Tested basic DSI generation for LWIR

src/main/java/com/elphel/imagej/cameras/EyesisCorrectionParameters.java

@@ -160,7 +160,8 @@ public class EyesisCorrectionParameters {
   		public boolean clt_batch_genMl =      true;  // Generate ML output
   		public boolean clt_batch_dbg1 =       true;  // Generate debug images if a single set is selected
   		public boolean clt_batch_dsi =        true;  // Create and save DSI combo image with the model
-  		public boolean clt_batch_dsi_aux =    false;  // Calculate and save aux camera DSI (currently it is offset from the main/rig data
+		public boolean clt_batch_dsi_aux =    false;  // Calculate and save aux camera DSI (currently it is offset from the main/rig data
+		public boolean clt_batch_dsi_aux_full=false;  // more than just preExpandCLTQuad3d() (same as for Lazy Eye
   		public boolean clt_batch_save_extrinsics =    true;  // Save cameras extrinsic parameters with the model
   		public boolean clt_batch_save_all =    true;  // Save all parameters with the model
 
@@ -302,6 +303,7 @@ public class EyesisCorrectionParameters {
 
   			cp.clt_batch_dsi=    		  this.clt_batch_dsi;
   			cp.clt_batch_dsi_aux=    	  this.clt_batch_dsi_aux;
+  			cp.clt_batch_dsi_aux_full= 	  this.clt_batch_dsi_aux_full;
   			cp.clt_batch_save_extrinsics= this.clt_batch_save_extrinsics;
   			cp.clt_batch_save_all=        this.clt_batch_save_all;
 
@@ -482,6 +484,7 @@ public class EyesisCorrectionParameters {
 
     		properties.setProperty(prefix+"clt_batch_dsi",             this.clt_batch_dsi+"");
     		properties.setProperty(prefix+"clt_batch_dsi_aux",         this.clt_batch_dsi_aux+"");
+    		properties.setProperty(prefix+"clt_batch_dsi_aux_full",    this.clt_batch_dsi_aux_full+"");
     		properties.setProperty(prefix+"clt_batch_save_extrinsics", this.clt_batch_save_extrinsics+"");
     		properties.setProperty(prefix+"clt_batch_save_all",        this.clt_batch_save_all+"");
 
@@ -640,6 +643,7 @@ public class EyesisCorrectionParameters {
 
 			if (properties.getProperty(prefix+"clt_batch_dsi")!= null)             this.clt_batch_dsi=Boolean.parseBoolean(properties.getProperty(prefix+"clt_batch_dsi"));
 			if (properties.getProperty(prefix+"clt_batch_dsi_aux")!= null)         this.clt_batch_dsi_aux=Boolean.parseBoolean(properties.getProperty(prefix+"clt_batch_dsi_aux"));
+			if (properties.getProperty(prefix+"clt_batch_dsi_aux_full")!= null)    this.clt_batch_dsi_aux_full=Boolean.parseBoolean(properties.getProperty(prefix+"clt_batch_dsi_aux_full"));
 			if (properties.getProperty(prefix+"clt_batch_save_extrinsics")!= null) this.clt_batch_save_extrinsics=Boolean.parseBoolean(properties.getProperty(prefix+"clt_batch_save_extrinsics"));
 			if (properties.getProperty(prefix+"clt_batch_save_all")!= null)        this.clt_batch_save_all=Boolean.parseBoolean(properties.getProperty(prefix+"clt_batch_save_all"));
 
@@ -1015,6 +1019,10 @@ public class EyesisCorrectionParameters {
     		gd.addCheckbox    ("Include/genarate separate aux camera DSI data in the combo DSI",     this.clt_batch_dsi_aux,
     				"8-rig: DSI for the AUX camera is offset (by the rig baseline) from the main and rig DSI. Aux DSI requires extra processing time."+
     		" EO+LWIR - generate a separate GT+AUX file");
+    		gd.addCheckbox    ("Additional steps to calculate Auf DSI (more than for LY adjustment)",   this.clt_batch_dsi_aux_full,
+    				"(Not yet tested)");
+    		
+    		
     		gd.addCheckbox    ("Save field adjustment data with the model",                          this.clt_batch_save_extrinsics,
     				"This data can be used to restore specific filed-adjusted cameras extrinsics used when the model was generated");
     		gd.addCheckbox    ("Save all parameters with the model",                                 this.clt_batch_save_all,
@@ -1103,6 +1111,7 @@ public class EyesisCorrectionParameters {
     		this.clt_batch_dbg1=         gd.getNextBoolean(); // 29
     		this.clt_batch_dsi=             gd.getNextBoolean();
     		this.clt_batch_dsi_aux=         gd.getNextBoolean();
+    		this.clt_batch_dsi_aux_full=         gd.getNextBoolean();
     		this.clt_batch_save_extrinsics= gd.getNextBoolean();
     		this.clt_batch_save_all=        gd.getNextBoolean();
     		if (clt_parameters != null) {
@@ -1291,6 +1300,10 @@ public class EyesisCorrectionParameters {
     		extensions[0] = sourceSuffix;
     		prefixes[0] =   sourcePrefix;
 			MultipleExtensionsFileFilter setFilter = new MultipleExtensionsFileFilter(prefixes,extensions,"Image sets");
+			MultipleExtensionsFileFilter setFilterMain = new MultipleExtensionsFileFilter(
+					new String[] {prefixes[0]},new String[] {extensions[0]},"Image sets main");
+			MultipleExtensionsFileFilter setFilterAux = new MultipleExtensionsFileFilter(
+					new String[] {prefixes[1]},new String[] {extensions[1]},"Image sets main");
 
 	    	DirectoryChoser dc = new DirectoryChoser(
 	    			setFilter,
@@ -1319,16 +1332,27 @@ public class EyesisCorrectionParameters {
 	    	ArrayList<File>  setFilesList = new ArrayList<File>(); // list of set files
 	    	for (int nFile=0;nFile<files.length;nFile++) {
 //	    		String [] setChnFiles = files[nFile].list(setFilter);
-	    		File [] setChnFiles = files[nFile].listFiles(setFilter);
+	    		File [] setChnFiles =     files[nFile].listFiles(setFilter);
+	    		File [] setMainChnFiles = files[nFile].listFiles(setFilterMain);
+	    		File [] setAuxChnFiles =  files[nFile].listFiles(setFilterAux);
 	    		int num_match = setChnFiles.length;
-	    		if (    (num_match == num_chn_files) || // all files for main and aux
-	    				(num_match == num_chn_main) || // only main camera files
-	    				(num_match == num_chn_aux))   // only aux camera files
-	    				{ // only use sets of exact number of files
+	    		if (num_match == num_chn_files) {
+//	    			|| // all files for main and aux
+//	    				(setMainChnFiles.length == num_chn_main) || // has all needed main camera files
+//	    				(setAuxChnFiles.length == num_chn_aux))   //   has all needed camera files
+//	    				{ // only use sets of exact number of files
 	    			setDirList.add(files[nFile]);
 	    			for (File f: setChnFiles) {
 	    				setFilesList.add(f);
 	    			}
+	    		} else if ((setMainChnFiles.length == num_chn_main) || (setAuxChnFiles.length == num_chn_aux))  {
+	    			setDirList.add(files[nFile]);
+	    			if (setMainChnFiles.length == num_chn_main) {
+		    			for (File f: setMainChnFiles) setFilesList.add(f);
+	    			}
+	    			if (setAuxChnFiles.length == num_chn_aux) {
+		    			for (File f: setAuxChnFiles) setFilesList.add(f);
+	    			}
 	    		}
 	    	}
 	    	String [] sourceSetPaths = new String[setDirList.size()];

src/main/java/com/elphel/imagej/common/PolynomialApproximation.java

@@ -269,7 +269,7 @@ public class PolynomialApproximation {
 				   this.debugLevel);
 			   }
 
-	   public double [][] quadraticApproximation(
+	   public double [][] quadraticApproximation( // no use
 			   double [][][] data,
 			   boolean forceLinear,  // use linear approximation
 			   int debugLevel
@@ -312,8 +312,8 @@ public class PolynomialApproximation {
 				   1.0E-15,  // threshold ratio of matrix determinant to norm for quadratic approximation (det too low - fail)
 				   this.debugLevel);
 	   }
-
-	   public double [][] quadraticApproximation(
+/*
+	   public double [][] quadraticApproximation( // no use
 			   double [][][] data,
 			   boolean forceLinear,  // use linear approximation
 			   double thresholdLin,  // threshold ratio of matrix determinant to norm for linear approximation (det too low - fail)
@@ -328,7 +328,7 @@ public class PolynomialApproximation {
 				   1.0E-15,  // threshold ratio of matrix determinant to norm for quadratic approximation (det too low - fail)
 				   this.debugLevel);
 	   }
-
+*/
 	   public double [][] quadraticApproximation(
 			   double [][][] data,
 			   boolean forceLinear,  // use linear approximation
@@ -441,8 +441,12 @@ public class PolynomialApproximation {
 					   }
 				   }
 			   }
-
-			   int zDim=data[0][1].length;
+			   
+			   int zDim = 0; // =data[0][1].length;
+			   for (int i = 0; i < data.length; i++) if (data[i] != null){
+				   zDim =data[i][1].length;
+				   break;
+			   }
 
 			   double w,z,x,x2,x3,x4,y,y2,y3,y4,wz;
 			   int i,j,n=0;
@@ -465,7 +469,7 @@ public class PolynomialApproximation {
 				   SZ02[i]=0.0;
 				   SZ20[i]=0.0;
 			   }
-			   for (i=0;i<data.length;i++)  {
+			   for (i=0;i<data.length;i++)  if (data[i] != null){
 				   w=(data[i].length>2)? data[i][2][0]:1.0;
 				   if (w>0) {
 					   n++;
@@ -585,7 +589,7 @@ public class PolynomialApproximation {
 			   }
 			   return ABCDEF;
 		   }
-//			calcualte "volume" made of the matrix row-vectors, placed orthogonally
+//			calculate "volume" made of the matrix row-vectors, placed orthogonally
 		// to be compared to determinant
 			public double normMatix(double [][] a) {
 		        double d,norm=1.0;

src/main/java/com/elphel/imagej/tileprocessor/CLTPass3d.java

@@ -64,14 +64,15 @@ public class CLTPass3d{
 		// texture_selection is only used for the GPU and if not null means it is for the GPU
 		public boolean []       texture_selection =    null; // use by the GPU to set texture to generate
 				
-		public  double [][]      max_tried_disparity =  null; //[ty][tx] used for combined passes, shows maximal disparity for this tile, regardless of results
+		public  double [][]     max_tried_disparity =  null; //[ty][tx] used for combined passes, shows maximal disparity for this tile, regardless of results
+		public  int             clust_radius =         0;    // 0 - no clusters, 1 = 1x1 (same as 0, just different program), 2 - 3x3, 3 - 5x5
 		public  boolean         is_combo =             false;
 		public  boolean         is_measured =          false;
 		public  String          texture = null; // relative (to x3d) path
 		public  Rectangle       texture_bounds; // in tiles, not pixels !
 		public  int             dbg_index;
 		public  int             disparity_index =      ImageDtt.DISPARITY_INDEX_CM; // may also be ImageDtt.DISPARITY_INDEX_POLY
-		public   int            lma_disparity_index =  ImageDtt.DISPARITY_INDEX_POLY; // set to -1 to ignore and always use just CM (also applies to lma_strength - next)
+		public  int             lma_disparity_index =  ImageDtt.DISPARITY_INDEX_POLY; // set to -1 to ignore and always use just CM (also applies to lma_strength - next)
 		public double [][]      tiles_RBGA =           null;
 
 		SuperTiles              superTiles = null;
@@ -96,7 +97,14 @@ public class CLTPass3d{
 
 			}
 		}
-
+		public int getClustRadius() {
+			return clust_radius;
+		}
+		
+		public void setClustRadius (int clust_radius) {
+			this.clust_radius = clust_radius;
+		}
+		
 		public TileProcessor getTileProcessor()
 		{
 			return this.tileProcessor;
@@ -606,32 +614,38 @@ public class CLTPass3d{
 				return calc_disparity_combo;
 			}
 		}
+		public double [] getDisparityLMA() {
+			if (calc_disparity == null) conditionDisparity(); // sets has_lma;
+			double [] disparityLMA = calc_disparity.clone();
+			for (int i = 0; i < disparityLMA.length; i++) {
+				if (!has_lma[i]) {
+					disparityLMA[i] = Double.NaN;
+				}
+			}
+			return disparityLMA;
+		}
 
 		// methods to "condition" measured disparity values
 		public void conditionDisparity()
 		{
-/*			
-			conditionDisparity(disparity_index);
-		}
-
-		public void conditionDisparity(int disparity_index) // only called from above
-		{
-*/		
 			int tilesX = tileProcessor.getTilesX();
 			int tilesY = tileProcessor.getTilesY();
 			double corr_magic_scale =     tileProcessor.getMagicScale();
 			double corr_magic_scale_LMA = 1.0;
-//			int lma_disparity_index = ImageDtt.DISPARITY_INDEX_POLY;
-//			this.disparity_index = disparity_index;
 			calc_disparity =      new double[tilesY*tilesX];
 			calc_disparity_hor =  new double[tilesY*tilesX];
 			calc_disparity_vert = new double[tilesY*tilesX];
+			
 			double [] lma_disparity = (lma_disparity_index >= 0) ? disparity_map[lma_disparity_index] : null;
+			double [] lma_strength =  (lma_disparity_index >= 0) ? disparity_map[lma_disparity_index+1] : null;
+			has_lma = (lma_disparity != null) ? new boolean[tilesX * tilesY] : null;
+
 			for (int i = 0; i < tilesY; i++){
 				for (int j = 0; j < tilesX; j++){
 					int indx = i * tilesX + j;
-					if ((lma_disparity != null) && !Double.isNaN(lma_disparity[indx])) {
+					if ((lma_disparity != null) && !Double.isNaN(lma_disparity[indx]) && (lma_strength[indx] > 0.0)) {
 						calc_disparity[indx] =  lma_disparity[indx]/corr_magic_scale_LMA +                            this.disparity[i][j];
+						has_lma[indx] = true;
 					} else {
 						calc_disparity[indx] =  disparity_map[disparity_index][indx]/corr_magic_scale +               this.disparity[i][j];
 					}
@@ -654,10 +668,11 @@ public class CLTPass3d{
 			int tilesX = tileProcessor.getTilesX();
 			int tilesY = tileProcessor.getTilesY();
 			double [] lma_disparity = (lma_disparity_index >= 0) ? disparity_map[lma_disparity_index] : null;
+			double [] lma_strength =  (lma_disparity_index >= 0) ? disparity_map[lma_disparity_index+1] : null;
 			boolean [] lma_defined = new boolean[tilesX * tilesY];
 			if (lma_disparity != null) {
 				for (int i = 0; i < lma_disparity.length; i++) {
-					lma_defined[i] = !Double.isNaN(lma_disparity[i]);
+					lma_defined[i] = !Double.isNaN(lma_disparity[i]) && (lma_strength[i] > 0);
 				}
 			}
 			return lma_defined;

src/main/java/com/elphel/imagej/tileprocessor/ExtrinsicAdjustment.java

@@ -2439,7 +2439,7 @@ public class ExtrinsicAdjustment {
 					this.last_ymfx); // modifies this.last_ymfx (weights and subtracts fx)
 			this.initial_rms = this.last_rms.clone();
 			this.good_or_bad_rms = this.last_rms.clone();
-			if (debug_level > -1) {
+			if (debug_level > 1) {
 				showDerivatives(0);
 				showDerivatives(1);
 				showDerivatives(2);