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Commit 86efce83 authored by Andrey Filippov's avatar Andrey Filippov
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Extracting radial pattern

parent 8667ae4b
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Showing with 786 additions and 65 deletions
src/main/java/com/elphel/imagej/orthomosaic/ComboMatch.java
View file @ 86efce83
......@@ -46,7 +46,7 @@ public class ComboMatch {
public static boolean openTestPairGps(
CLTParameters clt_parameters,
GPUTileProcessor gpu_tile_processor, // initialized by the caller
boolean extract_mines,
boolean extract_objects,
int debugLevel) {
GPU_TILE_PROCESSOR = gpu_tile_processor;
PairwiseOrthoMatch pairwiseOrthoMatch = null;
......@@ -55,6 +55,19 @@ public class ComboMatch {
String [] gpu_spair = null;
boolean use_marked_image = false; // will be set if found
String [] all_scenes = null;
ArrayList<ObjectLocation> object_list = null;
int zool_lev_objects = 0;
if (extract_objects) {
if (imp_sel == null) {
System.out.println("Need multi-sliced image with marked objects as points");
return false;
}
int [] zoom_lev_objectsp = new int [1];
object_list = getObjectsFromSelectedImage(
imp_sel,
zoom_lev_objectsp); // ImagePlus imp)
zool_lev_objects = zoom_lev_objectsp[0];
} else {
if (imp_sel != null) {
pair_names = new String[2];
String [][] all_scenes1=new String[1][];
......@@ -68,6 +81,7 @@ public class ComboMatch {
all_scenes = all_scenes1[0];
}
}
}
// find -L /media/elphel/SSD3-4GB/lwir16-proc/berdich3/linked/linked_1697875868-1697879449-b/ -type f -name "*-GCORR-GEO.tiff" | sort > GCORR-GEO.list
// String files_list_path = "/media/elphel/SSD3-4GB/lwir16-proc/ortho_videos/maps_03_short.list";
......@@ -254,6 +268,236 @@ public class ComboMatch {
maps_collection = new OrthoMapsCollection(files_list_path); // should have ".list" extension
}
String [] names = maps_collection.getNames();
if (object_list != null) {
int corr_size = 128;
int extr_size = 200; // 256;
int zoomout = 2; // 1; //2; // 1; 2 for simulated,1 - for extracted
int patt_choice = 3;
double phaseCoeff = 0.98;
double min_corr = 0.01; // 0.0025; // real max >0.005 with scale -500000;
int radius_search = 32;
int radius_centroid = 4;
double lim_rad = 80; // 60; // 40; // 50.0;
double trans_width = 60; // 40; // 20.0;
double reversal_rad = 0; // 26;// 22; // cut at first direction reversal after
double frac_outliers = 0.4;
int default_kernel = 1; // 0; // 1; // default kernel choice 25-> 50// 1 for simulated, 0 - for extracted
boolean only_correlate = true;
int sub_pattern_index = 0;
// String pattern_dir= "/media/elphel/SSD3-4GB/lwir16-proc/ortho_videos/debug/mines/pattern_25m_zoom1/synthetic/";
String pattern_dir= "/media/elphel/NVME/lwir16-proc/ortho_videos/mines_extract/evening_50m_sept12/debug_cross/new_synth/";
String [] pattern_files={
"patterns_r30.0_e8.0_ir10.0_ie8.0_is-0.1_or45.0_oe30.0_os-1.5_h8_w0.6_s-40.0_200x200.tif",
"old_02.tiff",
"patterns_r30.0_e24.0_ir10.0_ie8.0_is-0.1_or62.0_oe40.0_os-1.0_h8_w0.6_s-60.0_200x200.tif",
"patterns_r30.0_e8.0_ir10.0_ie8.0_is-0.1_or45.0_oe30.0_os-1.0_h8_w0.6_s-60.0_200x200.tif",
"patterns_r30.0_e8.0_ir10.0_ie8.0_is0.0_or45.0_oe30.0_os-1.0_h8_w0.6_s-60.0_200x200.tif",
"patterns_r30.0_e6.0_ir10.0_ie8.0_is0.0_or45.0_oe30.0_os-1.0_h8_w0.6_s-60.0_200x200.tif",
"patterns_r30.0_e6.0_ir10.0_ie6.0_is-1.0_or45.0_oe30.0_os-1.0_h8_w0.6_s-60.0_200x200.tif",
"patterns_r30.0_e6.0_ir10.0_ie6.0_is-0.8_or45.0_oe30.0_os-1.0_h8_w0.6_s-60.0_200x200.tif",
"patterns_r30.0_e4.0_ir10.0_ie4.0_is-1.0_or45.0_oe30.0_os-1.0_h8_w0.6_s-60.0_200x200.tif",
"patterns_r30.0_e5.0_ir12.0_ie5.0_is-1.0_or45.0_oe30.0_os-1.0_h8_w0.6_s-60.0_200x200.tif",
"patterns_r30.0_e5.0_ir12.0_ie5.0_is-1.0_or45.0_oe20.0_os-1.0_h8_w0.6_s-60.0_200x200.tif",
"patterns_r30.0_e5.0_ir12.0_ie5.0_is-1.0_or50.0_oe40.0_os-1.0_h8_w0.6_s-60.0_200x200.tif", // best
"patterns_r30.0_e5.0_ir12.0_ie5.0_is-1.0_or55.0_oe50.0_os-1.0_h8_w0.6_s-60.0_200x200.tif",
"patterns_r30.0_e5.0_ir12.0_ie5.0_is0.0_or50.0_oe40.0_os-1.0_h8_w0.6_s-60.0_200x200.tif"
};
GenericJTabbedDialog gdo = new GenericJTabbedDialog("Set image pair",1200,900);
gdo.addNumericField("Correlation size", corr_size, 0,4,"",
"Correlation size, power of 2");
gdo.addNumericField("Extracted size", extr_size, 0,4,"",
"size of a square output size");
// gdo.addStringField ("Pattern directory", OrthoMap.pattern_dir, 180, "Absolute path including trailing \"/\".");
// gdo.addChoice ("Pattern filename:", OrthoMap.pattern_files, OrthoMap.pattern_files[patt_choice]);
gdo.addStringField ("Pattern directory", pattern_dir, 180, "Absolute path including trailing \"/\".");
gdo.addChoice ("Pattern filename:", pattern_files, OrthoMap.pattern_files[patt_choice]);
gdo.addNumericField("Zoom-out factor", zoomout, 0,4,"x", "Reduce pattern resolution to match image.");
gdo.addNumericField("Phase correlation coefficient", phaseCoeff, 3,7,"","1.0 - pure phase correlation, 0.0 - regular correlation.");
gdo.addNumericField("Minimal correlation", min_corr, 5,7,"","Minimal correlation value to keep.");
gdo.addNumericField("Search radius", radius_search, 0,4,"pix", "Radius to search for the object center.");
gdo.addNumericField("Centroid radius", radius_centroid, 0,4,"pix", "Limit centroid radius.");
gdo.addMessage("Clean-up circular pattern:");
gdo.addNumericField("Limit output patter radius", lim_rad, 0,4,"pix", "All zero outside this radius.");
gdo.addNumericField("Transition width", trans_width, 0,4,"pix", "cosine transition width.");
gdo.addNumericField("Last reversal radius", reversal_rad, 0,4,"pix", "Cut at first derivative reversal after this.");
gdo.addNumericField("Outlier fraction", frac_outliers, 3,7,"", "Remove outliers when averaging different directions.");
gdo.addCheckbox ("Only correlate", only_correlate, "do not generate circular kernel.");
gdo.addNumericField("subpattern index", sub_pattern_index,0,4,"", "0 - full pattern, 1-8 - half-pattern.");
//only_correlate
gdo.showDialog();
if (gdo.wasCanceled()) return false;
corr_size = (int) gdo.getNextNumber();
extr_size = (int) gdo.getNextNumber();
// OrthoMap.pattern_dir= gdo.getNextString();
// String pattern_file = OrthoMap.pattern_files[gdo.getNextChoiceIndex()];
pattern_dir= gdo.getNextString();
String pattern_file = pattern_files[gdo.getNextChoiceIndex()];
zoomout= (int) gdo.getNextNumber();
phaseCoeff= gdo.getNextNumber();
min_corr= gdo.getNextNumber();
radius_search= (int) gdo.getNextNumber();
radius_centroid= (int) gdo.getNextNumber();
lim_rad= gdo.getNextNumber();
trans_width= gdo.getNextNumber();
reversal_rad= gdo.getNextNumber();
frac_outliers= gdo.getNextNumber();
only_correlate = gdo.getNextBoolean();
sub_pattern_index= (int) gdo.getNextNumber();
System.out.println("Will extract objects here, image zoom_level="+zool_lev_objects);
for (ObjectLocation ol: object_list) {
System.out.println(ol.name+": "+ol.xy_meters[0]+"/"+ol.xy_meters[1]);
}
maps_collection.reverseRender(
object_list, // ArrayList<ObjectLocation> objects,
zool_lev_objects); // int zoom_level){
System.out.println("Object coordinates in source images: ");
for (ObjectLocation ol: object_list) {
System.out.println(ol.name+": "+ol.getPixels()[0]+"/"+ol.getPixels()[1]);
}
double [][] object_stack = new double [object_list.size()][];
String [] object_titles = new String [object_stack.length];
for (int i = 0; i < object_stack.length; i++) {
ObjectLocation ol = object_list.get(i);
object_titles[i] = ol.getName();
object_stack[i] = ol.extractObjectImage(
maps_collection,
extr_size);
}
ImagePlus imp_obj = ShowDoubleFloatArrays.makeArrays(
object_stack,
extr_size,
extr_size,
OrthoMap.removeKnownExtension(imp_sel.getTitle())+"-OBJECT_"+extr_size+"x"+extr_size+".tiff",
object_titles); // test_titles,
imp_obj.show();
// get pattern(s)
// String pattern_path=OrthoMap.pattern_dir+pattern_file;
String pattern_path=pattern_dir+pattern_file;
ImagePlus imp_pattern = new ImagePlus(pattern_path);
int pattern_size = imp_pattern.getWidth();
if (pattern_size == 0) {
System.out.println("testPatternCorrelate(): pattern \""+pattern_path+"\" is not found.");
return false;
}
System.out.println("Using pattern file: "+pattern_path+", subpattern="+sub_pattern_index);
ImageStack stack_pattern = imp_pattern.getStack();
int nSlices = stack_pattern.getSize();
double [][] patterns = new double[nSlices][];
String [] pattern_labels = new String[nSlices];
for (int n = 0; n < patterns.length; n++) {
pattern_labels[n]=stack_pattern.getShortSliceLabel(n+1);
float [] fpixels_pattern = (float[]) stack_pattern.getPixels(n+1);
patterns[n]=new double[fpixels_pattern.length];
for (int i = 0; i < fpixels_pattern.length; i++) {
patterns[n][i] = fpixels_pattern[i];
}
}
double [] kernel = OrthoMap.getConvolutionKernel(default_kernel);
double [][] centers = new double [object_stack.length][];
for (int i = 0; i < object_stack.length; i++) {
String dbg_prefix = "corr_patt_"+i;
ObjectLocation ol = object_list.get(i);
centers[i] = ObjectLocation.getPatternCenter(
object_stack[i], // double [] data,
patterns[sub_pattern_index], // double [] pattern,
kernel, // double [] kernel,
zoomout, // int zoomout,
phaseCoeff, // double phaseCoeff,
min_corr, // double min_corr,
radius_search, // int radius_search,
radius_centroid, // int radius_centroid,
dbg_prefix, // String dbg_prefix,
debugLevel); // int debugLevel)
System.out.println(i+": center at "+centers[i][0]+"/"+centers[i][1]+", strength="+centers[i][2]);
}
PointRoi roi = new PointRoi();
roi.setOptions("label");
for (int i = 0; i < centers.length; i++) {
roi.addPoint(centers[i][0]+extr_size/2, centers[i][1]+extr_size/2, i+1); // ,1);
}
imp_obj.setRoi(roi);
if (only_correlate) {
System.out.println("testPatternCorrelate(): correlation DONE, only_correlate is set to true, exiting");
return true;
}
// imp_obj.show();
// First process each captured object separately, then compare and average?
// TODO: use finer grid, deconvolve with altitude kernel, calculate effective width of the pattern
double [][] output_patterns = new double [object_stack.length+1][];
String [] output_patt_titles = new String[output_patterns.length];
output_patt_titles[output_patt_titles.length-1]= "average";
output_patterns[object_stack.length] = new double [corr_size*corr_size];
//object_titles
boolean debug_good = debugLevel > -4;
boolean [][] good_pix = debug_good ? (new boolean[object_stack.length][extr_size*extr_size]) : null; // debugging
String settings_str = "_fo"+frac_outliers+"_lr"+lim_rad+"_tw"+trans_width+"_rr"+reversal_rad;
for (int i = 0; i < object_stack.length; i++) {
output_patterns[i] = ObjectLocation.getRadialPattern(
object_stack[i], // double [] data,
centers[i], // double [] xy_offs,
corr_size, // int corr_size,
lim_rad, // double lim_rad, // outside all 0
trans_width, //double trans_width, // lim_rad-trans_width - start reducing
frac_outliers, // double frac_outliers,
reversal_rad, // double reversal_rad,
((good_pix != null)? good_pix[i] : null), // boolean [] good, // null or same size as data
debugLevel); // int debugLevel)
output_patt_titles[i] = object_titles[i];
for (int j = 0; j < output_patterns[i].length; j++) {
output_patterns[object_stack.length][j] += output_patterns[i][j];
}
}
for (int j = 0; j < output_patterns[0].length; j++) {
output_patterns[object_stack.length][j] /= object_stack.length;
}
ImagePlus imp_out_patt = ShowDoubleFloatArrays.makeArrays(
output_patterns,
corr_size,
corr_size,
OrthoMap.removeKnownExtension(imp_sel.getTitle())+"-PATTERN"+settings_str+"_"+corr_size+"x"+corr_size+".tiff",
output_patt_titles); // test_titles,
imp_out_patt.show();
if (good_pix != null) {
double [][] object_stack_masked = new double [2 * object_stack.length][];
String [] object_titles_masked = new String [2 * object_stack.length];
PointRoi roi_masked = new PointRoi();
roi_masked.setOptions("label");
for (int i = 0; i < centers.length; i++) {
roi_masked.addPoint(centers[i][0]+extr_size/2, centers[i][1]+extr_size/2, 2*i+1); // ,1);
roi_masked.addPoint(centers[i][0]+extr_size/2, centers[i][1]+extr_size/2, 2*i+2); // ,1);
}
for (int i = 0; i < object_stack.length; i++) {
object_stack_masked[2*i + 0] = object_stack[i];
object_stack_masked[2*i + 1] = object_stack[i].clone();
for (int j = 0; j < object_stack[i].length; j++) {
if (!good_pix[i][j]) {
object_stack_masked[2*i + 1][j] = Double.NaN;
}
}
}
ImagePlus imp_obj_masked = ShowDoubleFloatArrays.makeArrays(
object_stack_masked,
extr_size,
extr_size,
OrthoMap.removeKnownExtension(imp_sel.getTitle())+"-OBJECT_MASKED"+settings_str+"_"+extr_size+"x"+extr_size+".tiff",
object_titles_masked); // test_titles,
imp_obj_masked.setRoi(roi_masked);
imp_obj_masked.show();
}
return true;
}
if (use_marked_image) {
// verify matching names
//all_scenes
......@@ -691,6 +935,50 @@ adjusted affines[1] for a pair: 1694564291_293695/1694564778_589341
return null;
}
public static ArrayList<ObjectLocation> getObjectsFromSelectedImage(
ImagePlus imp,
int [] zoom_levp) {
// get zoom from the name and list of the slice names prefixes (before second "_"
String title = imp.getTitle();
String[] tokens = title.replace(".","_").split("_");
for (int i = 0; i < tokens.length; i++) {
if (tokens[i].startsWith("zoom")) {
int zoom_level = Integer.parseInt(tokens[i].substring(4));
System.out.println("zoom level = "+zoom_level);
double pix_size = OrthoMap.getPixelSizeMeters (zoom_level); // meters
ImageStack stack_scenes = imp.getStack();
int nSlices = stack_scenes.getSize();
String [] scene_names = new String [nSlices];
for (int n = 0; n < scene_names.length; n++) {
scene_names[n] = stack_scenes.getSliceLabel(n+1).substring(0,17);
}
PointRoi pRoi = (PointRoi) imp.getRoi();
FloatPolygon fp = pRoi.getContainedFloatPoints();
// Use only 2 last markers
if (fp == null) {
System.out.println("getPairFromSelectedImage(): no markers found");
return null;
}
ArrayList<ObjectLocation> list = new ArrayList<ObjectLocation>();
for (int np = 0; np < fp.npoints; np++) {
String name = scene_names[pRoi.getPointPosition(np) -1];
double [] xy_meters = {
fp.xpoints[np] * pix_size,
fp.ypoints[np] * pix_size};
list.add(new ObjectLocation (
name, // String name,
xy_meters)); // double [] xy_meters)
}
if (zoom_levp != null) {
zoom_levp[0] = zoom_level;
}
return list;
}
}
return null;
}
public static String [] getPairChoices(
int [][] pairs,
String [] names) {
......@@ -703,18 +991,6 @@ adjusted affines[1] for a pair: 1694564291_293695/1694564778_589341
/*
public static TDCorrTile [] rectilinearCorrelate_TD( // scene0/scene1
final CLTParameters clt_parameters,
final float [][] fpixels, // to check for empty
final int img_width,
Rectangle woi, // if null, use full GPU window
final double [][][] affine, // [2][2][3] affine coefficients to translate common to 2 images
final boolean batch_mode,
final int debugLevel) {
*/
public static double [][][] rectilinearVectorField( // scene0/scene1
final CLTParameters clt_parameters,
final float [][] fpixels, // to check for empty
......
src/main/java/com/elphel/imagej/orthomosaic/ObjectLocation.java
View file @ 86efce83
package com.elphel.imagej.orthomosaic;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collections;
import java.util.Comparator;
import com.elphel.imagej.common.ShowDoubleFloatArrays;
import com.elphel.imagej.tileprocessor.Correlation2d;
import com.elphel.imagej.tileprocessor.TileNeibs;
import ij.ImagePlus;
import ij.gui.PointRoi;
public class ObjectLocation {
String name;
double [] xy_meters;
double [] xy_pixels;
public ObjectLocation (
String name,
double [] xy_meters) {
this.name = name;
this.xy_meters = xy_meters;
}
public String getName() {
return name;
}
public double [] getMetric() {
return xy_meters;
}
public int [] getPixels() {
return new int[] {
(int) Math.round(xy_pixels[0]),
(int) Math.round(xy_pixels[1])};
};
public void setPixels(double [] xy) {
xy_pixels = xy;
}
public double [] extractObjectImage(
OrthoMapsCollection maps_collection,
int size) {
int nmap =maps_collection.getIndex(getName());
OrthoMap [] ortho_maps=maps_collection.getMaps();
final int width = ortho_maps[nmap].getImageData().width;
final int height = ortho_maps[nmap].getImageData().height;
final float [] src_img = ortho_maps[nmap].getImageData().data;
double [] dcrop = new double [size*size];
Arrays.fill(dcrop, Double.NaN);
int hsize = size/2;
int [] xy = getPixels();
boolean has_NaN=false;
for (int y = 0; y < size; y++) {
int src_y = y - hsize + xy[1];
if ((src_y >= 0) && (y < height)) {
for (int x = 0; x < size; x++) {
int src_x = x - hsize + xy[0];
if ((src_x >= 0) && (x < width)) {
double d = src_img[src_x + src_y * width];
dcrop[x + size * y] = d;
has_NaN |= Double.isNaN(d);
} else {
has_NaN=true;
}
}
} else {
has_NaN=true;
}
}
if (has_NaN) {
TileNeibs tn = new TileNeibs(size,size);
OrthoMap.fillNaNs(
dcrop, // double [] data,
tn, // TileNeibs tn,
3); // int min_neibs)
}
return dcrop;
}
public static double [] getPatternCenter(
double [] data_in,
double [] pattern,
double [] kernel,
int zoomout,
double phaseCoeff,
double min_corr,
int radius_search,
int radius_centroid,
String dbg_prefix,
int debugLevel){
int refine = 1;
int extr_size = (int) Math.sqrt(data_in.length);
int corr_size = 1;
for (; corr_size <= extr_size; corr_size*=2);
corr_size /=2;
double [] data = data_in;
if (corr_size < extr_size) {
data = new double [corr_size*corr_size];
int offs = extr_size/2 - corr_size/2;
for (int i = 0; i < corr_size; i++) {
System.arraycopy(
data_in,
offs * (extr_size + 1) + i * extr_size,
data,
i * corr_size,
corr_size);
}
}
int pattern_size = (int) Math.sqrt(pattern.length);
/*
// Already done while extracting
boolean has_NaN=false;
for (int i = 0; i < data.length; i++) {
if (Double.isNaN(data[i])) {
has_NaN=true;
break;
}
}
if (has_NaN) {
TileNeibs tn = new TileNeibs(corr_size,corr_size);
OrthoMap.fillNaNs(
data, // double [] data,
tn, // TileNeibs tn,
3); // int min_neibs)
}
*/
if (radius_search > (corr_size/2 - 1)) {
radius_search = corr_size/2 - 1;
System.out.println("getPatterCenter(): limiting radius_search to "+radius_search);
}
if (radius_centroid > radius_search) {
radius_centroid = radius_search;
System.out.println("getPatterCenter(): limiting radius_centroid to "+radius_centroid);
}
double [] corr_pattern = OrthoMap.patternZoomCropPad(
pattern, // double [] pattern,
pattern_size, // int pattern_size,
corr_size, // int size,
zoomout, // int zoomout,
false); // true); // out_normalize); // boolean normalize)
if (kernel != null) {
corr_pattern = OrthoMap.convolveWithKernel(
corr_pattern, // final double [] data,
kernel, // final double [] kernel,
corr_size); // final int width)
}
double [] corr_out= OrthoMap.correlateWithPattern(
data, // final double [] data,
corr_size, // final int width,
corr_size, // final int psize, // power of 2, such as 64
corr_pattern, // final double [] pattern, // [psize*psize]
false, // final boolean convolve, // convolve, not correlate
phaseCoeff, // final double phaseCoeff,
debugLevel); // final int debugLevel)
int data_width = 2 *radius_search + 1;
int offs = corr_size/2 - radius_search;
double [] data_max = new double [data_width*data_width];
for (int i = 0; i < data_width; i++) {
System.arraycopy(
corr_out,
offs * (corr_size + 1) + i * corr_size,
data_max,
i * data_width,
data_width);
}
// TODO: use min_corr and clusterize! Or use fixed fraction (50%) of the maximum ?
double [] xys = Correlation2d.getMaxXYCm( // last, average
data_max, // corrs.length-1], // double [] data,
data_width, // int data_width, // = 2 * transform_size - 1;
radius_centroid, // double radius, // 0 - all same weight, > 0 cosine(PI/2*sqrt(dx^2+dy^2)/rad)
refine, // int refine, // re-center window around new maximum. 0 -no refines (single-pass)
null, // boolean [] fpn_mask,
false, // boolean ignore_border, // only if fpn_mask != null - ignore tile if maximum touches fpn_mask
false); // boolean debug)
if (dbg_prefix != null) {
String [] dbg_titles = {"corr", "orig", "pattern"};
double [][] dbg_img = {corr_out, data, corr_pattern};
ImagePlus imp_corrs = ShowDoubleFloatArrays.makeArrays(
dbg_img,
corr_size,
corr_size,
dbg_prefix+"_pc"+phaseCoeff+"_rad"+radius_centroid,
dbg_titles); // test_titles,
PointRoi roi = new PointRoi();
roi.setOptions("label");
roi.addPoint(xys[0]+corr_size/2, xys[1]+corr_size/2); // ,1);
imp_corrs.setRoi(roi);
imp_corrs.show();
}
return xys;
}
public static double [] getRadialPattern(
final double [] data,
double [] xy_offs,
int corr_size,
double lim_rad, // outside all 0
double trans_width, // lim_rad-trans_width - start reducing
double frac_outliers,
double reversal_rad,
boolean [] good, // null or same size as data
int debugLevel) {
if (good != null) {
Arrays.fill(good, false);
}
double min_abs_weight = 10.0; // Do not touch very center?
int extr_size = (int) Math.sqrt(data.length);
double [] rad_patt = new double [corr_size*corr_size];
double xc = extr_size/2+xy_offs[0];
double yc = extr_size/2+xy_offs[1];
int size_1d = (int) Math.ceil(lim_rad);
double lr2 = size_1d * size_1d;
double [] sw = new double [size_1d + 2];
double [] swd = new double [sw.length];
double [] swd2 = new double [sw.length];
// boolean [] good = new boolean [data.length];
double [] distance = new double [data.length];
ArrayList<ArrayList<Integer>> rad_lists = new ArrayList<ArrayList<Integer>>();
for (int i = 0; i < sw.length; i++) {
rad_lists.add(new ArrayList<Integer>());
}
for (int y = 0; y < extr_size; y++) {
double dy = y - yc;
double y2 = dy*dy;
if (y2 <= lr2) {
for (int x = 0; x < extr_size; x++) {
double dx = x - xc;
double r2 = y2 + dx*dx;
if (r2 <= lr2) {
int indx = x + extr_size * y;
double r = Math.sqrt(r2);
int ir = (int) Math.floor(r);
distance[indx] = r;
rad_lists.get(ir).add(indx);
rad_lists.get(ir+1).add(indx);
double w1 = r-ir;
double w0 = 1.0 - w1;
double d = data[indx];
sw[ir] += w0;
swd[ir] += w0 * d;
swd2[ir] += w0 * d * d;
sw[ir+1] += w1;
swd[ir+1] += w1 * d;
swd2[ir+1] += w1 * d * d;
if (good != null) {
good[indx] = true;
}
}
}
}
}
//size_1d
for (int i = 0; i < sw.length; i++) {
if (sw[i] > 0) {
swd[i] /= sw[i];
swd2[i] /= sw[i];
}
}
double [] sw0 = sw.clone(); // to watch how many were removed (frac_outliers)
// now sort each list and later remove from either
for (ArrayList<Integer> rad_list:rad_lists) {
Collections.sort(rad_list, new Comparator<Integer>() {
@Override
public int compare(Integer lhs, Integer rhs) {
double rhsd = data[rhs];
double lhsd = data[lhs];
return (rhsd > lhsd) ? -1 : (rhsd < lhsd) ? 1 : 0;
}
});
}
// min_weight = 10.0
// Starting from very center remove fartherst (first or last) pixel,
// until remaining weight drops below min_weight or sw0[]*(1-frac_outliers).
// weight of the previous radius may fall also, but likely not too much
for (int nr = 1; nr < sw.length; nr++) {
double min_weight = Math.max(min_abs_weight, sw0[nr] * (1-frac_outliers));
ArrayList<Integer> rad_list = rad_lists.get(nr);
ArrayList<Integer> rad_list_prev = (nr > 0)? rad_lists.get(nr-1): null;
ArrayList<Integer> rad_list_next = (nr < (sw.length -1))? rad_lists.get(nr+1): null;
while (sw[nr] > min_weight) { // will break trying to remove last
if (rad_list.size()==0) {
System.out.println("BUG! - empty list for nr="+nr);
break;
}
int indx_first = rad_list.get(0);
int indx_last = rad_list.get(rad_list.size()-1);
boolean remove_first = Math.abs(data[indx_first] - swd[nr]) > Math.abs(data[indx_last] - swd[nr]);
int indx_worst = remove_first? indx_first : indx_last;
double d = data[indx_worst];
double dist = distance[indx_worst];
boolean other_next = dist >= nr;
double removed_w = other_next ? ( 1 - (dist - nr)) : (1 + (dist - nr));
double new_w = sw[nr] - removed_w;
if (new_w < min_weight) {
break;
}
swd[nr] = (swd[nr] * sw[nr] - removed_w * d) / new_w;
swd2[nr] = (swd2[nr] * sw[nr] - removed_w * d * d) / new_w;
sw[nr] = new_w;
rad_list.remove(remove_first ? 0 : (rad_list.size()-1));
if (good != null) {
good[indx_worst] = false; // seems not used - just for debug/display
}
// now remove from previous/next list
if (dist == nr) {
break;
}
int nr_other = other_next? (nr+1): (nr-1);
ArrayList<Integer> rad_list_other = other_next? rad_list_next : rad_list_prev;
// check for consistency:
int indx_in_other = rad_list_other.indexOf(indx_worst);
if (indx_in_other < 0) {
System.out.println("BUG in getRadialPattern(), pixel "+indx_worst+" from nr="+nr+" is missing in "+nr_other);
break;
}
double removed_w_other = 1.0 - removed_w;
double new_w_other = sw[nr_other] - removed_w_other; // no check for remaining weight here
swd[nr_other] = (swd[nr_other] * sw[nr_other] - removed_w_other * d) / new_w_other;
swd2[nr_other] = (swd2[nr_other] * sw[nr_other] - removed_w_other * d * d) / new_w_other;
sw[nr_other]= new_w_other;
rad_list_other.remove(indx_in_other);
}
}
int lr = size_1d;
if (reversal_rad > 0) {
int irr = (int) reversal_rad;
boolean is_growing = swd[irr+1] > swd[irr];
for (lr = irr+1; lr <= size_1d; lr++) {
if (is_growing) {
if (swd[lr+1] < swd[lr]) {
break;
}
} else {
if (swd[lr+1] > swd[lr]) {
break;
}
}
}
}
for (int i = 0; i < lr; i++) {
swd[i] -= swd[lr];
}
for (int i = lr; i <swd.length; i++) {
swd[i] = 0;
}
// TODO: add outlier removal here
// apply window
if (trans_width > 0) {
for (int i = (int) (lim_rad-trans_width); i < sw.length; i++) {
if (i < lim_rad) {
swd[i] *= 0.5*(1.0 + Math.cos(Math.PI*(i - (lim_rad-trans_width))/trans_width));
} else {
swd[i] = 0;
}
}
}
// generate output pattern
int oc = corr_size/2;
for (int y = 0; y < corr_size; y++) {
double dy = y - oc;
double y2 = dy*dy;
if (y2 <= lr2) {
for (int x = 0; x < corr_size; x++) {
double dx = x - oc;
double r2 = y2 + dx*dx;
if (r2 <= lr2) {
double r = Math.sqrt(r2);
int ir = (int) Math.floor(r);
double w1 = r-ir;
double w0 = 1.0 - w1;
rad_patt[x + corr_size * y] = w0 * swd[ir] + w1 * swd[ir + 1];
}
}
}
}
return rad_patt;
}
}
src/main/java/com/elphel/imagej/orthomosaic/OrthoMap.java
View file @ 86efce83
......@@ -67,6 +67,20 @@ public class OrthoMap implements Comparable <OrthoMap>, Serializable{
"/media/elphel/NVME/lwir16-proc/ortho_videos/kernel_50_100.tiff"
};
public static String pattern_dir= "/media/elphel/SSD3-4GB/lwir16-proc/ortho_videos/debug/mines/pattern_25m_zoom1/synthetic/";
public static String [] pattern_files=
{"patterns_50m_zoom1_200x200.tiff",
"patterns_50m_evening_zoom1_200x200.tiff",
"patterns_50m_evening_01_zoom1_200x200_00.tiff",
"patterns_50m_evening_02_zoom1_200x200_00.tiff",
"patterns_50m_evening_03_zoom1_200x200_00.tiff",
"patterns_50m_evening_04_zoom1_200x200_00.tiff",
"patterns_50m_evening_05_zoom1_200x200_00.tiff",
"mine1_zoom0.tiff",
"mine2_zoom0.tiff",
"mine3_zoom0.tiff",
"mine4_zoom0.tiff",
"mine6_zoom0.tiff"};
public static final String ALT_SUFFIX = "-ALT";
......@@ -1095,9 +1109,12 @@ public class OrthoMap implements Comparable <OrthoMap>, Serializable{
* @return square kernel as a 1-d double array or null
*/
public static double [] getConvolutionKernel() {
return getConvolutionKernel(kernel_paths.length-1);
}
public static double [] getConvolutionKernel(int choice) {
String kernel_path = null;
GenericJTabbedDialog gds = new GenericJTabbedDialog("Select kernel path",1200,400);
gds.addChoice("Kernel path:", kernel_paths, kernel_paths[kernel_paths.length-1]);
gds.addChoice("Kernel path:", kernel_paths, kernel_paths[choice]);
gds.showDialog();
if (gds.wasCanceled()) return null;
int kernel_index = gds.getNextChoiceIndex();
......@@ -3038,6 +3055,7 @@ public class OrthoMap implements Comparable <OrthoMap>, Serializable{
double [] wnd_in,
double phaseCoeff) {
// phaseCoeff = 0.5;
boolean dbg=false;
double [] data = data_in.clone();
double [] pattern = pattern_in.clone();
double [] wnd = wnd_in.clone();
......@@ -3047,7 +3065,7 @@ public class OrthoMap implements Comparable <OrthoMap>, Serializable{
for (int i = 0; i < data.length; i++) {
data[i] *= wnd[i];
}
{
if (dbg) {
String [] rslt_titles= {"original","window","windowed","pattern"};
ShowDoubleFloatArrays.showArrays(
new double[][] {data_orig, wnd, data, pattern},
......@@ -3096,7 +3114,7 @@ public class OrthoMap implements Comparable <OrthoMap>, Serializable{
}
}
{
if (dbg) {
String [] rslt_titles= {"corr", "original","window","windowed","pattern"};
ShowDoubleFloatArrays.showArrays(
new double[][] {corr_out, data_orig, wnd, data_orig2, pattern_orig},
......@@ -3106,7 +3124,7 @@ public class OrthoMap implements Comparable <OrthoMap>, Serializable{
convolve?"output_conv":("output_corr"+phaseCoeff),
rslt_titles);
}
System.out.println("testPhaseCorr() done");
if (dbg) System.out.println("testPhaseCorr() done");
return corr_out;
}
......@@ -3192,8 +3210,8 @@ public class OrthoMap implements Comparable <OrthoMap>, Serializable{
public static void testPatternCorrelate(
ImagePlus imp_src) {
/*
String pattern_dir= "/media/elphel/SSD3-4GB/lwir16-proc/ortho_videos/debug/mines/pattern_25m_zoom1/synthetic/";
// String pattern_file= "patterns_50m_zoom1_200x200.tiff";
String [] pattern_files=
{"patterns_50m_zoom1_200x200.tiff",
"patterns_50m_evening_zoom1_200x200.tiff",
......@@ -3202,6 +3220,7 @@ public class OrthoMap implements Comparable <OrthoMap>, Serializable{
"patterns_50m_evening_03_zoom1_200x200_00.tiff",
"patterns_50m_evening_04_zoom1_200x200_00.tiff",
"patterns_50m_evening_05_zoom1_200x200_00.tiff"};
*/
int zoomout = 2; // 1;
int corr_size = 128; // 256;
double phaseCoeff = 0.5;
......@@ -3297,7 +3316,6 @@ public class OrthoMap implements Comparable <OrthoMap>, Serializable{
double [][] corrs_out = new double[patterns.length][];
double [][] convolve_out = new double[patterns.length][];
// double [][] lim_corr = new double[patterns.length][];
double [][] corr_patterns = new double[patterns.length][];
for (int n = 0; n < patterns.length; n++) {
corr_patterns[n] = patternZoomCropPad(
......@@ -3331,6 +3349,11 @@ public class OrthoMap implements Comparable <OrthoMap>, Serializable{
height,
removeKnownExtension(imp_src.getTitle())+"-PATTERN_CORRS",
patt_titles); // test_titles,
if (src_marks != null) {
PointRoi roi = new PointRoi();
roi.setOptions("label");
......@@ -3881,40 +3904,16 @@ public class OrthoMap implements Comparable <OrthoMap>, Serializable{
public static void testPatternGenerate() {
int half_size = 100;
boolean half_pix = false; // center between pixels
boolean evening_mode = false; // glare around object, use radius
double radius_out= 42;
double edge_out = 6;
double scale_out = 1.5;
boolean evening_mode = true; // false; // glare around object, use radius
double radius = 30; // 32; // 32;
double edge= 15; // 4;
double radius_in= 15; // if 0 - skip
double edge_in = 8;
double scale_in = -0.05;
double radius_out= 42;
double edge_out = 6;
double scale_out = 1.5;
double scale = -200; // black 200
if (evening_mode) {
radius_out= 42;
edge_out = 8;
scale_out =-1.5; // relative to scale
radius = 30; // 32; // 32;
edge= 15; // 4;
radius_in= 10; // if 0 - skip
edge_in = 8;
scale_in = -0.7;
scale = -40; // black 200
} else {
radius_out= 42;
edge_out = 6;
scale_out =.08;
radius = 30; // 32; // 32;
edge= 15; // 4;
radius_in= 15; // if 0 - skip
edge_in = 8;
scale_in = -0.05;
scale = -170; // black 200
}
boolean normalize = false;
int halves_number = 8; // hidden mines - number of diameter cuts
......@@ -3930,15 +3929,15 @@ public class OrthoMap implements Comparable <OrthoMap>, Serializable{
if (gd0.wasCanceled()) return;
evening_mode= gd0.getNextBoolean();
if (evening_mode) {
radius_out= 62; // 42;
edge_out = 40; // 8;
scale_out =-1.5; // relative to scale
radius = 30; // 32; // 32;
edge= 24; // 8; // 4;
edge= 8; // 8; // 4;
radius_in= 10; // if 0 - skip
edge_in = 8;
scale_in = -0.1; // 7;
scale = -40; // black 200
scale_in = 0; // -0.1; // 7;
radius_out= 45; // 42;
edge_out = 30; // 8;
scale_out =-1.0; // relative to scale
scale = -60; // black 200
} else {
radius_out= 42;
edge_out = 6;
......
src/main/java/com/elphel/imagej/orthomosaic/OrthoMapsCollection.java
View file @ 86efce83
......@@ -396,6 +396,64 @@ public class OrthoMapsCollection implements Serializable{
return bounds;
}
/**
* Use object coordinates (now metric) on the composite image to
* determine corresponding pixel coordinates of the source images
* @param objects ArrayList of objects with the scene name and xy coordinates
* in the composite image. Will fill in pixel coordinates of the objects
* @param zoom_level zoom level of the composite image
*/
public void reverseRender(
ArrayList<ObjectLocation> objects,
int zoom_level){
int [][] bounds = getBoundsPixels( // should be for rectified, {-bounds[0][0], -bounds[0][1]} - exact center
zoom_level,
null);
int width = bounds[0][1] - bounds[0][0]; // bounds[x][0] - negative
int height = bounds[1][1] - bounds[1][0];
/*
int [] indices = new int [ortho_maps.length]; //maybe will get rid of
for (int i = 0; i < indices.length; i++) {
indices[i] = i;
}
*/
final int reference_index = 0;
for (ObjectLocation ol: objects) {
int nmap =getIndex(ol.getName());
final double scale = 1.0/OrthoMap.getPixelSizeMeters(zoom_level);
final double src_scale = 1.0/OrthoMap.getPixelSizeMeters(ortho_maps[nmap].orig_zoom_level); // pix per meter
double [][] mbounds = ortho_maps[nmap].getBoundsMeters(true); // keep original bounds
double [] enu_offset = ortho_maps[reference_index].enuOffsetTo(ortho_maps[nmap]);
double [] scaled_out_center = { // xy center to apply affine to
-bounds[0][0] + scale * enu_offset[0],
-bounds[1][0] - scale * enu_offset[1]};
double [] metric_center = { // back to meters to match objects
scaled_out_center[0]/scale,
scaled_out_center[1]/scale};
double dX = ol.getMetric()[0]-metric_center[0]; // matching dX, dY in renderMulti()
double dY = ol.getMetric()[1]-metric_center[1];
// final int [][] obounds = new int [2][2]; // output (rectified, combined) image bounds, relative to thje top-left
// for (int n = 0; n< 2; n++) {
// obounds[n][0] = (int) Math.floor(scaled_out_center[n] + scale*mbounds[n][0]);
// obounds[n][1] = (int) Math.ceil (scaled_out_center[n] + scale*mbounds[n][1]);
// }
// Output window size (keep original affine - OK if will not exactly fit)
// final int ownd_width = obounds[0][1] - obounds[0][0];
// final int ownd_height = obounds[1][1] - obounds[1][0];
// final int ownd_len = ownd_width * ownd_height;
double [][] src_bounds=ortho_maps[nmap].getBoundsMeters (true); // using original affines
final double [] src_center = {-src_bounds[0][0],-src_bounds[1][0]}; // x,y center offset in the source image
final double [][] affine = ortho_maps[nmap].affine; // only here use provided
// final int src_width = ortho_maps[nmap].getImageData().width;
// final int src_height = ortho_maps[nmap].getImageData().height;
// final float [] src_img = ortho_maps[nmap].getImageData().data; // FIXME: will not use
double [] xy_src = { // pixels of the source image
src_scale * (affine[0][0]*dX + affine[0][1]*dY + affine[0][2] + src_center[0]),
src_scale * (affine[1][0]*dX + affine[1][1]*dY + affine[1][2] + src_center[1])};
ol.setPixels(xy_src);
}
}
public ImagePlus renderMulti (
......
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