Debugging LMA-based LY measurement, added initial LY estimation, more (2a11eb19) · Commits · Elphel / imagej-elphel

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

+44 −5

Original line number	Diff line number	Diff line
		@@ -301,6 +301,13 @@ public class CLTParameters {
		private double lym_change_aux = 1e-4; // same for aux camera (currntly)lwir
		public double lym_poly_change = 0.002; // Parameter vector difference to exit from polynomial correction

		public boolean lym_mod_map = true; // Modify preliminary disparity map before running LY
		public boolean lym_top_bg = true; // All above found BG is also BG (valid for most, but not all scenes)
		public int lym_fill_gaps_bg = 0; // fill small gaps in found background
		public int lym_fill_gaps_combo = 2; // 1 - in 4 directions by 1, 2 - in 8 directions by 1,
		public boolean lym_use_strength = true; // Use strength when averaging disparity from neighbors
		public double lym_scale_deriv_str=0.5; // Scale strength of the interpolated tiles from average neighbors strength

		public boolean lyf_filter = false; // Filter lazy eye pairs by their values
		public int lyf_smpl_side = 3; // 8 x8 masked, 16x16 sampled
		public double lyf_rms_max = 0.1; // Maximal RMS (all components to components average)
		@@ -1190,15 +1197,20 @@ public class CLTParameters {
		properties.setProperty(prefix+"ly_disp_rvar_gt", this.ly_disp_rvar_gt +"");
		properties.setProperty(prefix+"ly_norm_disp", this.ly_norm_disp +"");
		properties.setProperty(prefix+"lym_overexp", this.lym_overexp +"");

		properties.setProperty(prefix+"lym_dbg_path", this.lym_dbg_path +"");

		properties.setProperty(prefix+"lym_update_disp", this.lym_update_disp+"");
		properties.setProperty(prefix+"lym_iter", this.lym_iter+"");
		properties.setProperty(prefix+"lym_change", this.lym_change +"");
		properties.setProperty(prefix+"lym_change_aux", this.lym_change_aux +"");
		properties.setProperty(prefix+"lym_poly_change", this.lym_poly_change +"");

		properties.setProperty(prefix+"lym_mod_map", this.lym_mod_map +"");
		properties.setProperty(prefix+"lym_top_bg", this.lym_top_bg +"");
		properties.setProperty(prefix+"lym_fill_gaps_bg", this.lym_fill_gaps_bg +"");
		properties.setProperty(prefix+"lym_fill_gaps_combo", this.lym_fill_gaps_combo +"");
		properties.setProperty(prefix+"lym_use_strength", this.lym_use_strength +"");
		properties.setProperty(prefix+"lym_scale_deriv_str", this.lym_scale_deriv_str +"");

		properties.setProperty(prefix+"lyf_filter", this.lyf_filter+"");
		properties.setProperty(prefix+"lyf_smpl_side", this.lyf_smpl_side+"");
		properties.setProperty(prefix+"lyf_rms_max", this.lyf_rms_max +"");
		@@ -2007,9 +2019,15 @@ public class CLTParameters {
		if (properties.getProperty(prefix+"lym_iter")!=null) this.lym_iter=Integer.parseInt(properties.getProperty(prefix+"lym_iter"));
		if (properties.getProperty(prefix+"lym_change")!=null) this.lym_change=Double.parseDouble(properties.getProperty(prefix+"lym_change"));
		if (properties.getProperty(prefix+"lym_change_aux")!=null) this.lym_change_aux=Double.parseDouble(properties.getProperty(prefix+"lym_change_aux"));

		if (properties.getProperty(prefix+"lym_poly_change")!=null) this.lym_poly_change=Double.parseDouble(properties.getProperty(prefix+"lym_poly_change"));

		if (properties.getProperty(prefix+"lym_mod_map")!=null) this.lym_mod_map=Boolean.parseBoolean(properties.getProperty(prefix+"lym_mod_map"));
		if (properties.getProperty(prefix+"lym_top_bg")!=null) this.lym_top_bg=Boolean.parseBoolean(properties.getProperty(prefix+"lym_top_bg"));
		if (properties.getProperty(prefix+"lym_fill_gaps_bg")!=null) this.lym_fill_gaps_bg=Integer.parseInt(properties.getProperty(prefix+"lym_fill_gaps_bg"));
		if (properties.getProperty(prefix+"lym_fill_gaps_combo")!=null) this.lym_fill_gaps_combo=Integer.parseInt(properties.getProperty(prefix+"lym_fill_gaps_combo"));
		if (properties.getProperty(prefix+"lym_use_strength")!=null) this.lym_use_strength=Boolean.parseBoolean(properties.getProperty(prefix+"lym_use_strength"));
		if (properties.getProperty(prefix+"lym_scale_deriv_str")!=null) this.lym_scale_deriv_str=Double.parseDouble(properties.getProperty(prefix+"lym_scale_deriv_str"));

		if (properties.getProperty(prefix+"lyf_filter")!=null) this.lyf_filter=Boolean.parseBoolean(properties.getProperty(prefix+"lyf_filter"));
		if (properties.getProperty(prefix+"lyf_smpl_side")!=null) this.lyf_smpl_side=Integer.parseInt(properties.getProperty(prefix+"lyf_smpl_side"));
		if (properties.getProperty(prefix+"lyf_rms_max")!=null) this.lyf_rms_max=Double.parseDouble(properties.getProperty(prefix+"lyf_rms_max"));
		@@ -2908,9 +2926,23 @@ public class CLTParameters {
		gd.addNumericField("Maximal number of iterations", this.lym_iter, 0);
		gd.addNumericField("Parameter vector difference to exit (main camera)", this.lym_change, 10,12,"");
		gd.addNumericField("Parameter vector difference to exit (aux camera)", this.lym_change_aux, 10,12,"");

		gd.addNumericField("Parameter vector difference to exit from polynomial correction", this.lym_poly_change, 10);

		gd.addMessage ("--- Lazy eye data preparation ---");
		gd.addCheckbox ("Modify preliminary disparity map before running LY", this.lym_mod_map,
		"LY may tolerate some disparity errors when just pure LY is needed");
		gd.addCheckbox ("Consider all above infinity to be infinity", this.lym_top_bg,
		"Valid for many, but not all scenes, such as tree branches over sky background");
		gd.addNumericField("Fill gaps in background selection", this.lym_fill_gaps_bg, 0, 2, "pix",
		"1 - 1 pixel in 4 directions, 2 - 1 step in 8 directions, ...");
		gd.addNumericField("Fill gaps in combo selection", this.lym_fill_gaps_combo, 0, 2, "pix",
		"1 - 1 pixel in 4 directions, 2 - 1 step in 8 directions, ...");
		gd.addCheckbox ("Use strength when averaging disparity from neighbors", this.lym_use_strength,
		"Weight by strength when averaging missing disparity tiles, false - use equal weights");
		gd.addNumericField("Scale strength of the interpolated tiles from average neighbors strength", this.lym_scale_deriv_str, 3, 6, "",
		"Multiply average strength of neighbors when assigning to a missing tile");


		gd.addMessage ("--- Lazy eye samples filter ---");
		gd.addCheckbox ("Filter lazy eye pairs by their values", this.lyf_filter);
		gd.addNumericField("Fileter sample side (if 8, 8 x8 masked, 16x16 sampled)", this.lyf_smpl_side, 0);
		@@ -3851,6 +3883,13 @@ public class CLTParameters {

		this.lym_poly_change= gd.getNextNumber();

		this.lym_mod_map= gd.getNextBoolean();
		this.lym_top_bg= gd.getNextBoolean();
		this.lym_fill_gaps_bg = (int) gd.getNextNumber();
		this.lym_fill_gaps_combo = (int) gd.getNextNumber();
		this.lym_use_strength= gd.getNextBoolean();
		this.lym_scale_deriv_str = gd.getNextNumber();

		this.lyf_filter= gd.getNextBoolean();
		this.lyf_smpl_side= (int) gd.getNextNumber();
		this.lyf_rms_max= gd.getNextNumber();

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

+5 −0

Original line number	Diff line number	Diff line
		@@ -504,6 +504,11 @@ public class CLTPass3d{
		}
		return strength;
		}

		public void setStrength(double [] strength) {
		this.strength = strength;
		}

		/**
		* Get four pairs (original) correlation strength. Not a copy
		* @return line-scan array of per-tile horizontal pairs correlation strength by reference (not a copy)

src/main/java/com/elphel/imagej/tileprocessor/Corr2dLMA.java

+515 −38

File changed.

Preview size limit exceeded, changes collapsed.

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

+9 −3

Original line number	Diff line number	Diff line
		@@ -597,8 +597,11 @@ public class CorrVector{ // TODO: Update to non-quad (extract to a file first)?
		}

		@Override
		public String toString() // USED in lwir
		{
		public String toString() { // USED in lwir
		return toString(false);
		}

		public String toString(boolean short_out) {
		String s;
		double [] sym_vect = toSymArray(null);
		double [] v = new double [vector.length];
		@@ -649,6 +652,9 @@ public class CorrVector{ // TODO: Update to non-quad (extract to a file first)?
		s+= "azimuth (right):"; for (int i = 0; i < n; i++) s += String.format(" %8.4fpx", azimuths[i]); s+=" (shift of the image center)\n";
		s+= "roll (CW): "; for (int i = 0; i < n; i++) s += String.format(" %8.4fpx", rolls[i]); s+=" (shift at the image half-width from the center)\n";
		s+= "diff zoom (in): "; for (int i = 0; i < n; i++) s += String.format(" %8.4fpx", zooms[i]); s+=" (shift at the image half-width from the center)\n";
		if (short_out) {
		return s;
		}
		s += "Symmetrical vector:\n";
		if (getNumSensors() == 4) { // Use arrows for quad camera only (but update to match new
		// ← → ↑ ↓ ⇖ ⇗ ⇘ ⇙ ↔ ↺ ↻

src/main/java/com/elphel/imagej/tileprocessor/Correlation2d.java

+110 −13

Original line number	Diff line number	Diff line
		@@ -2120,6 +2120,45 @@ public class Correlation2d {
		}
		return rslt;
		}

		/**
		* Get fractional center as a "center of mass" for all pixels
		* Data should be masked by the caller
		* @param data correlation data [(2 * transform_size - 1) * (2 * transform_size - 1)]
		* @param data_width
		* @param center_row
		* @param debug
		* @return argmax() relative to the tile center
		*/

		public double [] getMaxXYCm( // not used in lwir
		double [] data,
		int data_width, // = 2 * transform_size - 1;
		int center_row,
		boolean debug)
		{
		int data_height = data.length/data_width;
		int center_x = (data_width - 1)/2; // = transform_size - 1;
		//calculate as "center of mass"
		double s0 = 0, sx=0,sy = 0;
		for (int iy = 0; iy < data_height; iy++) {
		double y = iy - center_row;
		for (int ix = 0; ix < data_width; ix++) {
		double x = ix - center_x;
		double d = data[iy * data_width + ix];
		s0 += d;
		sx += d * x;
		sy += d * y;
		}
		}
		double [] rslt = {sx / s0, sy / s0};
		if (debug){
		System.out.println("getMaxXYCm() -> "+rslt[0]+":"+rslt[1]);
		}
		return rslt;
		}


		/**
		* Calculate 1-d maximum location, strength and half-width for the special strip (odd rows shifted by 0.5
		* Negative values are ignored!
		@@ -3430,7 +3469,6 @@ public class Correlation2d {
		imgdtt_params.lma_adjust_wy, // boolean adjust_ellipse, // allow non-circular correlation maximums lma_adjust_wy
		true, // imgdtt_params.lma_adjust_wxy, // boolean adjust_lazyeye_par, // adjust disparity corrections parallel to disparities lma_adjust_wxy
		true, // imgdtt_params.lma_adjust_ly1, // boolean adjust_lazyeye_ortho, // adjust disparity corrections orthogonal to disparities lma_adjust_ly1

		ds, // disp_str, // xcenter_str, // double [][] disp_str, // initial value of disparity/strength/?
		imgdtt_params.lma_half_width, // double half_width, // A=1/(half_widh)^2 lma_half_width
		imgdtt_params.lma_cost_wy, // double cost_lazyeye_par, // cost for each of the non-zero disparity corrections lma_cost_wy
		@@ -3600,7 +3638,7 @@ public class Correlation2d {


		double [][] dbg_corr = debug_graphic ? new double [corrs.length][] : null;
		double [][] dbg_weights = debug_graphic ? new double [corrs.length][] : null;
		// double [][] dbg_weights = debug_graphic ? new double [corrs.length][] : null;
		if (debug_graphic) {
		(new ShowDoubleFloatArrays()).showArrays(
		corrs,
		@@ -3614,6 +3652,7 @@ public class Correlation2d {


		// for (int npair = 0; npair < corrs.length; npair++) if ((corrs[npair] != null) && (((pair_mask >> npair) & 1) !=0)){
		double [][] filtWeight = new double [corrs.length][];
		for (int npair = 0; npair < corrs.length; npair++) if ((corrs[npair] != null) && (pair_mask[npair])){

		// double[] corr = corrs[npair].clone();
		@@ -3638,7 +3677,7 @@ public class Correlation2d {
		// filter convex
		int ix0 = (imx % corr_size) - center; // signed, around center to match filterConvex
		int iy0 = (imx / corr_size) - center; // signed, around center to match filterConvex
		double [] filtWeight = filterConvex(
		filtWeight[npair] = filterConvex(
		corr_blur, // double [] corr_data,
		imgdtt_params.cnvx_hwnd_size, // int hwin,
		ix0, // int x0,
		@@ -3647,17 +3686,17 @@ public class Correlation2d {
		imgdtt_params.cnvx_weight, // double nc_cost,
		(debug_level > 2)); // boolean debug);
		if (dbg_corr != null) dbg_corr [npair] = corr_blur;
		if (dbg_weights != null) dbg_weights[npair] = filtWeight;
		// if (dbg_weights != null) dbg_weights[npair] = filtWeight[npair];

		// Normalize weight for each pair to compensate for different number of convex samples?

		// int fcam = PAIRS[npair][0];
		// int scam = PAIRS[npair][1];
		for (int i = 1; i < filtWeight.length; i++) if (filtWeight[i] > 0.0) {
		for (int i = 1; i < filtWeight[npair].length; i++) if (filtWeight[npair][i] > 0.0) {
		int ix = i % corr_size; // >=0
		int iy = i / corr_size; // >=0
		double v = corrs[npair][i]; // not blurred
		double w = filtWeight[i];
		double w = filtWeight[npair][i];
		if (vasw_pwr != 0) {
		w *= Math.pow(Math.abs(v), vasw_pwr);
		}
		@@ -3685,7 +3724,7 @@ public class Correlation2d {
		getCorrTitles());

		(new ShowDoubleFloatArrays()).showArrays(
		dbg_weights,
		filtWeight,
		corr_size,
		corr_size,
		true,
		@@ -3699,22 +3738,45 @@ public class Correlation2d {
		disp_str2[0] = disp_str;
		}
		// double [][] disp_str2 = {{0.0, 1.0}}; // temporary // will be calculated/set later



		boolean lmaSuccess = false;
		double [] disp = null;
		// adjust_ly
		double [][] ly_offsets_pairs = null;
		if (adjust_ly) {
		ly_offsets_pairs = getPairsCenters(
		corrs, // double [][] corrs,
		filtWeight); // double [][] weights)
		}
		double step_weight = 0.5; // scale corrections
		double min_correction = 0.1; // exit when maximal XY correction is below

		while (!lmaSuccess) {
		lma.initVector( // USED in lwir
		lma.initVector(
		imgdtt_params.lmas_adjust_wm, // boolean adjust_width, // adjust width of the maximum - lma_adjust_wm
		imgdtt_params.lmas_adjust_ag, // boolean adjust_scales, // adjust 2D correlation scales - lma_adjust_ag
		imgdtt_params.lmas_adjust_wy, // boolean adjust_ellipse, // allow non-circular correlation maximums lma_adjust_wy
		(adjust_ly ? imgdtt_params.lma_adjust_wxy : false), //imgdtt_params.lma_adjust_wxy, // boolean adjust_lazyeye_par, // adjust disparity corrections parallel to disparities lma_adjust_wxy
		(adjust_ly ? imgdtt_params.lma_adjust_ly1: false), // imgdtt_params.lma_adjust_ly1, // boolean adjust_lazyeye_ortho, // adjust disparity corrections orthogonal to disparities lma_adjust_ly1
		disp_str2, // xcenter, // double disp0, // initial value of disparity
		disp_str2, // xcenter,
		imgdtt_params.lma_half_width, // double half_width, // A=1/(half_widh)^2 lma_half_width
		(adjust_ly ? imgdtt_params.lma_cost_wy : 0.0), // imgdtt_params.lma_cost_wy, // double cost_lazyeye_par, // cost for each of the non-zero disparity corrections lma_cost_wy
		(adjust_ly ? imgdtt_params.lma_cost_wxy : 0.0) //imgdtt_params.lma_cost_wxy // double cost_lazyeye_odtho // cost for each of the non-zero ortho disparity corrections lma_cost_wxy
		);

		lma.setMatrices(disp_dist);
		lma.initMatrices(); // should be called after initVector and after setMatrices
		boolean all_sensors_used = lma.setInitialLYOffsets(
		ly_offsets_pairs, // double [][] pair_centers,
		step_weight, // double step_weight, // scale corrections
		min_correction, // double min_correction ){ // exit when maximal XY correction is below
		(debug_level > 0)); //
		if (adjust_ly && !all_sensors_used) {
		return null; //LY requested, but not all sensors present
		}

		//center
		disp = null;
		if (need_poly) {
		@@ -3724,8 +3786,15 @@ public class Correlation2d {
		debug_graphic?dbg_title:null); // double [] rslt = {-approx2d[0], approx2d[2], hwx, hwy};

		if (disp == null) {
		if (imgdtt_params.lmas_poly_continue && (disp == null)) {
		disp = disp_str2[0];
		if (debug_level > 0) {
		System.out.println("Poly disparity=NULL");
		System.out.println("Poly disparity=NULL, using tile center for initial LMA");
		}
		} else {
		if (debug_level > 0) {
		System.out.println("Poly disparity=NULL, set lmas_poly_continue to true to use tile center instead");
		}
		}
		} else {
		disp[1] *= imgdtt_params.lmas_poly_str_scale;
		@@ -3748,6 +3817,9 @@ public class Correlation2d {
		} else {
		disp = disp_str;
		}



		if (disp != null) {
		disp_str2[0] = disp;
		lma.initDisparity( // USED in lwir
		@@ -3785,7 +3857,7 @@ public class Correlation2d {
		lma.updateFromVector();


		double [][] dispStr = lma.lmaDisparityStrength(
		double [][] dispStr = lma.lmaDisparityStrength( //TODO: add parameter to filter out negative minimums ?
		imgdtt_params.lmas_max_rel_rms, // maximal relative (to average max/min amplitude LMA RMS) // May be up to 0.3)
		imgdtt_params.lmas_min_strength, // minimal composite strength (sqrt(average amp squared over absolute RMS)
		imgdtt_params.lmas_min_ac, // minimal of A and C coefficients maximum (measures sharpest point/line)
		@@ -3846,6 +3918,31 @@ public class Correlation2d {
		return lmaSuccess? lma: null;
		}

		public double [][] getPairsCenters(
		double [][] corrs,
		double [][] weights){
		double [][] xy_offsets_pairs = new double[corrs.length][]; //
		for (int np = 0; np < corrs.length; np++) if (corrs[np]!= null) {
		double [] wcorr = new double [corrs[np].length];
		double pair_weights = 0.0;
		for (int i = 0; i < wcorr.length; i++) if (weights[np][i] > 0.0){
		wcorr[i] = corrs[np][i]*weights[np][i];
		pair_weights += wcorr [i];
		}
		double [] dxy = getMaxXYCm(
		wcorr, // double [] data,
		getCombWidth(), // data_width,
		getCombHeight()/2 - getCombOffset(), // int center_row
		false); // boolean debug)
		xy_offsets_pairs[np] = new double[3];
		xy_offsets_pairs[np][0] = dxy[0];
		xy_offsets_pairs[np][1] = dxy[1];
		xy_offsets_pairs[np][2] = pair_weights;
		}
		return xy_offsets_pairs;
		}



		public Correlations2dLMA corrLMA( // USED in lwir
		ImageDttParameters imgdtt_params,

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