Commit 33f052a0 authored by Andrey Filippov's avatar Andrey Filippov

Working on 100m AGL

parent 758adc65
......@@ -70,6 +70,24 @@ public class ItemMatch {
return match.getMatch(indx);
}
/**
* Return correlation value as the one of the pattern correlations pointed
* by the best subpattern index.
* @param groundObjectPattern
* @return selected correlation value
*/
public double getMatchValue(GroundObjectPattern groundObjectPattern) {
return getMatchValue(groundObjectPattern.getPatternPath());
}
public double getMatchValue(String pattern_path) {
int indx = getPatternMatch(pattern_path).getBestSub(); // -1;
return getMatchValue(pattern_path,indx);
}
public double getMatchValue(GroundObjectPattern groundObjectPattern, int indx) {
return getMatchValue(groundObjectPattern.getPatternPath(), indx);
}
......
......@@ -2073,18 +2073,28 @@ public class OrthoMap implements Comparable <OrthoMap>, Serializable{
* @param ipattern square pattern array corresponding to data. 1 means
* average (w/o outliers) and add, 2 - average and subtract
* @param outliers_frac - fraction of outliers to remove while averaging
* @param obscure_frac fraction between center average and peripheral ring to compare when obscure_warm
* is set.
* @param masked_data null or double[data.length] - will return a copy of data
* with NaN for all unused for averaging
* @param debug show debug images
* @return difference between average in-pattern (1) and outside (2) average
* values
* @return a pair of : difference between average in-pattern (1) and outside (2) average
* values, and difference between third zone and a threshold between averages of zone1
* and zone2. For full patterns (no zone3) this value is NaN. Positive values are good,
* regardless the cold or warm center. For cold patterns (morning) positive means
* that zone 3 minimum is warmer than fraction point between zone1 and zone2 (cold
* object obscured by something warmer, for hot - that obscurant is colder.
*
*/
public static double getAbsoluteContrast(
public static double [] getAbsoluteContrast(
double [] data,
int [] ipattern,
double outliers_frac,
// boolean obscure_warm, // = true; // obscured can only be by warmer objects
double obscure_frac, // 0.25; // obscured threshold between center and outer
double [] masked_data, // null or double [data.length] to return masked data
boolean debug) {
int num_segments = 3;
if (debug) {
int size = (int) Math.sqrt(data.length);
ShowDoubleFloatArrays.showArrays(
......@@ -2095,11 +2105,14 @@ public class OrthoMap implements Comparable <OrthoMap>, Serializable{
}
ArrayList<ArrayList<Integer>> lists = new ArrayList<ArrayList<Integer>>();
for (int i = 0; i < 2; i++) {
for (int i = 0; i < num_segments; i++) {
lists.add(new ArrayList<Integer>());
}
double [] swd = new double [2],sw = new double [2], avg= new double[2], fracw=new double[2];
for (int n = 0; n < swd.length; n++) {
double [] swd = new double [num_segments],
sw = new double [num_segments],
avg= new double[num_segments],
fracw=new double[num_segments];
for (int n = 0; n < num_segments; n++) { // swd.length; n++) {
ArrayList<Integer> list = lists.get(n);
int n1 = n+1;
for (int i = 0; i < ipattern.length; i++) if (ipattern[i] == n1){
......@@ -2110,9 +2123,23 @@ public class OrthoMap implements Comparable <OrthoMap>, Serializable{
avg[n] = swd[n]/sw[n];
fracw[n] = (1.0-outliers_frac) * sw[n];
}
double [] zone3_min_max = {Double.NaN, Double.NaN};
int zone3=3;
for (int i:lists.get(zone3-1)) {
if (Double.isNaN(zone3_min_max[0]) || (data[i] < zone3_min_max[0])) {
zone3_min_max[0] = data[i];
}
if (Double.isNaN(zone3_min_max[1]) || (data[i] > zone3_min_max[1])) {
zone3_min_max[1] = data[i];
}
}
if (debug) {
System.out.println("getAbsoluteContrast() before outliers: avg[0] ="+avg[0]+", avg[1]="+avg[1]+", avg[0]-avg[1]="+(avg[0]-avg[1]));
}
if (outliers_frac > 0) {
for (int n = 0; n < swd.length; n++) {
ArrayList<Integer> list = lists.get(n);
......@@ -2124,7 +2151,7 @@ public class OrthoMap implements Comparable <OrthoMap>, Serializable{
return (rhsd > lhsd) ? -1 : (rhsd < lhsd) ? 1 : 0;
}
});
while (sw[n] >= fracw[n]) {
while (!list.isEmpty() && (sw[n] >= fracw[n])) {
int indx_first = list.get(0);
int indx_last = list.get(list.size()-1);
boolean remove_first = Math.abs(data[indx_first] - avg[n]) > Math.abs(data[indx_last] - avg[n]);
......@@ -2137,6 +2164,11 @@ public class OrthoMap implements Comparable <OrthoMap>, Serializable{
}
}
}
double threshold = obscure_frac * avg[0] + (1.0 - obscure_frac) * avg[1];
double over_thresh = (avg[0] < avg[1]) ? (zone3_min_max[0] - threshold) : (threshold - zone3_min_max[1]);
if (masked_data != null) {
Arrays.fill(masked_data, Double.NaN);
for (int n = 0; n < lists.size(); n++) {
......@@ -2175,14 +2207,15 @@ public class OrthoMap implements Comparable <OrthoMap>, Serializable{
if (debug) {
System.out.println("getAbsoluteContrast() after outliers: avg[0] ="+avg[0]+", avg[1]="+avg[1]+", avg[0]-avg[1]="+(avg[0]-avg[1]));
}
return avg[0]-avg[1];
return new double [] {avg[0]-avg[1], over_thresh};
}
/**
* From existing pattern (only for simple dark main scene)
* create two zones to calculate average (w/o outliers) inside
* the pattern and around it. Mark inner with 1, outer - 2, keep
* other 0. Then later find 2 averages (removing outliers) and their
* the pattern and around it. Mark inner with 1, outer - 2,
* 3 - potential obscurant for partial patterns
* keep other 0. Then later find 2 averages (removing outliers) and their
* difference - absolute contrast.
* @param patterns set of square patterns, first [0] for full pattern,
* others - for half-patterns cut in different directions.
......@@ -2287,6 +2320,8 @@ public class OrthoMap implements Comparable <OrthoMap>, Serializable{
( fys)*( fxs)*npatterns[n][sindx+size+1];
if (sdn/sd0 > 0.5) {
ipatterns[n][indx] = ipatterns[0][indx]; // =2
} else {
ipatterns[n][indx] = 3; // =2
}
}
}
......@@ -2305,6 +2340,7 @@ public class OrthoMap implements Comparable <OrthoMap>, Serializable{
switch (ipatterns[n][i]) {
case 1: dbg_img[n][i] = 1.0; break;
case 2: dbg_img[n][i] = -1.0; break;
case 3: dbg_img[n][i] = -2.0; break;
}
}
}
......@@ -4297,7 +4333,7 @@ public class OrthoMap implements Comparable <OrthoMap>, Serializable{
final int dbg_pix3 = 1439211; // 2827822;
final int dbg_x = 1445;
final int dbg_y = 2338;
final int dbg_tolerance = 10;
final int dbg_tolerance = -10;
for (int ithread = 0; ithread < threads.length; ithread++) {
threads[ithread] = new Thread() {
public void run() {
......
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