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imagej-elphel
Commit 951a84a6 authored by Andrey Filippov's avatar Andrey Filippov
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Before 3d models

parent 2c606e97
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Showing with 274 additions and 51 deletions
src/main/java/com/elphel/imagej/cameras/CLTParameters.java
View file @ 951a84a6
......@@ -376,6 +376,11 @@ public class CLTParameters {
public double photo_min_strength = 0.0; // maybe add to filter out weak tiles
public double photo_max_diff = 40.0; // To filter mismatches. Normal (adjusted) have RMSE ~9
public int photo_order = 2; // Approximation order: 0 - just offset, 1 - linear, 2 - quadratic
public double photo_std_1 = 75.0; // Minimal standard deviation of the filtered values for poly order 1
public double photo_std_2 = 200.0; // Minimal standard deviation of the filtered values for poly order 2
public int photo_offs_set = 0; // 0 - keep weighted offset average, 1 - balance result image, 2 - set weighted average to specific value
public double photo_offs = 21946; // weighted average offset target value, if photo_offs_set (and not photo_offs_balance)
public boolean photo_debug = false; // Generate images and text
......@@ -1367,6 +1372,10 @@ public class CLTParameters {
properties.setProperty(prefix+"photo_min_strength", this.photo_min_strength+""); // double
properties.setProperty(prefix+"photo_max_diff", this.photo_max_diff+""); // double
properties.setProperty(prefix+"photo_order", this.photo_order+""); // int
properties.setProperty(prefix+"photo_std_1", this.photo_std_1+""); // double
properties.setProperty(prefix+"photo_std_2", this.photo_std_2+""); // double
properties.setProperty(prefix+"photo_offs_set", this.photo_offs_set+""); // int
properties.setProperty(prefix+"photo_offs", this.photo_offs+""); // double
properties.setProperty(prefix+"photo_debug", this.photo_debug+""); // boolean
properties.setProperty(prefix+"show_textures", this.show_textures+"");
......@@ -2234,6 +2243,10 @@ public class CLTParameters {
if (properties.getProperty(prefix+"photo_min_strength")!=null) this.photo_min_strength=Double.parseDouble(properties.getProperty(prefix+"photo_min_strength"));
if (properties.getProperty(prefix+"photo_max_diff")!=null) this.photo_max_diff=Double.parseDouble(properties.getProperty(prefix+"photo_max_diff"));
if (properties.getProperty(prefix+"photo_order")!=null) this.photo_order=Integer.parseInt(properties.getProperty(prefix+"photo_order"));
if (properties.getProperty(prefix+"photo_std_1")!=null) this.photo_std_1=Double.parseDouble(properties.getProperty(prefix+"photo_std_1"));
if (properties.getProperty(prefix+"photo_std_2")!=null) this.photo_std_2=Double.parseDouble(properties.getProperty(prefix+"photo_std_2"));
if (properties.getProperty(prefix+"photo_offs_set")!=null) this.photo_offs_set=Integer.parseInt(properties.getProperty(prefix+"photo_offs_set"));
if (properties.getProperty(prefix+"photo_offs")!=null) this.photo_offs=Double.parseDouble(properties.getProperty(prefix+"photo_offs"));
if (properties.getProperty(prefix+"photo_debug")!=null) this.photo_debug=Boolean.parseBoolean(properties.getProperty(prefix+"photo_debug"));
if (properties.getProperty(prefix+"show_textures")!=null) this.show_textures=Boolean.parseBoolean(properties.getProperty(prefix+"show_textures"));
......@@ -3245,12 +3258,18 @@ public class CLTParameters {
gd.addNumericField("Approximation polynomial order", this.photo_order, 0,3,"",
"0 - only offset, 1 - linear, 2 - quadratic");
gd.addNumericField("Minimal standard deviation for poly 1", this.photo_std_1, 5,7,"",
"Minimal standard deviation to use polynomial order 1.");
gd.addNumericField("Minimal standard deviation for poly 2", this.photo_std_2, 5,7,"",
"Minimal standard deviation to use polynomial order 2.");
gd.addNumericField("Set photo offset (0-keep, 1-balance, 2-set)",this.photo_offs_set, 0,3,"",
"0 - keep weighted average offset, 1 - set offset to balance result image, 2 - use next value.");
gd.addNumericField("Target value to weighted average offset",this.photo_offs, 5,7,"",
"Target weighted (by scales) average offset.");
gd.addCheckbox ("Debug photometric calibration", this.photo_debug,
"Generate debug images an text output.");
gd.addTab ("3D", "3D reconstruction");
gd.addCheckbox ("Show generated textures", this.show_textures);
gd.addCheckbox ("show intermediate results of filtering", this.debug_filters);
......@@ -4251,6 +4270,12 @@ public class CLTParameters {
this.photo_min_strength = gd.getNextNumber();
this.photo_max_diff = gd.getNextNumber();
this.photo_order = (int) gd.getNextNumber();
this.photo_std_1 = gd.getNextNumber();
this.photo_std_2 = gd.getNextNumber();
this.photo_offs_set = (int) gd.getNextNumber();
this.photo_offs = gd.getNextNumber();
this.photo_debug = gd.getNextBoolean();
this.show_textures= gd.getNextBoolean();
......
src/main/java/com/elphel/imagej/tileprocessor/IntersceneMatchParameters.java
View file @ 951a84a6
......@@ -195,6 +195,7 @@ public class IntersceneMatchParameters {
public double max_search_rms = 1.5; // good - 0.34, so-so - 0.999
public double maybe_fom = 1.0; // good - 38, second good - 4.5
public double sure_fom = 12.0; // good - 38, second good - 4.5
public boolean treat_serch_fpn = false; // use FPN (higher) thresholds during search (even if offset is not small)
// Reference scene disparity
......@@ -627,6 +628,8 @@ public class IntersceneMatchParameters {
"Minimal acceptable Figure of Merit (semi-total strength divided by standard deviation of offsets), will look for the best among matching.");
gd.addNumericField("\"Sure\" FOM", this.sure_fom, 5,7,"",
"Definitely sufficient FOM (semi-total strength divided by standard deviation of offsets), will non continue looking for better.");
gd.addCheckbox ("Treat search all FPN", this.treat_serch_fpn,
"Use FPN (higher) thresholds during search (even if offset is not small).");
gd.addMessage ("Reference scene disparity");
......@@ -972,6 +975,7 @@ public class IntersceneMatchParameters {
this.max_search_rms = gd.getNextNumber();
this.maybe_fom = gd.getNextNumber();
this.sure_fom = gd.getNextNumber();
this.treat_serch_fpn = gd.getNextBoolean();
this.use_combo_dsi = gd.getNextBoolean();
this.use_lma_dsi = gd.getNextBoolean();
this.fpn_remove = gd.getNextBoolean();
......@@ -1252,6 +1256,7 @@ public class IntersceneMatchParameters {
properties.setProperty(prefix+"max_search_rms", this.max_search_rms+""); // double
properties.setProperty(prefix+"maybe_fom", this.maybe_fom+""); // double
properties.setProperty(prefix+"sure_fom", this.sure_fom+""); // double
properties.setProperty(prefix+"treat_serch_fpn", this.treat_serch_fpn+""); // boolean
properties.setProperty(prefix+"use_combo_dsi", this.use_combo_dsi+""); // boolean
properties.setProperty(prefix+"use_lma_dsi", this.use_lma_dsi+""); // boolean
properties.setProperty(prefix+"fpn_remove", this.fpn_remove+""); // boolean
......@@ -1485,6 +1490,7 @@ public class IntersceneMatchParameters {
if (properties.getProperty(prefix+"max_search_rms")!=null) this.max_search_rms=Double.parseDouble(properties.getProperty(prefix+"max_search_rms"));
if (properties.getProperty(prefix+"maybe_fom")!=null) this.maybe_fom=Double.parseDouble(properties.getProperty(prefix+"maybe_fom"));
if (properties.getProperty(prefix+"sure_fom")!=null) this.sure_fom=Double.parseDouble(properties.getProperty(prefix+"sure_fom"));
if (properties.getProperty(prefix+"treat_serch_fpn")!=null) this.treat_serch_fpn=Boolean.parseBoolean(properties.getProperty(prefix+"treat_serch_fpn"));
if (properties.getProperty(prefix+"use_combo_dsi")!=null) this.use_combo_dsi=Boolean.parseBoolean(properties.getProperty(prefix+"use_combo_dsi"));
if (properties.getProperty(prefix+"use_lma_dsi")!=null) this.use_lma_dsi=Boolean.parseBoolean(properties.getProperty(prefix+"use_lma_dsi"));
if (properties.getProperty(prefix+"fpn_remove")!=null) this.fpn_remove=Boolean.parseBoolean(properties.getProperty(prefix+"fpn_remove"));
......@@ -1735,6 +1741,7 @@ public class IntersceneMatchParameters {
imp.max_search_rms = this.max_search_rms;
imp.maybe_fom = this.maybe_fom;
imp.sure_fom = this.sure_fom;
imp.treat_serch_fpn = this.treat_serch_fpn;
imp.use_combo_dsi = this.use_combo_dsi;
imp.use_lma_dsi = this.use_lma_dsi;
imp.fpn_remove = this.fpn_remove;
......
src/main/java/com/elphel/imagej/tileprocessor/QuadCLT.java
View file @ 951a84a6
......@@ -2452,7 +2452,11 @@ public class QuadCLT extends QuadCLTCPU {
final QuadCLT ref_scene, // now - may be null - for testing if scene is rotated ref
final double min_strength,
final double max_diff, // 30.0
final int photo_order, // 0 - offset only, 1 - linear, 2 - quadratic
int photo_order, // 0 - offset only, 1 - linear, 2 - quadratic
final double photo_std_1, // 50.0; // Minimal standard deviation of the filtered values for poly order 1
final double photo_std_2, // 200.0; // Minimal standard deviation of the filtered values for poly order 2
final int photo_offs_set, // 0; // 0 - keep weighted offset average, 1 - balance result image, 2 - set weighted average to specific value
final double photo_offs, // 21946; // weighted average offset target value, if photo_offs_set (and not photo_offs_balance)
final int num_refines, // 2
final double [][] combo_dsn_final, // double [][] combo_dsn_final, // dls,
int threadsMax,
......@@ -2461,7 +2465,7 @@ public class QuadCLT extends QuadCLTCPU {
// filter disparity by LMA only, same bg and fg
double [] disparity_ref= combo_dsn_final[OpticalFlow.COMBO_DSN_INDX_DISP].clone();
for (int i = 00; i < disparity_ref.length; i++) {
for (int i = 0; i < disparity_ref.length; i++) {
if (combo_dsn_final[OpticalFlow.COMBO_DSN_INDX_STRENGTH][i] < min_strength) {
disparity_ref[i] = Double.NaN;
} else if (combo_dsn_final[OpticalFlow.COMBO_DSN_INDX_DISP_BG_ALL][i] !=
......@@ -2512,13 +2516,10 @@ public class QuadCLT extends QuadCLTCPU {
double [] offs_old = ref_scene.getLwirOffsets();
double [] scales_old = ref_scene.getLwirScales();
double [] scales2_old = ref_scene.getLwirScales2();
// Calculate avg_pix - average (for all 16 channels) pixel value and initial good_pix
// next passes avg_pix will be modified and more bad pixels added
double [] offs_new = new double [num_sens];
double [] scales_new = new double [num_sens];
double [] scales2_new = new double [num_sens];
for (int nref = 0; nref < num_refines; nref++) {
Arrays.fill(avg_pix, 0.0);
double avg_img = 0.0;
int num_good = 0;
for (int i = 0; i < len; i++) {
for (int n = 0; n < num_sens; n++) {
......@@ -2527,15 +2528,33 @@ public class QuadCLT extends QuadCLTCPU {
}
avg_pix[i] /= dpixels.length;
if (good_pix[i]) {
avg_img += avg_pix[i];
num_good++;
}
}
double [][][] pa_data = new double [num_sens][num_good][2];
avg_img /= num_good;
double wavg_offs = photo_offs;
boolean set_offs = true;
if (photo_offs_set == 1) { // balance
for (int i = 0; i < len; i++) {
avg_pix[i] -= avg_img;
}
set_offs = false;
} else if (photo_offs_set == 0) {
double s = 1.0;
wavg_offs = 0.0;
for (int n = 0; n < num_sens; n++) {
s *= scales_old[n];
wavg_offs += offs_old[n]*scales_old[n];
}
s = Math.pow(s, 1.0/num_sens);
wavg_offs /= num_sens * s;
}
// recover original "raw" pixel values undoing old corrections
double [][] raw = new double [num_sens][len];
for (int nsens = 0; nsens < num_sens; nsens++) {
Arrays.fill(raw[nsens],Double.NaN); // debug only
int indx = 0;
for (int i = 0; i < len; i++) if (good_pix[i]){
double A0 = scales2_old[nsens];
double B0 = scales_old[nsens];
......@@ -2545,10 +2564,63 @@ public class QuadCLT extends QuadCLTCPU {
double c = (C0*C0*A0 -C0 * B0 - dpixels[nsens][i]);
double p = -c/b;
if (Math.abs(a) >= min_abs_a) {
p= (-b + Math.sqrt(b*b - 4 * a * c))/(2 * a);
double d2 = b*b - 4 * a * c;
if (d2 < 0) {
System.out.println("calibratePhotometric2() 0: Failed quadratic: a = "+a+", b = "+b+", c="+c);
return false;
}
p= (-b + Math.sqrt(d2))/(2 * a);
}
raw[nsens][i] = p;
pa_data[nsens][indx][0] = p; // dpixels[nsens][i];
}
}
double [] offs_new = new double [num_sens];
double [] scales_new = new double [num_sens];
double [] scales2_new = new double [num_sens];
double [] avg_chn = new double [num_sens];
double [] std_chn = new double [num_sens];
double std = 0.0;
for (int nref = 0; nref < num_refines; nref++) {
Arrays.fill(avg_chn, 0.0);
Arrays.fill(std_chn, 0.0);
num_good = 0;
for (int i = 0; i < len; i++) {
if (good_pix[i]) {
num_good++;
for (int n = 0; n < num_sens; n++) {
avg_chn[n] += dpixels[n][i];
std_chn[n] += dpixels[n][i] * dpixels[n][i];
}
}
}
std = 0.0;
for (int n = 0; n < num_sens; n++) {
avg_chn[n] /= num_good;
std_chn[n] /= num_good;
std_chn[n] = Math.sqrt(std_chn[n] - avg_chn[n] * avg_chn[n]);
std += std_chn[n] * std_chn[n];
}
std = Math.sqrt(std/num_sens);
if ((photo_order > 0) && (std < photo_std_1)) {
photo_order = 0;
System.out.println ("Standard deviation = "+std+" < "+photo_std_1+", adjusting only offsets. nref = "+nref);
nref = -1;
continue; // restart
} else if ((photo_order > 1) && (std < photo_std_2)) {
photo_order = 1;
System.out.println ("Standard deviation = "+std+" < "+photo_std_2+", adjusting only offsets and scales. nref = "+nref);
nref = -1;
continue; // restart
} else if (debug) {
System.out.println ("Standard deviation = "+std+", nref = "+nref);
}
double [][][] pa_data = new double [num_sens][num_good][2];
for (int nsens = 0; nsens < num_sens; nsens++) {
int indx = 0;
for (int i = 0; i < len; i++) if (good_pix[i]){
pa_data[nsens][indx][0] = raw[nsens][i]; // dpixels[nsens][i];
pa_data[nsens][indx][1] = avg_pix[i];
indx++;
}
......@@ -2573,7 +2645,12 @@ public class QuadCLT extends QuadCLTCPU {
double A = a;
double C = -c/b;
if (Math.abs(a) >= min_abs_a) {
C = (-b + Math.sqrt(b*b - 4*a*c))/(2 * a);
double d2 = b*b - 4*a*c;
if (d2 < 0) {
System.out.println("calibratePhotometric2() 1: Failed quadratic: a = "+a+", b = "+b+", c="+c);
return false;
}
C = (-b + Math.sqrt(d2))/(2 * a);
}
double B = 2 * C * a + b;
scales2_new[nsens] = A;
......@@ -2594,6 +2671,14 @@ public class QuadCLT extends QuadCLTCPU {
pa_data[nsens][i][1] /= scales_avg;
}
}
for (int i = 0; i < avg_pix.length; i++) { // for the next iteration
avg_pix[i] /= scales_avg;
}
//avg_pix[i]
if (debug) {
System.out.println ("scales_avg = "+scales_avg+", nref = "+nref);
}
}
// make scales2 be average zero, re-run scales
if (photo_order > 1) {
......@@ -2606,10 +2691,15 @@ public class QuadCLT extends QuadCLTCPU {
scales2_new[nsens] -= scales2_offset;
}
// modify pa_data, re-run linear
for (int nsens = 0; nsens < num_sens; nsens++) {
for (int i = 0; i < num_good; i++) {
double poffs = pa_data[nsens][i][0] - offs_new[nsens];
pa_data[nsens][i][1] -=poffs*poffs*scales2_new[nsens];
int indx = 0;
// for (int i = 0; i < num_good; i++) {
for (int i = 0; i < avg_pix.length; i++) if (good_pix[i]){
double poffs = pa_data[nsens][indx][0] - offs_new[nsens];
pa_data[nsens][indx][1] -= poffs*poffs*scales2_new[nsens];
// avg_pix[i] -= poffs*poffs*scales2_offset/num_sens; // for the next iteration
indx++;
}
pa_coeff[nsens] =(new PolynomialApproximation(0)).polynomialApproximation1d(
pa_data[nsens], 1);
......@@ -2618,7 +2708,48 @@ public class QuadCLT extends QuadCLTCPU {
scales_new [nsens] = b;
offs_new[nsens] = -c/b;
}
// re-normalize scales_new
double scales_avg = 1.0;
for (int nsens = 0; nsens < num_sens; nsens++) {
scales_avg *= scales_new [nsens];
}
scales_avg = Math.pow(scales_avg, 1.0/num_sens);
for (int nsens = 0; nsens < num_sens; nsens++) {
scales_new [nsens] /= scales_avg;
scales2_new [nsens] /= scales_avg;
for (int i = 0; i < num_good; i++) {
pa_data[nsens][i][1] /= scales_avg;
}
}
for (int i = 0; i < avg_pix.length; i++) { // for the next iteration
avg_pix[i] /= scales_avg;
}
//avg_pix[i]
if (debug) {
System.out.println ("normalization after quadratic: scales_avg = "+scales_avg+", nref = "+nref);
}
}
// update offsets if set_offs
if (set_offs) {
double wa = 0.0;
for (int nsens = 0; nsens < num_sens; nsens++) {
wa += offs_new[nsens] * scales_new [nsens];
}
wa /= num_sens;
double a = wavg_offs - wa;
for (int nsens = 0; nsens < num_sens; nsens++) {
offs_new[nsens] += a/scales_new [nsens];
}
for (int i = 0; i < avg_pix.length; i++) if (good_pix[i]){
avg_pix[i] -= a;
}
if (debug) {
System.out.println ("calibratePhotometric2(): wa = "+wa+", a="+a);
}
}
if (true) { // debug) { during debug,
System.out.println("DEBUG: calibratePhotometric() nref="+nref);
......
src/main/java/com/elphel/imagej/tileprocessor/TwoQuadCLT.java
View file @ 951a84a6
......@@ -8798,6 +8798,10 @@ if (debugLevel > -100) return true; // temporarily !
}
double pts_scale = clt_parameters.imp.video_fps/clt_parameters.imp.sensor_fps;
String shellCommand;
//ffmpeg -i input_file.mkv -c copy -metadata:s:v:0 stereo_mode=1 output_file.mkv
//https://ffmpeg.org/ffmpeg-formats.html
//ffmpeg -i sample_left_right_clip.mpg -an -c:v libvpx -metadata stereo_mode=left_right -y stereo_clip.webm
//anaglyph_cyan_red
if (this_stereo_width > 0) {// add padding to stereo video
int padded_width= 16* ( (int) Math.round((this_stereo_width + stereo_gap) * stereo_phone_width/stereo_intereye/32));
shellCommand = String.format(
......
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