloatArrays();
double [][] dbg_img = new double [3][];
dbg_img[0] = stDisparity;
dbg_img[1] =stStrength;
dbg_img[2] = new double [superTileSize2*superTileSize2];
for (int i = 0; i < dbg_img[2].length; i++){
dbg_img[2][i] = sel_all[i]?1.0:0.0;
}
sdfa_instance.showArrays(dbg_img, superTileSize2, superTileSize2, true, "p2_disp_str_sel");
}
}
// now try to remove outliers
int max_outliers = (int) Math.round(pd.getNumPoints() * plFractOutliers);
if (max_outliers > plMaxOutliers) max_outliers = plMaxOutliers;
double targetV = corrMaxEigen(
plTargetEigen,
plDispNorm,
pd);
if (pd.getValue() > targetV) {
pd = tpl.removePlaneOutliers(
pd,
sTiles,
stDisparity,
stStrength,
sel_all,
targetV, // double targetEigen, // target eigenvalue for primary axis (is disparity-dependent, so is non-constant)
max_outliers, // int maxRemoved, // maximal number of tiles to remove (not a constant)
plMinPoints, // int minLeft, // minimal number of tiles to keep
plPreferDisparity,
dl1); // 0); // debugLevel);
if (pd == null) continue;
if (dl > 0) {
if (swc_common > 0.3) { // 1.0) {
System.out.println("Removed outliers["+nsTile+"]"+
", stileX="+stileX+
", stileY="+stileY+
", numPoints="+ pd.getNumPoints()+
", sw = "+swc_common+
", swc = "+pd.getWeight()+
", center=["+pd.getZxy()[0]+","+pd.getZxy()[1]+","+pd.getZxy()[2]+"]"+
", eig_val = {"+pd.getValues()[0]+","+pd.getValues()[1]+","+pd.getValues()[2]+"}"+
", eig_vect[0] = {"+pd.getVector()[0]+","+pd.getVector()[1]+","+pd.getVector()[2]+"}");
}
}
} // nothing to do if already OK
if (dl > 0) {
System.out.println("Calculating World normal["+nsTile+"]");
}
double [] norm_xyz = pd.getWorldXYZ(
correct_distortions,
dl);
if (dl > 0) {
System.out.println("World normal["+nsTile+"] = {"+
norm_xyz[0]+", "+norm_xyz[1]+", "+norm_xyz[2]+"}");
}
st_planes.add(pd); // adding [0] - all supertile tiles, not clustered by disparity value
// now try for each of the disparity-separated clusters (only for multi-peak histograms)
double [][] mm = maxMinMax[nsTile];
if (mm.length > 1) { // multiple maximums - separate into multiple selections
boolean [][] stSels = new boolean[(mm.length +1)/2][stSel.length];
for (int i = 0; i< stSel.length; i++) if (stSel[i]){
double d = stDisparity[i];
loop:{
for (int m = 0; m < (stSels.length-1); m++){
if (d < mm[2 * m + 1][0]){
stSels[m][i] = true;
break loop;
}
}
stSels[stSels.length-1][i] = true;
}
}
double [][][][] rslts = new double [stSels.length][][][];
int [] np = new int[stSels.length];
String dbg_str = "";
for (int m = 0; m < stSels.length; m++){
for (int i =0; i < stSels[m].length; i++){
if (stSels[m][i]) np[m]++;
}
dbg_str +=" "+np[m];
if (m < stSels.length -1){
dbg_str +="("+mm[2*m+1][0]+")";
}
}
if ((dl > 0) && (swc_common > 1.0)) {
System.out.println("Processing subplanes["+nsTile+"]:"+dbg_str);
}
for (int m = 0; m < stSels.length; m++) if (np[m] > plMinPoints) {
pd = tpl.getPlane(
sTiles,
stDisparity,
stStrength,
stSels[m],
plPreferDisparity,
0); // debugLevel);
if (pd != null) {
if (dl > 0) {
if (swc_common > 1.0) {
System.out.println("Processing subplane["+nsTile+"]["+m+"]"+
", stileX="+stileX+
", stileY="+stileY+
", numPoints="+ pd.getNumPoints()+
", sw = "+swc_common+
", swc = "+pd.getWeight()+
", center=["+pd.getZxy()[0]+","+pd.getZxy()[1]+","+pd.getZxy()[2]+"]"+
", eig_val = {"+pd.getValues()[0]+","+pd.getValues()[1]+","+pd.getValues()[2]+"}"+
", eig_vect[0] = {"+pd.getVector()[0]+","+pd.getVector()[1]+","+pd.getVector()[2]+"}");
}
}
// now try to remove outliers
max_outliers = (int) Math.round(pd.getNumPoints() * plFractOutliers);
if (max_outliers > plMaxOutliers) max_outliers = plMaxOutliers;
targetV = plTargetEigen;
double z0 = pd.getZxy()[0];
if ((plDispNorm > 0.0) && (z0 > plDispNorm)) {
double dd = (plDispNorm + z0)/ plDispNorm; // > 1
targetV *= dd * dd; // > original
}
if (pd.getValues()[0] > targetV) {
pd = tpl.removePlaneOutliers(
pd,
sTiles,
stDisparity,
stStrength,
stSels[m],
targetV, // double targetEigen, // target eigenvalue for primary axis (is disparity-dependent, so is non-constant)
max_outliers, // int maxRemoved, // maximal number of tiles to remove (not a constant)
plMinPoints, // int minLeft, // minimal number of tiles to keep
plPreferDisparity,
dl1); // 0); // debugLevel);
if (pd == null) {
continue;
}
if (dl > 0) {
if (swc_common > 1.0) {
System.out.println("Removed outliers["+nsTile+"]["+m+"]"+
", stileX="+stileX+
", stileY="+stileY+
", numPoints="+ pd.getNumPoints()+
", sw = "+swc_common+
", swc = "+pd.getWeight()+
", center=["+pd.getZxy()[0]+","+pd.getZxy()[1]+","+pd.getZxy()[2]+"]"+
", eig_val = {"+pd.getValues()[0]+","+pd.getValues()[1]+","+pd.getValues()[2]+"}"+
", eig_vect[0] = {"+pd.getVector()[0]+","+pd.getVector()[1]+","+pd.getVector()[2]+"}");
}
}
}
norm_xyz = pd.getWorldXYZ(
correct_distortions);
st_planes.add(pd);
if (dl > 0) {
System.out.println("World normal["+nsTile+"]["+m+"] = {"+
norm_xyz[0]+", "+norm_xyz[1]+", "+norm_xyz[2]+"}");
}
}
}
}
}
if (st_planes.size() > 0){
planes[nsTile] = st_planes.toArray(new TilePlanes.PlaneData[0] );
if (dl >0){
System.out.println("processPlanes2(): nsTile="+nsTile);
}
}
} // if sw >0
}
}
};
}
ImageDtt.startAndJoin(threads);
}
public void processPlanes3(
final boolean [] selected, // or null
final double min_disp,
......@@ -1731,6 +1244,7 @@ public class SuperTiles{
sTiles, // int [] sTileXY,
tileSize, // int tileSize,
geometryCorrection, // GeometryCorrection geometryCorrection,
correct_distortions,
measuredLayers, // MeasuredLayers measuredLayers,
plPreferDisparity); // boolean preferDisparity)
boolean [][] tile_sel = dflt_select.clone();
......@@ -1973,7 +1487,7 @@ public class SuperTiles{
boolean [][][] selections)
{
int num_ml = disp_strength.length;
int num_p = selections.length;
int num_p = (selections == null) ? 0: selections.length;
int num_pm = num_ml * num_p;
String [] titles = new String [num_pm + 3 * num_ml];
for (int np = 0; np < num_p; np++){
......@@ -1982,9 +1496,9 @@ public class SuperTiles{
}
}
for (int ml = 0; ml < num_ml; ml++){
titles [num_pm + 0 * num_ml + ml] = "sel_"+ml;
titles [num_pm + 1 * num_ml + ml] = "disp_"+ml;
titles [num_pm + 2 * num_ml + ml] = "strn_"+ml;
titles [num_pm + 0 * num_ml + ml] = "disp_"+ml;
titles [num_pm + 1 * num_ml + ml] = "strn_"+ml;
titles [num_pm + 2 * num_ml + ml] = "sel_"+ml;
}
......@@ -1996,7 +1510,7 @@ public class SuperTiles{
{
int superTileSize = tileProcessor.getSuperTileSize();
int num_ml = disp_strength.length;
int num_p = selections.length;
int num_p = (selections == null) ? 0: selections.length;
int num_pm = num_ml * num_p;
double [][] data = new double [num_pm + 3 * num_ml][]; // 4* superTileSize*superTileSize];
for (int np = 0; np < num_p; np++) if (selections [np] != null){
......@@ -2013,7 +1527,7 @@ public class SuperTiles{
}
}
for (int ml = 0; ml < num_ml; ml++) if (disp_strength[ml]!=null){
int nd = num_pm + 0 * num_ml + ml;
int nd = num_pm + 2 * num_ml + ml;
data [nd] = new double [4* superTileSize*superTileSize];
for (int i = 0; i < data[nd].length; i++){
......@@ -2023,17 +1537,131 @@ public class SuperTiles{
break;
}
}
data [num_pm + 1 * num_ml + ml] = disp_strength[ml][0];
data [num_pm + 2 * num_ml + ml] = disp_strength[ml][1];
data [num_pm + 0 * num_ml + ml] = disp_strength[ml][0];
data [num_pm + 1 * num_ml + ml] = disp_strength[ml][1];
}
return data;
}
public double [][][][] getPlaneDispStrengths(
final double [] world_plane_norm, // real world normal vector to a suggested plane family (0,1,0) for horizontal planes
final int stMeasSel, // = 1; // Select measurements for supertiles : +1 - combo, +2 - quad +4 - hor +8 - vert
final boolean plPreferDisparity, // Always start with disparity-most axis (false - lowest eigenvalue)
final GeometryCorrection geometryCorrection,
final boolean correct_distortions,
final boolean smplMode, // = true; // Use sample mode (false - regular tile mode)
final int smplSide, // = 2; // Sample size (side of a square)
final int smplNum, // = 3; // Number after removing worst
final double smplRms, // = 0.1; // Maximal RMS of the remaining tiles in a sample
final int debugLevel,
final int dbg_X,
final int dbg_Y)
{
final int tilesX = tileProcessor.getTilesX();
final int tilesY = tileProcessor.getTilesY();
final int superTileSize = tileProcessor.getSuperTileSize();
final int tileSize = tileProcessor.getTileSize();
final int stilesX = (tilesX + superTileSize -1)/superTileSize;
final int stilesY = (tilesY + superTileSize -1)/superTileSize;
final int nStiles = stilesX * stilesY;
final Thread[] threads = ImageDtt.newThreadArray(tileProcessor.threadsMax);
final AtomicInteger ai = new AtomicInteger(0);
final int debug_stile = (debugLevel > -1)? (dbg_Y * stilesX + dbg_X):-1;
// TODO: Remove when promoting PlaneData
final TilePlanes tpl = new TilePlanes(tileSize,superTileSize, geometryCorrection);
final double [][][][] plane_disp_strength = new double [nStiles][][][];
for (int ithread = 0; ithread < threads.length; ithread++) {
threads[ithread] = new Thread() {
public void run() {
for (int nsTile = ai.getAndIncrement(); nsTile < nStiles; nsTile = ai.getAndIncrement()) {
if (nsTile == debug_stile){
System.out.println("getPlaneDispStrengths(): nsTile="+nsTile);
}
int stileY = nsTile / stilesX;
int stileX = nsTile % stilesX;
int [] sTiles = {stileX, stileY};
// first make a plane from all tiles
TilePlanes.PlaneData pd0 = tpl.new PlaneData (
sTiles, // int [] sTileXY,
tileSize, // int tileSize,
geometryCorrection, // GeometryCorrection geometryCorrection,
correct_distortions,
measuredLayers, // MeasuredLayers measuredLayers,
plPreferDisparity); // boolean preferDisparity)
int dl = (nsTile == debug_stile) ? 3 : 0;
plane_disp_strength[nsTile] = new double[measuredLayers.getNumLayers()][][];
for (int ml = 0; ml < plane_disp_strength[nsTile].length; ml++) if ((stMeasSel & ( 1 << ml)) != 0){
if (smplMode) {
plane_disp_strength[nsTile][ml] = measuredLayers.getDisparityStrength(
ml, // int num_layer,
stileX, // int stX,
stileY, // int stY,
null, // boolean [] sel_in,
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
true); // boolean null_if_none);
} else {
plane_disp_strength[nsTile][ml] = measuredLayers.getDisparityStrength(
ml, // int num_layer,
stileX, // int stX,
stileY, // int stY,
null, // boolean [] sel_in,
strength_floor, // double strength_floor,
strength_pow, // double strength_pow,
true); // boolean null_if_none);
}
}
// find average disparity for the supertile (improve?)
double sd = 0.0, sw = 0.0;
for (int ml = 0; ml < plane_disp_strength[nsTile].length; ml++) if ((stMeasSel & ( 1 << ml)) != 0){
for (int i = 0; i < plane_disp_strength[nsTile][ml][1].length; i++){
double w = plane_disp_strength[nsTile][ml][1][i];
double d = plane_disp_strength[nsTile][ml][0][i];
sd += w * d;
sw += w;
}
}
if (sw > 0) {
if (dl > 0) {
System.out.println("Plane tilted disparity for stileX = "+stileX+" stileY="+stileY+", average disparity "+(sd/sw));
}
plane_disp_strength[nsTile] = pd0.getDisparityToPlane(
world_plane_norm, // double [] world_normal_xyz,
sd / sw, // average disparity // double disp_center,
null, // boolean [][] tile_sel, // null - do not use, {} use all (will be modified)
plane_disp_strength[nsTile], // double [][][] disp_str, // calculate just once if null
1); // int debugLevel);
if (dl>1) {
String [] dbg_titles = showSupertileSeparationTitles( plane_disp_strength[nsTile], null);
double [][] dbg_img = showSUpertileSeparation(plane_disp_strength[nsTile], null); // plane_sels);
showDoubleFloatArrays sdfa_instance = new showDoubleFloatArrays();
sdfa_instance.showArrays(dbg_img, 2 * superTileSize, 2* superTileSize, true, "plane_separation"+nsTile,dbg_titles);
}
} else {
plane_disp_strength[nsTile] = null;
}
}
}
};
}
ImageDtt.startAndJoin(threads);
return plane_disp_strength;
}
public void processPlanes4(
final boolean [] selected, // or null
final double min_disp,
// final boolean [] selected, // or null
// final double min_disp,
final int stMeasSel, // = 1; // Select measurements for supertiles : +1 - combo, +2 - quad +4 - hor +8 - vert
final double plDispNorm,
final int plMinPoints, // = 5; // Minimal number of points for plane detection
......@@ -2071,6 +1699,7 @@ public class SuperTiles{
final int debug_stile = (debugLevel > -1)? (dbg_Y * stilesX + dbg_X):-1;
// final boolean [][] dflt_select = {{}, null, null, null, null}; // use layer 0 (combo) only
/*
final boolean [][] dflt_select = new boolean [measuredLayers.getNumLayers()][];
for (int i = 0; i < dflt_select.length; i++){
if ((stMeasSel & (1 << i)) !=0){
......@@ -2079,7 +1708,7 @@ public class SuperTiles{
dflt_select[i] = null;
}
}
*/
// TODO: Remove when promoting PlaneData
final TilePlanes tpl = new TilePlanes(tileSize,superTileSize, geometryCorrection);
......@@ -2103,7 +1732,56 @@ public class SuperTiles{
showDoubleFloatArrays sdfa_instance = new showDoubleFloatArrays();
sdfa_instance.showArrays(dbg_img, tileProcessor.getTilesX(), tileProcessor.getTilesY(), true, "measuredLayers",titles);
}
getMaxMinMax(null, null);
// getMaxMinMax(
// null, // final double [][][][] disparity_strength, // pre-calculated disparity/strength [per super-tile][per-measurement layer][2][tiles] or null
// null); // final boolean [][] tile_sel // null or per-measurement layer, per-tile selection. For each layer null - do not use, {} - use all
double [] world_hor = {0.0, 1.0, 0.0};
final double [][][][] plane_disp_strength = getPlaneDispStrengths(
world_hor, // final double [] world_plane_norm, // real world normal vector to a suggested plane family (0,1,0) for horizontal planes
stMeasSel, //final int stMeasSel, // = 1; // Select measurements for supertiles : +1 - combo, +2 - quad +4 - hor +8 - vert
plPreferDisparity, // final boolean plPreferDisparity, // Always start with disparity-most axis (false - lowest eigenvalue)
geometryCorrection, // final GeometryCorrection geometryCorrection,
correct_distortions, // final boolean correct_distortions,
smplMode, // final boolean smplMode, // = true; // Use sample mode (false - regular tile mode)
smplSide, //final int smplSide, // = 2; // Sample size (side of a square)
smplNum, //final int smplNum, // = 3; // Number after removing worst
smplRms, //final double smplRms, // = 0.1; // Maximal RMS of the remaining tiles in a sample
debugLevel,
dbg_X,
dbg_Y);
String [] dbg_hist_titles = {"all","hor","mm_all","mm_hor"};
double [][] dbg_hist = new double [dbg_hist_titles.length][];
System.out.println("Calculating histograms for hoirizontal planes");
resetDisparityHistograms();
final double [][][] mmm_hor = getMaxMinMax(
plane_disp_strength, // final double [][][][] disparity_strength, // pre-calculated disparity/strength [per super-tile][per-measurement layer][2][tiles] or null
null); // final boolean [][] tile_sel // null or per-measurement layer, per-tile selection. For each layer null - do not use, {} - use all
if (debugLevel > -1) {
dbg_hist[1] = showDisparityHistogram().clone();
dbg_hist[3] = showMaxMinMax().clone();
}
resetDisparityHistograms();
final double [][][] mmm_all = getMaxMinMax(
null, // final double [][][][] disparity_strength, // pre-calculated disparity/strength [per super-tile][per-measurement layer][2][tiles] or null
null); // final boolean [][] tile_sel // null or per-measurement layer, per-tile selection. For each layer null - do not use, {} - use all
if (debugLevel > -1) {
dbg_hist[0] = showDisparityHistogram().clone();
dbg_hist[2] = showMaxMinMax().clone();
}
if (debugLevel > -1) {
int hist_width0 = showDisparityHistogramWidth();
int hist_height0 = dbg_hist[0].length/hist_width0;
showDoubleFloatArrays sdfa_instance = new showDoubleFloatArrays(); // just for debugging?
sdfa_instance.showArrays(dbg_hist, hist_width0, hist_height0, true, "all_hor_histograms",dbg_hist_titles);
}
for (int ithread = 0; ithread < threads.length; ithread++) {
threads[ithread] = new Thread() {
......@@ -2121,16 +1799,25 @@ public class SuperTiles{
sTiles, // int [] sTileXY,
tileSize, // int tileSize,
geometryCorrection, // GeometryCorrection geometryCorrection,
correct_distortions,
measuredLayers, // MeasuredLayers measuredLayers,
plPreferDisparity); // boolean preferDisparity)
/*
boolean [][] tile_sel = dflt_select.clone();
for (int i = 0; i < dflt_select.length; i++){
if (dflt_select[i] != null) tile_sel[i] = dflt_select[i].clone();
}
int dl1 = (nsTile == debug_stile) ? 3 : 0;
*/
// int dl1 = (nsTile == debug_stile) ? 3 : 0;
int dl = (nsTile == debug_stile) ? 3 : 0;
// plane_disp_strength
if (dl > 2) {
String [] dbg_titles = showSupertileSeparationTitles(plane_disp_strength[nsTile], null);
double [][] dbg_img = showSUpertileSeparation(plane_disp_strength[nsTile], null);
showDoubleFloatArrays sdfa_instance = new showDoubleFloatArrays();
sdfa_instance.showArrays(dbg_img, 2 * superTileSize, 2* superTileSize, true, "HOR_SEP_"+nsTile,dbg_titles);
}
ArrayList<TilePlanes.PlaneData> st_planes = new ArrayList<TilePlanes.PlaneData>();
double[][][] disp_strength = new double[measuredLayers.getNumLayers()][][];
......@@ -2162,6 +1849,7 @@ public class SuperTiles{
}
boolean OK;
double [][] mm = maxMinMax[nsTile];
if (mm == null){
......@@ -2452,7 +2140,7 @@ public class SuperTiles{
return wh;
}
// TODO: Obsolete (never used)?
TilePlanes.PlaneData [][] getNeibPlanes(
final int dir, // 0: get from up (N), 1:from NE, ... 7 - from NW
final boolean preferDisparity,
......@@ -2487,6 +2175,7 @@ public class SuperTiles{
neib_planes[nsTile0] = new TilePlanes.PlaneData[planes[nsTile].length];
for (int np = 0; np < planes[nsTile].length; np++){
GeometryCorrection geometryCorrection = planes[nsTile][np].getGeometryCorrection();
boolean correct_distortions = planes[nsTile][np].getCorrectDistortions();
int [] sTileXY0 = {stx0,sty0};
if (tpl == null) {
tpl = new TilePlanes(tileSize,superTileSize, geometryCorrection);
......@@ -2495,7 +2184,8 @@ public class SuperTiles{
sTileXY0,
tileSize,
superTileSize,
geometryCorrection);
geometryCorrection,
correct_distortions);
/*
TilePlanes.PlaneData pd = planes[nsTile0][np].clone();
pd.setS
......
src/main/java/TilePlanes.java
View file @ c475ffe4
......@@ -90,8 +90,9 @@ public class TilePlanes {
this.sTileXY,
this.tileSize,
this.superTileSize,
this.geometryCorrection);
pd.correctDistortions = this.correctDistortions;
this.geometryCorrection,
this.correctDistortions);
// pd.correctDistortions = this.correctDistortions;
pd.num_points = this.num_points;
pd.weight = this.weight;
if (this.plane_sel != null) pd.plane_sel = this.plane_sel.clone();
......@@ -204,9 +205,11 @@ public class TilePlanes {
int [] sTileXY,
int tileSize,
int superTileSize,
GeometryCorrection geometryCorrection)
GeometryCorrection geometryCorrection,
boolean correctDistortions)
{
this.geometryCorrection = geometryCorrection;
this.correctDistortions = correctDistortions;
this.tileSize = tileSize;
this.superTileSize = superTileSize;
this.sTileXY = sTileXY.clone();
......@@ -216,10 +219,12 @@ public class TilePlanes {
int [] sTileXY,
int tileSize,
GeometryCorrection geometryCorrection,
boolean correctDistortions,
MeasuredLayers measuredLayers,
boolean preferDisparity)
{
this.geometryCorrection = geometryCorrection;
this.correctDistortions = correctDistortions;
this.tileSize = tileSize;
this.superTileSize = measuredLayers.getSuperTileSize();
this.sTileXY = sTileXY.clone();
......@@ -591,7 +596,9 @@ public class TilePlanes {
}
}
double n_by_w = normal_row.times(st_xyz).get(0, 0);
if (debugLevel > 1) {
System.out.println("st_xyz = {"+st_xyz.get(0, 0)+","+st_xyz.get(1, 0)+","+st_xyz.get(2, 0)+"}"+" ="+n_by_w);
}
for (int ml = 0; ml < disp_str.length; ml++) if (disp_str[ml] != null){
for (int dy = 0; dy < stSize2; dy ++ ){
double y = (dy - stSize + 0.5) * tileSize;
......@@ -611,9 +618,11 @@ public class TilePlanes {
double n_by_p = normal_row.times(w_xyz).get(0, 0);
double z = st_xyz.get(2, 0)*n_by_p / n_by_w;
if (disp_str[ml][1][indx] > 0){ // do not bother with zero-strength
if (debugLevel > 1) {
System.out.println("dy = "+dy+", dx=" + dx+ " {"+w_xyz.get(0, 0)+","+w_xyz.get(1, 0)+","+w_xyz.get(2, 0)+"}"+" z="+z+" n_by_p = "+n_by_p
+" disp = "+disp_str[ml][0][indx]+" px = "+(px_py[0] + x)+" py = "+(px_py[1] + y));
}
}
// convert z to disparity
eff_disp_str[ml][0][indx] = geometryCorrection.getDisparityFromZ (-z);
}
......@@ -1972,12 +1981,13 @@ public class TilePlanes {
{swz, swx, swy}}};
return rslt;
}
// TODO: obsolete - remove
public PlaneData getPlane(
int [] sTileXY,
double [] data,
double [] weight,
boolean [] select, // null OK, will enable all tiles
boolean correctDistortions,
boolean preferDisparity, // Always start with disparity-most axis (false - lowest eigenvalue)
int debugLevel){
if (select == null) {
......@@ -2042,7 +2052,8 @@ public class TilePlanes {
sTileXY,
this.tileSize,
this.stSize,
this.geometryCorrection);
this.geometryCorrection,
correctDistortions);
pd.setZxy(szxy);
// pd.setValues(eig_val[oindx][oindx],eig_val[hindx][hindx],eig_val[vindx][vindx]); // eigenvalues [0] - thickness, 2 other to detect skinny (poles)
......@@ -2081,6 +2092,7 @@ public class TilePlanes {
double [] data,
double [] weight,
boolean [] select, // will be modified
boolean correctDistortions,
double targetEigen, // target eigenvalue for primary axis (is disparity-dependent, so is non-constant)
int maxRemoved, // maximal number of tiles to remove (not a constant)
int minLeft, // minimal number of tiles to keep
......@@ -2093,6 +2105,7 @@ public class TilePlanes {
data,
weight,
select, // null OK
correctDistortions,
preferDisparity,
debugLevel);
} else if (select != null){
......@@ -2142,6 +2155,7 @@ public class TilePlanes {
data,
weight,
select,
correctDistortions,
preferDisparity,
debugLevel);
if (pd == null) {
......
src/main/java/TileProcessor.java
View file @ c475ffe4
......@@ -3043,8 +3043,8 @@ public class TileProcessor {
// moved here
if (clt_parameters.dbg_migrate) {
st.processPlanes4(
null, // final boolean [] selected, // or null
0.3, // final double min_disp,
// null, // final boolean [] selected, // or null
// 0.3, // final double min_disp,
clt_parameters.stMeasSel, // = 1 //Select measurements for supertiles : +1 - combo, +2 - quad +4 - hor +8 - vert
clt_parameters.plDispNorm, // = 2.0; // Normalize disparities to the average if above
clt_parameters.plMinPoints, // = 5; // Minimal number of points for plane detection
......@@ -3086,23 +3086,6 @@ public class TileProcessor {
0, // -1, // debugLevel, // final int debugLevel)
clt_parameters.tileX,
clt_parameters.tileY);
/*
st.processPlanes2(
null, // final boolean [] selected, // or null
0.3, // final double min_disp,
false, // final boolean invert_disp, // use 1/disparity
clt_parameters.plDispNorm, // = 2.0; // Normalize disparities to the average if above
clt_parameters.plMinPoints, // = 5; // Minimal number of points for plane detection
clt_parameters.plTargetEigen, // = 0.1; // Remove outliers until main axis eigenvalue (possibly scaled by plDispNorm) gets below
clt_parameters.plFractOutliers, // = 0.3; // Maximal fraction of outliers to remove
clt_parameters.plMaxOutliers, // = 20; // Maximal number of outliers to remove\
clt_parameters.plPreferDisparity,
geometryCorrection,
clt_parameters.correct_distortions,
0, // -1, // debugLevel, // final int debugLevel)
clt_parameters.tileX,
clt_parameters.tileY);
*/
}
showDoubleFloatArrays sdfa_instance = null;
......@@ -3317,6 +3300,10 @@ public class TileProcessor {
plane_data[indx++] = plane_data_nan[i];
}
plane_data[indx++] = split_lines;
if (indx <2) { // out of bound
System.out.println("BUG: insufficient data");
return;
}
plane_data[indx] = plane_data[indx-2].clone(); // java.lang.ArrayIndexOutOfBoundsException: -1
for (int i = 0; i < plane_data[indx].length;i++){
if (Double.isNaN(plane_data[indx][i])) plane_data[indx][i] = 0.0;
......
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