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Updated illumination invariant paper documentation
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matlabbe
56
archive/2022-IlluminationInvariant/README.md
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56
archive/2022-IlluminationInvariant/README.md
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## Multi-Session Visual SLAM for Illumination Invariant Re-Localization in Indoor Environments
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* Paper: https://doi.org/10.3389/frobt.2022.801886
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* The setup: we did 6 mapping sessions at dusk to evaluate how well RTAB-Map can localize (only by vision) on maps taken at different illumination conditions. The data has been collected with [RTAB-Map Tango](https://play.google.com/store/apps/details?id=com.introlab.rtabmap&hl=en_CA&gl=US).
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]
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## Description
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This folder contains scripts to re-generate results from the paper. The main idea behind this work is that using Multi-Session mapping can help to localize visually in illumination changing environments even with features that are not very robust to such conditions. We compared common hand-made visual features like SIFT, SURF, BRIEF, BRISK, FREAK, DAISY, KAZE with learned descriptor SuperPoint. The following picture show how robust are the visual features tested when localizing against single session recorded at different time. For example, the bottom-left and top-right cells are when the robot tries to localize the night on a map taken the day or vice-versa. The diagonal is localization performance when the localization session is about the same time than when the map was recorded. SuperPoint has clearly an advantage on this single-session experiment.
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]
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The following image shows when we do the same localization experiment at different hours, but against maps created by assembling maps taken at different hours. In this case, we can see that even binary features like BRIEF can work relatively well in illumination-variant environments. See the paper for more detailled results and comments. The line `1+2+3+4+5+6` refers to the assembled map shown below containing all mapping sessions linked together in same database.
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]
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]
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## Dataset
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We provide two formats: the first one is more general and the second one is used to produce the results in this paper with RTAB-Map. Please open issue if the links are outdated.
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* [Images](https://usherbrooke-my.sharepoint.com/:u:/g/personal/labm2414_usherbrooke_ca/EV8F4PZUxOxLhwAyEehlzKwBjF-9xNuxR32Q4mUjx5u-rA?e=eCJ3TW):
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* `rgb`: folder containing *.jpg color camera images
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* `depth`: folder containing *.png 16bits mm depth images
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* `calib`: folder containing calibration for each color image. Each calibration contains also the transform between `device` and `camera` frames as `local_transform`.
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* `device_poses.txt`: poses of of each image in `device` frame
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* `camera_poses.txt`: poses of of each image in `camera` frame
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* [RTAB-Map Databases](https://usherbrooke-my.sharepoint.com/:u:/g/personal/labm2414_usherbrooke_ca/EU5fb0jEKzlGhPK3OWjMGLUBnDo1BRAoZwtB2czyeVLE_A?e=Y0JyXY)
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## How reproduce results shown in the paper
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1. RTAB-Map should be built from source with those dependencies (don't need to "install" it, we will launch it from build directory in the scripts below to avoid conflicting with another rtabmap already installed):
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* OpenCV built with xfeatures2d and nonfree modules
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* torchlib c++ to enable SuperPoint (superpoint.pt can be downloaded [here](https://github.com/KinglittleQ/SuperPoint_SLAM/blob/master/superpoint.pt))
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* Python3 to use SuperGlue
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2. Download database version of the dataset and extract the databases in the `script` directory.
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3. Adjust the path inside `rtabmap_latest.sh` script to match where you just built rtabmap with right dependencies.
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4. Run `run_all.sh OUTPUT_PATH`, this script will do (warning, this could take hours to do...):
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* Recreate the map databases for each feature type
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* Create the merged databases
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* Run localization databases over all map/merged databases
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* Run consecutive localization experiment
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5. Export statistics with `export_stats.sh` script.
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6. Use the MatLab/Octave scripts in this folder to show results you want. Set `dataDir` to directory containing the exported statistics.
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BIN
archive/2022-IlluminationInvariant/images/fig_map_merged_999.jpg
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archive/2022-IlluminationInvariant/images/fig_map_merged_999.jpg
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archive/2022-IlluminationInvariant/images/fig_overview.jpg
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169
archive/2022-IlluminationInvariant/results_common.m
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archive/2022-IlluminationInvariant/results_common.m
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clear all
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close all
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# sudo apt install octave-signal
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pkg load signal
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# Use with files generated by export_stats.sh
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dataDir = '2'; % '0'=old, '1'=new, 2=revised(2022)
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resultsToShow = 1; % 1=single 2=Consecutive
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prefix = 'Stat';
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RAMaddOverhead = 0;
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% Inliers_ratio = 'Loop/Visual_inliers/' ./ 'Keypoint/Current_frame/words'
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% Odometry_average = 'Memory/Distance_travelled/m'(2:end) - 'Memory/Distance_travelled/m'(1:end-1)
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statNames = {'Loop/Odom_correction_norm/m', 'Loop/Visual_inliers/', 'Inliers_ratio_%', 'Timing/Total/ms', 'Memory/RAM_usage/MB', 'Memory/RAM_estimated/MB', 'Keypoint/Current_frame/words', 'Loop/Map_id/', 'Memory/Local_graph_size/', 'Keypoint/Dictionary_size/words', 'Loop/Distance_since_last_loc/'}; % 'Odometry_average'
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datasets = [ 0 1 6 7 9 14 11 111 ]; % 0 1 6 7 9 12 14 11
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sep = [0, 1000, 3000, 5000, 7000, 9000, 12000];
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sepName = {'16:51', '17:31', '17:58', '18:30', '18:59', '19:42'};
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if resultsToShow == 2
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sep = [0, 1000, 3000, 5000, 7000, 9000];
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sepName = {'17:27', '17:54', '18:27', '18:56', '19:35'};
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prefix = 'Consecutive';
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statNames = {'Loop/Distance_since_last_loc/', 'Distance_since_last_loc_under_50cm'};
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endif
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MapsN = length(sepName);
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allCumResults = {};
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allMaxResults = {};
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for s=1:length(statNames)
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avgResults = {};
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maxResults = {};
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totalResults = {};
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absResults = {};
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statName = strrep(statNames{s},'/','-');
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for d=1:length(datasets)
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if strcmp(statName,'Inliers_ratio_%')
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data = dlmread([dataDir '/' prefix num2str(datasets(d)) '-' 'Loop-Visual_inliers-' '.txt'], '\t', 1, 0, "emptyvalue", 0);
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dataWords = dlmread([dataDir '/' prefix num2str(datasets(d)) '-' 'Keypoint-Current_frame-words' '.txt'], '\t', 1, 0, "emptyvalue", 0);
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data(:, 2:end) = data(:, 2:end) ./ dataWords(:, 2:end) * 100;
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elseif strcmp(statName, 'Odometry_average')
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data = dlmread([dataDir '/' prefix num2str(datasets(d)) '-' 'Memory-Distance_travelled-m' '.txt'], '\t', 1, 0, "emptyvalue", 0);
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elseif strcmp(statName, 'Distance_since_last_loc_under_50cm')
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data = dlmread([dataDir '/' prefix num2str(datasets(d)) '-' 'Loop-Distance_since_last_loc-' '.txt'], '\t', 1, 0, "emptyvalue", 0);
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else
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data = dlmread([dataDir '/' prefix num2str(datasets(d)) '-' statName '.txt'], '\t', 1, 0, "emptyvalue", 0);
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endif
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sessions = size(data,2)-1;
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avgResultsTmp = zeros(sessions, length(sep)-1);
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maxResultsTmp = zeros(sessions, length(sep)-1);
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totalResultsTmp = zeros(sessions, length(sep)-1);
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absResultsTmp = zeros(sessions, length(sep)-1);
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for i = 1:sessions
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for j = 1:length(sep)-1
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x = data(:,1);
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y = data(:,i+1);
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y = y(x>=sep(j) & x<=sep(j+1), :);
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x = x(x>=sep(j) & x<=sep(j+1), :);
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if strcmp(statName, 'Odometry_average')
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y(2:end) = y(2:end) - y(1:end-1);
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y(y < 0.05) = 0;
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elseif strcmp(statName, 'Loop-Map_id-')
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y = y+1;
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y(y>0) = 1;
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end
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if strcmp(statName, 'Memory-RAM_estimated-MB') && RAMaddOverhead == 1
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% Valgrind estimated around 90 MB constant overhead
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y = y + 90;
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if datasets(d) == 7
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%% 135 MB overhead for BRISK kernel
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y = y + 135;
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elseif datasets(d) == 11 || datasets(d) == 111
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%% 645 MB (library cuda) + 800 MB (network) for SuperPoint
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y = y + 645+800;
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elseif datasets(d) == 13 || datasets(d) == 14
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%% 64 MB overhead for DAISY
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y = y + 64;
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endif
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endif
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nonzeros = y(y>0);
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if strcmp(statName, 'Loop-Map_id-')
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nonzeros = y;
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end
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if strcmp(statName, 'Distance_since_last_loc_under_50cm')
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y(y>0.55) = 0;
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y(isnan(y)) = 0;
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y(y>0) = 1;
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nonzeros = y;
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end
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if length(nonzeros) > 0
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avgValue = sum(nonzeros)/length(nonzeros);
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avgResultsTmp(i,j) = avgValue;
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maxResultsTmp(i,j) = max(nonzeros);
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totalResultsTmp(i,j) = length(nonzeros);
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absResultsTmp(i,j) = sum(nonzeros);
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endif
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endfor
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endfor
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avgResults{1,d} = avgResultsTmp;
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maxResults{1,d} = maxResultsTmp;
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totalResults{1,d} = totalResultsTmp;
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absResults{1,d} = absResultsTmp;
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endfor
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% compute cumulative results
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cumResults = zeros(sessions+2, length(datasets)+1);
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for d=1:length(datasets)
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cumResults(1,d+1) = datasets(d);
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if sum(totalResults{1,d}, 2)
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cumResults(2:end-1,d+1) = sum(absResults{1,d}, 2) ./ sum(totalResults{1,d}, 2);
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endif
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cumResults(end,d+1) = sum(sum(absResults{1,d}(1:MapsN,1:MapsN).*eye(MapsN,MapsN))) / sum(sum(totalResults{1,d}(1:MapsN,1:MapsN).*eye(MapsN,MapsN)));
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end
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cumResults(2:end-1,1) = 1:sessions;
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allCumResults{1,s} = statNames{s};
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if strcmp(statNames{s}, 'Loop/Odom_correction_norm/m')
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cumResults(2:end,2:end) = cumResults(2:end,2:end) * 1000;
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allCumResults{1,s} = 'Loop/Odom_correction_norm/mm';
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elseif strcmp(statNames{s}, 'Loop/Map_id/')
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cumResults(2:end,2:end) = cumResults(2:end,2:end) * 100;
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endif
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allCumResults{2,s} = round(cumResults);
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% compute max results
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cumMaxResults = zeros(sessions+2, length(datasets)+1);
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for d=1:length(datasets)
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cumMaxResults(1,d+1) = datasets(d);
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if sum(totalResults{1,d}, 2)
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cumMaxResults(2:end-1,d+1) = max(maxResults{1,d}, [], 2);
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endif
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cumMaxResults(end,d+1) = max(max(maxResults{1,d}(1:MapsN,1:MapsN).*eye(MapsN,MapsN)));
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end
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cumMaxResults(2:end-1,1) = 1:sessions;
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allMaxResults{1,s} = statNames{s};
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allMaxResults{2,s} = cumMaxResults;
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endfor % statNames
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if resultsToShow == 2
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disp('30min')
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for d=1:length(datasets)
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round(sum(absResults{1,d} .* eye(5,5)) / sum(totalResults{1,d} .*eye(5,5)) * 100)
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endfor
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disp('60min')
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for d=1:length(datasets)
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round(sum(absResults{1,d} .* [[0;0;0;0] eye(4,4) ; [0 0 0 0 0]]) / sum(totalResults{1,d} .*[[0;0;0;0] eye(4,4) ; [0 0 0 0 0]]) * 100)
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endfor
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disp('120min')
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for d=1:length(datasets)
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round(avgResults{1,d}(1,5) * 100)
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endfor
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endif
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253
archive/2022-IlluminationInvariant/results_loc_over_time.m
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253
archive/2022-IlluminationInvariant/results_loc_over_time.m
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close all
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clear all
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pkg load signal
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# Use with files generated by export_stats.sh
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dataDir = '2'; % '0'(old) '1'(new) '2' (revised april 2022)
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resultsToShow = 1; % 1=single loc, 2=merged loc, 3=consecutive
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datasetPrefix = 'Stat';
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datasets = [0 1 6 7 9 14 11 111]; % 0 1 6 7 8 9 11 12
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datasetsName = {'SURF' 'SIFT' 'ORB' 'FAST/FREAK' 'FAST/BRIEF' 'GFTT/FREAK' 'GFTT/BRIEF' 'BRISK' 'GFTT/ORB' 'KAZE' 'ORB-OCTREE' 'SuperPoint' 'SURF/FREAK' 'GFTT/DAISY' 'SURF/DAISY'};
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datasetsName{112} = 'SuperGlue'
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sep = [0, 1000, 3000, 5000, 7000, 9000, 12000];
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sepName = {'16:51', '17:31', '17:58', '18:30', '18:59', '19:42'};
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if resultsToShow == 3
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sep = [0, 1000, 3000, 5000, 7000, 9000];
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sepName = {'17:27', '17:54', '18:27', '18:56', '19:35'};
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datasetPrefix = 'Consecutive'
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endif
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percentResults = {};
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totalResults = {};
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locResults = {};
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figure
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colors = get(gca, 'ColorOrder');
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tmp=colors(3,:);
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colors(3,:) = colors(5,:);
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colors(5,:) = tmp;
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globalSeparators = [];
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globalx = [];
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globaly = [];
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globalc = [];
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for d=1:length(datasets)
|
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|
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data = dlmread([dataDir '/' datasetPrefix num2str(datasets(d)) '-Loop-Map_id-' '.txt'], '\t', 1, 0, "emptyvalue", NaN);
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curvesBeg = 2;
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curvesEnd = size(data,2)-5; % -4 for '0', -5 for '1'
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if resultsToShow == 2
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curvesBeg = 8; % 2 if only 4 merged_reduced in stats, 8 to skip first 6
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||||
curvesEnd = size(data,2);
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elseif resultsToShow == 3
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||||
curvesEnd = size(data,2);
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||||
endif
|
||||
curves = curvesEnd - curvesBeg + 1;
|
||||
|
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percentResultsTmp = zeros(curves, length(sep)-1);
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totalResultsTmp = zeros(curves, length(sep)-1);
|
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locResultsTmp = zeros(curves, length(sep)-1);
|
||||
|
||||
offset = 1;
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|
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for i = 1:curves
|
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index = i + curvesBeg - 1;
|
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separators = [];
|
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x_all = [];
|
||||
y_all = [];
|
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m_all = [];
|
||||
previousMax = 0;
|
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for j = 1:length(sep)-1
|
||||
x = data(:,1);
|
||||
y = data(:,index);
|
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y = y(x>=sep(j) & x<=sep(j+1), :);
|
||||
x = x(x>=sep(j) & x<=sep(j+1), :);
|
||||
minimum = x(1,1);
|
||||
separators = [separators previousMax];
|
||||
x = x - (minimum-previousMax);
|
||||
previousMax = x(end,1);
|
||||
y = y + 1;
|
||||
m = y;
|
||||
y(y>0) = 1;
|
||||
y(isnan(y)) = 0;
|
||||
percent = sum(y)/length(y);
|
||||
percentResultsTmp(i,j) = percent;
|
||||
locResultsTmp(i,j) = sum(y);
|
||||
totalResultsTmp(i,j) = length(y);
|
||||
y(y>0) = -(d-1)*curves -i - (d-1)*offset;
|
||||
%x(y==0) = nan;
|
||||
m(y==0) = nan;
|
||||
y(y==0) = nan;
|
||||
if resultsToShow == 2
|
||||
if i==1 %% Merged 1, 6
|
||||
m(m==1) = 1;
|
||||
m(m==2) = 6;
|
||||
elseif i==2 %% Merged 1,3(2 sessions),5
|
||||
m(m==1) = 1;
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||||
m(m==2) = 3;
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||||
m(m==3) = 3;
|
||||
m(m==4) = 5;
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||||
elseif i==3 %% Merged 2(2 sessions),4,6
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||||
m(m==1) = 2;
|
||||
m(m==2) = 2;
|
||||
m(m==4) = 6;
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||||
m(m==3) = 4;
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||||
elseif i>=4 %% Merged 1, 2(2 sessions), 3(2 sessions),4,5,6
|
||||
m(m==1) = 1;
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||||
m(m==2) = 2;
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||||
m(m==3) = 2;
|
||||
m(m==4) = 3;
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||||
m(m==5) = 3;
|
||||
m(m==6) = 4;
|
||||
m(m==7) = 5;
|
||||
m(m==8) = 6;
|
||||
endif
|
||||
endif
|
||||
x = upsample(x, 2);
|
||||
y = upsample(y, 2);
|
||||
m = upsample(m, 2);
|
||||
x(2:2:end-1) = x(3:2:end);
|
||||
y(2:2:end-1) = y(3:2:end);
|
||||
m(2:2:end) = m(1:2:end);
|
||||
x = x(1:end-1);
|
||||
y = y(1:end-1);
|
||||
m = m(1:end-1);
|
||||
|
||||
x_all = [x_all nan x'];
|
||||
y_all = [y_all nan y'];
|
||||
m_all = [m_all nan m'];
|
||||
endfor
|
||||
if resultsToShow == 2
|
||||
globalx = [globalx x_all];
|
||||
globaly = [globaly y_all];
|
||||
globalc = [globalc m_all];
|
||||
else
|
||||
plot(x_all,y_all, 'linewidth', 3, 'color', colors(i,:))
|
||||
hold on
|
||||
endif
|
||||
separators = [separators previousMax];
|
||||
globalSeparators = separators;
|
||||
endfor
|
||||
percentResults{1,d} = percentResultsTmp;
|
||||
totalResults{1,d} = totalResultsTmp;
|
||||
locResults{1,d} = locResultsTmp;
|
||||
endfor
|
||||
|
||||
if resultsToShow == 2
|
||||
indColors = ones(length(globalc), 3);
|
||||
for j=1:length(globalc)
|
||||
if ~isnan(globalc(j))
|
||||
indColors(j,:) = colors(globalc(j),:);
|
||||
endif
|
||||
endfor
|
||||
for i=1:6
|
||||
tmpx = globalx;
|
||||
tmpy = globaly;
|
||||
tmpx(globalc~=i) = nan;
|
||||
tmpy(globalc~=i) = nan;
|
||||
plot(tmpx, tmpy, 'linewidth', 3, 'color', colors(i,:));
|
||||
if i==1
|
||||
hold on
|
||||
endif
|
||||
endfor
|
||||
endif
|
||||
|
||||
for j=1:length(globalSeparators)
|
||||
x = globalSeparators(j);
|
||||
plot([x,x],[(-length(datasets)*(curves+1)) ,0], 'k','linewidth', 2);
|
||||
endfor
|
||||
|
||||
for d=1:length(datasets)
|
||||
annotation ("textbox", [0, 0.96-((d-0.5)/length(datasets))*0.95, 0,0], 'string', datasetsName{datasets(d)+1})
|
||||
endfor
|
||||
for s=1:length(sep)-1
|
||||
annotation ("textbox", [0.1 + ((separators(s+1)-separators(s))/2+separators(s))/separators(end)*0.75, 0.98, 0,0], 'string', sepName{s})
|
||||
endfor
|
||||
axis('tight')
|
||||
|
||||
|
||||
|
||||
set(gca, 'units', 'normalized');
|
||||
Tight = get(gca, 'Position');
|
||||
NewPos = [Tight(1) 0.01 0.77 0.95]; %New plot position [X Y W H]
|
||||
set(gca, 'Position', NewPos);
|
||||
if length(sep) == 7
|
||||
legend('16:46', '17:27', '17:54', '18:27', '18:56', '19:35', "location", 'northeastoutside' )
|
||||
else
|
||||
legend('16:46', '17:27', '17:54', '18:27', '18:56', "location", 'northeastoutside' )
|
||||
endif
|
||||
box off
|
||||
axis off
|
||||
|
||||
#disp(percentResults);
|
||||
#disp(totalResults);
|
||||
|
||||
figure;
|
||||
for d=1:length(datasets)
|
||||
subplot(4,2,d)
|
||||
data=percentResults{1,d}*100;
|
||||
data(isnan(data)) = 0;
|
||||
hAxes = gca;
|
||||
% Upscaling the image to reduce anti-aliasing effect in pfd viewers
|
||||
scale = 50;
|
||||
tickXStep = zeros(1, size(data, 2));
|
||||
tickYStep = zeros(1, size(data, 1));
|
||||
dataUp = upsample(upsample(data',scale)',scale);
|
||||
for x=0:size(data, 2)-1
|
||||
for y=1:scale-1
|
||||
dataUp(:,(x*scale+1)+y) = dataUp(:,x*scale+1);
|
||||
endfor
|
||||
tickXStep(1,x+1) = scale/2 + scale*x;
|
||||
endfor
|
||||
for x=0:size(data, 1)-1
|
||||
for y=1:scale-1
|
||||
dataUp((x*scale+1)+y,:) = dataUp(x*scale+1,:);
|
||||
endfor
|
||||
tickYStep(1,x+1) = scale/2 + scale*x;
|
||||
endfor
|
||||
imagesc( hAxes, dataUp, [0, 100])
|
||||
%title({"",datasetsName{datasets(d)+1}})
|
||||
colors = [ones(100,1) [1:100]'*0.01 [1:100]'*0];
|
||||
colors(1,:) = 1;
|
||||
colormap( hAxes , colors)
|
||||
c = colorbar;
|
||||
labels = {};
|
||||
for v=get(c,'ytick'), labels{end+1} = sprintf('%d%%',v); end
|
||||
set(c,'yticklabel',labels);
|
||||
if mod(d,2) == 1
|
||||
ylabel("Map")
|
||||
endif
|
||||
xlabel([datasetsName{datasets(d)+1} " Localization"])
|
||||
set(gca, "xaxislocation", "top");
|
||||
set(gca, 'XTick', tickXStep)
|
||||
set(gca, 'XTickLabel', sepName, 'fontsize',7)
|
||||
set(gca, 'YTick', tickYStep)
|
||||
if resultsToShow == 3
|
||||
set(gca, 'YTickLabel', {'16:46', '17:27', '17:54', '18:27', '18:56'}, 'fontsize',7)
|
||||
elseif resultsToShow == 2
|
||||
set(gca, 'YTickLabel', {'1+6', '1+3+5', '2+4+6', '1+2+3+4+5+6', '1-2-3-4-5-6', 'not set'}, 'fontsize',7)
|
||||
else
|
||||
set(gca, 'YTickLabel', {'16:46', '17:27', '17:54', '18:27', '18:56', '19:35'}, 'fontsize',7)
|
||||
endif
|
||||
endfor
|
||||
|
||||
% compute cumulative localizations
|
||||
cumResults = zeros(curves+2, length(datasets)+1);
|
||||
for d=1:length(datasets)
|
||||
cumResults(1,d+1) = datasets(d);
|
||||
cumResults(2:end-1,d+1) = round(sum(locResults{1,d}, 2) ./ sum(totalResults{1,d}, 2) * 100);
|
||||
if resultsToShow == 1
|
||||
cumResults(end,d+1) = round(sum(sum(locResults{1,d}.*eye(curves,curves))) / sum(totalResults{1,d},2)(1,1) * 100);
|
||||
endif
|
||||
end
|
||||
cumResults(2:end-1,1) = 1:curves;
|
||||
cumResults
|
||||
109
archive/2022-IlluminationInvariant/results_loc_prob_by_dist.m
Normal file
109
archive/2022-IlluminationInvariant/results_loc_prob_by_dist.m
Normal file
@@ -0,0 +1,109 @@
|
||||
|
||||
clear all
|
||||
close all
|
||||
|
||||
# sudo apt install octave-signal
|
||||
pkg load signal
|
||||
|
||||
# Use with files generated by export_stats.sh
|
||||
|
||||
dataDir = '2'; % '0'(old) '1'(new) '2' (revised april 2022)
|
||||
prefix = 'Stat';
|
||||
|
||||
dataset = 6
|
||||
sep = [0, 1000, 3000, 5000, 7000, 9000, 12000];
|
||||
sepName = {'16:51', '17:31', '17:58', '18:30', '18:59', '19:42'};
|
||||
|
||||
statName = strrep('Loop/Distance_since_last_loc/','/','-');
|
||||
|
||||
data = dlmread([dataDir '/' prefix num2str(dataset) '-' statName '.txt'], '\t', 1, 0, "emptyvalue", 0);
|
||||
|
||||
sessions = size(data,2)-1
|
||||
|
||||
j = 1 % session #
|
||||
x3 = data(:,1);
|
||||
y3 = data(:,11);
|
||||
y3 = y3(x3>=sep(j) & x3<=sep(j+1), :);
|
||||
x3 = x3(x3>=sep(j) & x3<=sep(j+1), :);
|
||||
|
||||
max = 0;
|
||||
for i=2:length(y3)
|
||||
if isfinite(y3(i)) && isfinite(y3(i-1)) && (x3(i) - x3(i-1) < 1.5)
|
||||
v = y3(i);
|
||||
if v>max
|
||||
max = v
|
||||
endif
|
||||
endif
|
||||
endfor
|
||||
xb = max/2:max:5;
|
||||
[nn3, xx3] = hist (y3, xb);
|
||||
nn3 = nn3/length(x3);
|
||||
nn3(nn3==0) = NaN;
|
||||
|
||||
for j=1:6
|
||||
|
||||
x{j} = data(:,1);
|
||||
y{j} = data(:,2);
|
||||
y{j} = y{j}(x{j}>=sep(j) & x{j}<=sep(j+1), :);
|
||||
x{j} = x{j}(x{j}>=sep(j) & x{j}<=sep(j+1), :);
|
||||
[nn{j}, xx{j}] = hist (y{j}, xb);
|
||||
%nn{j} = nn{j}/length(x{j});
|
||||
%nn{j} = nn{j}/sum(nn{j});
|
||||
|
||||
for k=length(nn{j}):-1:1
|
||||
if nn{j}(k) != 0
|
||||
break;
|
||||
else
|
||||
nn{j}(k) = NaN;
|
||||
endif
|
||||
endfor
|
||||
|
||||
endfor
|
||||
|
||||
j = 6 % session #
|
||||
x4 = data(:,1);
|
||||
y4 = data(:,12);
|
||||
y4 = y4(x4>=sep(j) & x4<=sep(j+1), :);
|
||||
x4 = x4(x4>=sep(j) & x4<=sep(j+1), :);
|
||||
[nn4, xx4] = hist (y4, xb);
|
||||
nn4 = nn4/length(x4);
|
||||
nn4(nn4==0) = NaN;
|
||||
|
||||
figure
|
||||
hold on
|
||||
%plot(x1,y1, '.-');
|
||||
%plot(x2-x2(1),y2, '.-');
|
||||
plot(x3-x3(1),y3, '.-');
|
||||
%plot(x4-x4(1),y4, '.-');
|
||||
%legend('Map1 -> LocA', 'Map1 -> LocF', 'Map1+2+3+4+5+6 -> LocF', 'Map1-2-3-4-5-6 -> LocF')
|
||||
legend('Map1+2+3+4+5+6 -> LocA')
|
||||
xlabel('Time')
|
||||
ylabel('m')
|
||||
title('Distance since last loc')
|
||||
|
||||
figure
|
||||
hold on
|
||||
%plot(x1,y1, '.-');
|
||||
%plot(x2-x2(1),y2, '.-');
|
||||
plot(x{6}-x{6}(1),y{6}, '.-');
|
||||
%plot(x4-x4(1),y4, '.-');
|
||||
%legend('Map1 -> LocA', 'Map1 -> LocF', 'Map1+2+3+4+5+6 -> LocF', 'Map1-2-3-4-5-6 -> LocF')
|
||||
legend('Map1 -> LocF')
|
||||
xlabel('Time')
|
||||
ylabel('m')
|
||||
title('Distance since last loc')
|
||||
|
||||
figure
|
||||
hold on
|
||||
for j=1:6
|
||||
plot(xx{j},nn{j}, '-', 'linewidth', 3)
|
||||
endfor
|
||||
%plot(xx3,nn3, '.-', 'linewidth', 3)
|
||||
%plot(xx4,nn4, '.-', 'linewidth', 3)
|
||||
%legend('Loc-F', 'Loc-E', 'Loc-D', 'Loc-C', 'Loc-B', 'Loc-A')
|
||||
legend('A-16:51', 'B-17:31', 'C-17:58', 'D-18:30', 'E-18:59', 'F-19:42', 'Map1+2+3+4+5+6 -> LocF', 'Map1-2-3-4-5-6 -> LocF')
|
||||
%h = get(gca,'Children');
|
||||
%set(gca,'Children',[h(6) h(5) h(4) h(3) h(2) h(1)])
|
||||
%set(gca, 'YScale', 'log')
|
||||
xlabel(['Distance not localized (m) Step ' num2str(max) ' m'])
|
||||
ylabel('Re-Localization Probability on Map 1 (16:46)')
|
||||
19
archive/2022-IlluminationInvariant/scripts/export_stats.sh
Executable file
19
archive/2022-IlluminationInvariant/scripts/export_stats.sh
Executable file
@@ -0,0 +1,19 @@
|
||||
#!/bin/bash
|
||||
|
||||
if [ $# -lt 1 ]
|
||||
then
|
||||
echo "No arguments supplied. It should be the data directory (where the reprocessed map databases are saved)."
|
||||
exit
|
||||
fi
|
||||
DATA=$1
|
||||
|
||||
DETECTOR=(0 1 6 7 9 14 11 111)
|
||||
|
||||
source rtabmap_latest.bash
|
||||
|
||||
for d in "${DETECTOR[@]}"
|
||||
do
|
||||
rtabmap-report --export --export_prefix "Stat$d" --loc 32 Loop/Odom_correction_norm/m Loop/Visual_inliers/ Timing/Total/ms Timing/Proximity_by_space_visual/ms Timing/Likelihood_computation/ms Timing/Posterior_computation/ms TimingMem/Keypoints_detection/ms TimingMem/Descriptors_extraction/ms TimingMem/Add_new_words/ms Loop/Map_id/ Keypoint/Current_frame/words Memory/RAM_usage/MB Memory/RAM_estimated/MB Memory/Distance_travelled/m Loop/Distance_since_last_loc/ Memory/Local_graph_size/ Keypoint/Dictionary_size/words "$DATA/$d/loc"
|
||||
rtabmap-report --export --export_prefix "Consecutive$d" --loc 32 Loop/Map_id/ Loop/Distance_since_last_loc/ "$DATA/$d/consecutive_loc"
|
||||
done
|
||||
|
||||
40
archive/2022-IlluminationInvariant/scripts/reprocess_maps.sh
Executable file
40
archive/2022-IlluminationInvariant/scripts/reprocess_maps.sh
Executable file
@@ -0,0 +1,40 @@
|
||||
#!/bin/bash
|
||||
|
||||
if [ $# -lt 2 ]
|
||||
then
|
||||
echo "No arguments supplied. It should be the detector number type (0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK 8=GFTT/ORB 9=KAZE 10=ORB-OCTREE 11=SuperPoint) and the data directory (where reprocessed map databases will be saved)."
|
||||
exit
|
||||
fi
|
||||
TYPE=$1
|
||||
DATA=$2
|
||||
|
||||
source rtabmap_latest.bash
|
||||
|
||||
[ ! -d "$DATA" ] && mkdir $DATA
|
||||
[ ! -d "$DATA/$TYPE" ] && mkdir $DATA/$TYPE
|
||||
# 'map_190321-164651.db' 'map_190321-172717.db' 'map_190321-175428.db' 'map_190321-182709.db' 'map_190321-185608.db' 'map_190321-193556.db'
|
||||
DATABASES=( 'map_190321-164651.db' 'map_190321-172717.db' 'map_190321-175428.db' 'map_190321-182709.db' 'map_190321-185608.db' 'map_190321-193556.db' )
|
||||
|
||||
PARAMS="--Kp/DetectorStrategy $TYPE --Vis/FeatureType $TYPE"
|
||||
|
||||
if [ $TYPE -eq 2 ] || [ $TYPE -eq 3 ] || [ $TYPE -eq 4 ] || [ $TYPE -eq 5 ] || [ $TYPE -eq 6 ] || [ $TYPE -eq 7 ] || [ $TYPE -eq 8 ] || [ $TYPE -eq 10 ] || [ $TYPE -eq 12 ]
|
||||
then
|
||||
# binary descriptors
|
||||
PARAMS="--Vis/CorNNDR 0.8 $PARAMS"
|
||||
else
|
||||
# float descriptors
|
||||
PARAMS="--Vis/CorNNDR 0.6 $PARAMS"
|
||||
fi
|
||||
|
||||
if [ $TYPE -eq 111 ]
|
||||
then
|
||||
PARAMS="--Vis/CorNNType 6 --SuperGlue/Path ~/workspace/SuperGluePretrainedNetwork/rtabmap_superglue.py --Reg/RepeatOnce false --Vis/CorGuessWinSize 0 $PARAMS --Kp/DetectorStrategy 11 --Vis/FeatureType 11"
|
||||
fi
|
||||
|
||||
echo $PARAMS
|
||||
for db in "${DATABASES[@]}"
|
||||
do
|
||||
rtabmap-reprocess --RGBD/MarkerDetection false --RGBD/ProximityBySpace true --RGBD/LocalRadius 1 --Mem/InitWMWithAllNodes true --Rtabmap/TimeThr 0 --Mem/UseOdomFeatures false --Optimizer/GravitySigma 0.1 --Mem/UseOdomGravity true --RGBD/OptimizeFromGraphEnd false --Mem/DepthAsMask false --RGBD/OptimizeMaxError 10 --RGBD/ProximityOdomGuess false --Vis/MaxFeatures 1000 --Kp/MaxFeatures 400 --Vis/EpipolarGeometryVar 0.1 --Vis/EstimationType 1 --Vis/MinInliers 20 --Rtabmap/MaxRetrieved 2 --Optimizer/Iterations 20 --Mem/CompressionParallelized true --Kp/Parallelized true --Kp/MaxDepth 0 --Kp/BadSignRatio 0.2 --BRIEF/Bytes 32 --Kp/ByteToFloat true --SURF/HessianThreshold 100 --SIFT/ContrastThreshold 0.02 --BRISK/Thresh 10 --SuperPoint/ModelPath superpoint.pt --Rtabmap/PublishRAMUsage true --ORB/EdgeThreshold 19 --ORB/ScaleFactor 2 --ORB/NLevels 3 --Db/TargetVersion "" --Icp/CorrespondenceRatio 0.1 --RGBD/MaxOdomCacheSize 0 --uerror $PARAMS $db $DATA/$TYPE/$db
|
||||
rtabmap-detectMoreLoopClosures --uwarn $DATA/$TYPE/$db
|
||||
done
|
||||
|
||||
17
archive/2022-IlluminationInvariant/scripts/reprocess_maps_all.sh
Executable file
17
archive/2022-IlluminationInvariant/scripts/reprocess_maps_all.sh
Executable file
@@ -0,0 +1,17 @@
|
||||
#!/bin/bash
|
||||
|
||||
if [ $# -lt 1 ]
|
||||
then
|
||||
echo "No arguments supplied. It should be the data directory (where the reprocessed map databases will be saved)."
|
||||
exit
|
||||
fi
|
||||
DATA=$1
|
||||
|
||||
DETECTOR=(0 1 6 7 9 14 11 111)
|
||||
|
||||
for d in "${DETECTOR[@]}"
|
||||
do
|
||||
./reprocess_maps.sh $d $DATA
|
||||
./run_merge.sh $d $DATA
|
||||
done
|
||||
|
||||
5
archive/2022-IlluminationInvariant/scripts/rtabmap_latest.bash
Executable file
5
archive/2022-IlluminationInvariant/scripts/rtabmap_latest.bash
Executable file
@@ -0,0 +1,5 @@
|
||||
#!/bin/bash
|
||||
|
||||
export PATH=~/workspace/rtabmap/build/bin:$PATH
|
||||
export LD_LIBRARY_PATH=~/workspace/rtabmap/build/lib:$LD_LIBRARY_PATH
|
||||
|
||||
13
archive/2022-IlluminationInvariant/scripts/run_all.sh
Executable file
13
archive/2022-IlluminationInvariant/scripts/run_all.sh
Executable file
@@ -0,0 +1,13 @@
|
||||
#!/bin/bash
|
||||
|
||||
if [ $# -lt 1 ]
|
||||
then
|
||||
echo "No arguments supplied. It should be the data directory (where the reprocessed map databases will be saved)."
|
||||
exit
|
||||
fi
|
||||
DATA=$1
|
||||
|
||||
./reprocess_maps_all.sh $DATA
|
||||
./run_localization_single_all.sh $DATA
|
||||
./run_consecutive_localization_all.sh $DATA
|
||||
|
||||
25
archive/2022-IlluminationInvariant/scripts/run_consecutive_localization.sh
Executable file
25
archive/2022-IlluminationInvariant/scripts/run_consecutive_localization.sh
Executable file
@@ -0,0 +1,25 @@
|
||||
#!/bin/bash
|
||||
|
||||
if [ $# -lt 2 ]
|
||||
then
|
||||
echo "No arguments supplied. It should be the detector number type (0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK 8=GFTT/ORB 9=KAZE 10=ORB-OCTREE 11=SuperPoint) and the data directory (where map databases have been reprocessed)."
|
||||
exit
|
||||
fi
|
||||
TYPE=$1
|
||||
DATA=$2
|
||||
|
||||
source rtabmap_latest.bash
|
||||
|
||||
SOURCE=('map_190321-164651.db' 'map_190321-172717.db' 'map_190321-175428.db' 'map_190321-182709.db' 'map_190321-185608.db')
|
||||
TARGETS=($DATA/$TYPE'/map_190321-172717.db;'$DATA/$TYPE'/map_190321-175428.db;'$DATA/$TYPE'/map_190321-193556.db' $DATA/$TYPE'/map_190321-175428.db;'$DATA/$TYPE'/map_190321-182709.db;' $DATA/$TYPE'/map_190321-182709.db;'$DATA/$TYPE'/map_190321-185608.db' $DATA/$TYPE'/map_190321-185608.db;'$DATA/$TYPE'/map_190321-193556.db' $DATA/$TYPE'/map_190321-193556.db' )
|
||||
|
||||
|
||||
[ ! -d "$DATA/$TYPE/consecutive_loc" ] && mkdir $DATA/$TYPE/consecutive_loc
|
||||
|
||||
for i in ${!SOURCE[@]}
|
||||
do
|
||||
db=${SOURCE[$i]}
|
||||
loc_dbs=${TARGETS[$i]}
|
||||
rtabmap-reprocess --Mem/IncrementalMemory false --RGBD/ProximityBySpace true --RGBD/ProximityMaxPaths 1 --Mem/LocalizationDataSaved true --Mem/BinDataKept false --RGBD/SavedLocalizationIgnored true --Kp/IncrementalFlann false --Vis/MinInliers 20 --Rtabmap/PublishRAMUsage true --RGBD/ProximityOdomGuess false --uwarn "$DATA/$TYPE/$db;$loc_dbs" $DATA/$TYPE/consecutive_loc/loc_$db
|
||||
done
|
||||
|
||||
@@ -0,0 +1,16 @@
|
||||
#!/bin/bash
|
||||
|
||||
if [ $# -lt 1 ]
|
||||
then
|
||||
echo "No arguments supplied. It should be the data directory (where the reprocessed map databases will be saved)."
|
||||
exit
|
||||
fi
|
||||
DATA=$1
|
||||
|
||||
DETECTOR=(0 1 6 7 9 14 11 111)
|
||||
|
||||
for d in "${DETECTOR[@]}"
|
||||
do
|
||||
./run_consecutive_localization.sh $d $DATA
|
||||
done
|
||||
|
||||
32
archive/2022-IlluminationInvariant/scripts/run_localization_accuracy.sh
Executable file
32
archive/2022-IlluminationInvariant/scripts/run_localization_accuracy.sh
Executable file
@@ -0,0 +1,32 @@
|
||||
#!/bin/bash
|
||||
|
||||
if [ $# -eq 0 ]
|
||||
then
|
||||
echo "No arguments supplied. It should be the detector number type (0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK 8=GFTT/ORB 9=KAZE 10=ORB-OCTREE 11=SuperPoint)."
|
||||
exit
|
||||
fi
|
||||
TYPE=$1
|
||||
|
||||
PREFIX="/home/mathieu/workspace/rtabmap_cv_latest/bin/"
|
||||
REPROCESS_TOOL="${PREFIX}rtabmap-reprocess"
|
||||
|
||||
# loc_190321-165128.db;loc_190321-173134.db;loc_190321-175823.db;loc_190321-183051.db;loc_190321-185950.db;loc_190321-194226.db
|
||||
LOCALIZATION_DATABASES="loc_190321-165128.db;loc_190321-173134.db;loc_190321-175823.db;loc_190321-183051.db;loc_190321-185950.db;loc_190321-194226.db"
|
||||
|
||||
[ ! -d "results/$TYPE/loc" ] && mkdir results/$TYPE/accuracy
|
||||
|
||||
db=merged_9999.db
|
||||
|
||||
$REPROCESS_TOOL --Mem/IncrementalMemory false --RGBD/ProximityBySpace true --Mem/LocalizationDataSaved true --Mem/BinDataKept false --RGBD/SavedLocalizationIgnored true --Kp/IncrementalFlann false --Vis/MinInliers 20 --Rtabmap/PublishRAMUsage true --RGBD/ProximityOdomGuess false --Reg/RepeatOnce true --Vis/BundleAdjustment 1 --uwarn "results/$TYPE/$db;$LOCALIZATION_DATABASES" results/$TYPE/accuracy/ProxOff_DoubleRegOn_BaOn_$db
|
||||
|
||||
$REPROCESS_TOOL --Mem/IncrementalMemory false --RGBD/ProximityBySpace true --Mem/LocalizationDataSaved true --Mem/BinDataKept false --RGBD/SavedLocalizationIgnored true --Kp/IncrementalFlann false --Vis/MinInliers 20 --Rtabmap/PublishRAMUsage true --RGBD/ProximityOdomGuess false --Reg/RepeatOnce false --Vis/BundleAdjustment 1 --uwarn "results/$TYPE/$db;$LOCALIZATION_DATABASES" results/$TYPE/accuracy/ProxOff_DoubleRegOff_BaOn_$db
|
||||
|
||||
$REPROCESS_TOOL --Mem/IncrementalMemory false --RGBD/ProximityBySpace true --Mem/LocalizationDataSaved true --Mem/BinDataKept false --RGBD/SavedLocalizationIgnored true --Kp/IncrementalFlann false --Vis/MinInliers 20 --Rtabmap/PublishRAMUsage true --RGBD/ProximityOdomGuess false --Reg/RepeatOnce true --Vis/BundleAdjustment 0 --uwarn "results/$TYPE/$db;$LOCALIZATION_DATABASES" results/$TYPE/accuracy/ProxOff_DoubleRegOn_BaOff_$db
|
||||
|
||||
$REPROCESS_TOOL --Mem/IncrementalMemory false --RGBD/ProximityBySpace true --Mem/LocalizationDataSaved true --Mem/BinDataKept false --RGBD/SavedLocalizationIgnored true --Kp/IncrementalFlann false --Vis/MinInliers 20 --Rtabmap/PublishRAMUsage true --RGBD/ProximityOdomGuess false --Reg/RepeatOnce false --Vis/BundleAdjustment 0 --uwarn "results/$TYPE/$db;$LOCALIZATION_DATABASES" results/$TYPE/accuracy/ProxOff_DoubleRegOff_BaOff_$db
|
||||
|
||||
$REPROCESS_TOOL --Mem/IncrementalMemory false --RGBD/ProximityBySpace true --Mem/LocalizationDataSaved true --Mem/BinDataKept false --RGBD/SavedLocalizationIgnored true --Kp/IncrementalFlann false --Vis/MinInliers 20 --Rtabmap/PublishRAMUsage true --RGBD/ProximityOdomGuess true --Reg/RepeatOnce true --Vis/BundleAdjustment 1 --uwarn "results/$TYPE/$db;$LOCALIZATION_DATABASES" results/$TYPE/accuracy/ProxOn_DoubleRegOn_BaOn_$db
|
||||
|
||||
$REPROCESS_TOOL --Mem/IncrementalMemory false --RGBD/ProximityBySpace true --Mem/LocalizationDataSaved true --Mem/BinDataKept false --RGBD/SavedLocalizationIgnored true --Kp/IncrementalFlann false --Vis/MinInliers 20 --Rtabmap/PublishRAMUsage true --RGBD/ProximityOdomGuess true --Reg/RepeatOnce true --Vis/BundleAdjustment 0 --uwarn "results/$TYPE/$db;$LOCALIZATION_DATABASES" results/$TYPE/accuracy/ProxOn_DoubleRegOn_BaOff_$db
|
||||
|
||||
|
||||
26
archive/2022-IlluminationInvariant/scripts/run_localization_single.sh
Executable file
26
archive/2022-IlluminationInvariant/scripts/run_localization_single.sh
Executable file
@@ -0,0 +1,26 @@
|
||||
#!/bin/bash
|
||||
|
||||
if [ $# -lt 2 ]
|
||||
then
|
||||
echo "No arguments supplied. It should be the detector number type (0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK 8=GFTT/ORB 9=KAZE 10=ORB-OCTREE 11=SuperPoint) and the data directory (where map databases have been reprocessed)."
|
||||
exit
|
||||
fi
|
||||
TYPE=$1
|
||||
DATA=$2
|
||||
|
||||
source rtabmap_latest.bash
|
||||
|
||||
# 'map_190321-164651.db' 'map_190321-172717.db' 'map_190321-175428.db' 'map_190321-182709.db' 'map_190321-185608.db' 'map_190321-193556.db' 'merged_123456.db' 'merged_135.db' 'merged_246.db' 'merged_16.db' 'merged_123456_reduced.db'
|
||||
DATABASES=('map_190321-164651.db' 'map_190321-172717.db' 'map_190321-175428.db' 'map_190321-182709.db' 'map_190321-185608.db' 'map_190321-193556.db' 'merged_123456.db' 'merged_135.db' 'merged_246.db' 'merged_16.db' 'merged_123456_reduced.db')
|
||||
# loc_190321-165128.db;loc_190321-173134.db;loc_190321-175823.db;loc_190321-183051.db;loc_190321-185950.db;loc_190321-194226.db
|
||||
LOCALIZATION_DATABASES="loc_190321-165128.db;loc_190321-173134.db;loc_190321-175823.db;loc_190321-183051.db;loc_190321-185950.db;loc_190321-194226.db"
|
||||
|
||||
[ ! -d "$DATA/$TYPE/loc" ] && mkdir $DATA/$TYPE/loc
|
||||
|
||||
echo $PARAMS
|
||||
for db in "${DATABASES[@]}"
|
||||
do
|
||||
rtabmap-reprocess -loc_null --Mem/IncrementalMemory false --RGBD/ProximityBySpace true --RGBD/ProximityMaxPaths 1 --Mem/LocalizationDataSaved true --Mem/BinDataKept false --RGBD/SavedLocalizationIgnored true --Kp/IncrementalFlann false --Vis/MinInliers 20 --Rtabmap/PublishRAMUsage true --RGBD/ProximityOdomGuess false --uwarn "$DATA/$TYPE/$db;$LOCALIZATION_DATABASES" $DATA/$TYPE/loc/loc_$db
|
||||
done
|
||||
|
||||
|
||||
16
archive/2022-IlluminationInvariant/scripts/run_localization_single_all.sh
Executable file
16
archive/2022-IlluminationInvariant/scripts/run_localization_single_all.sh
Executable file
@@ -0,0 +1,16 @@
|
||||
#!/bin/bash
|
||||
|
||||
if [ $# -lt 1 ]
|
||||
then
|
||||
echo "No arguments supplied. It should be the data directory (where the reprocessed map databases will be saved)."
|
||||
exit
|
||||
fi
|
||||
DATA=$1
|
||||
|
||||
DETECTOR=(0 1 6 7 9 14 11 111)
|
||||
|
||||
for d in "${DETECTOR[@]}"
|
||||
do
|
||||
./run_localization_single.sh $d $DATA
|
||||
done
|
||||
|
||||
34
archive/2022-IlluminationInvariant/scripts/run_merge.sh
Executable file
34
archive/2022-IlluminationInvariant/scripts/run_merge.sh
Executable file
@@ -0,0 +1,34 @@
|
||||
#!/bin/bash
|
||||
|
||||
if [ $# -lt 2 ]
|
||||
then
|
||||
echo "No arguments supplied. It should be the detector number type (0=SURF 1=SIFT 2=ORB 3=FAST/FREAK 4=FAST/BRIEF 5=GFTT/FREAK 6=GFTT/BRIEF 7=BRISK 8=GFTT/ORB 9=KAZE 10=ORB-OCTREE 11=SuperPoint) and the data directory (where map databases have been reprocessed)."
|
||||
exit
|
||||
fi
|
||||
TYPE=$1
|
||||
DATA=$2
|
||||
|
||||
MIN_INLIERS=20 #20 40 60 80
|
||||
|
||||
source rtabmap_latest.bash
|
||||
|
||||
DATABASES="$DATA/$TYPE/map_190321-164651.db;$DATA/$TYPE/map_190321-172717.db;$DATA/$TYPE/map_190321-175428.db;$DATA/$TYPE/map_190321-182709.db;$DATA/$TYPE/map_190321-185608.db;$DATA/$TYPE/map_190321-193556.db"
|
||||
|
||||
# To compute "Ground truth"
|
||||
rtabmap-reprocess --uwarn --RGBD/OptimizeMaxError 10 "$DATABASES" $DATA/$TYPE/merged_123456.db
|
||||
|
||||
cp $DATA/$TYPE/merged_123456.db $DATA/$TYPE/merged_123456_gt.db
|
||||
rtabmap-detectMoreLoopClosures -r 0.5 -i 5 $DATA/$TYPE/merged_123456_gt.db
|
||||
|
||||
rtabmap-reprocess --uwarn --RGBD/OptimizeMaxError 10 -gt $DATA/$TYPE/merged_123456_gt.db $DATA/$TYPE/merged_123456.db
|
||||
|
||||
rtabmap-reprocess --uwarn --RGBD/OptimizeMaxError 10 "$DATA/$TYPE/map_190321-164651.db;$DATA/$TYPE/map_190321-193556.db" $DATA/$TYPE/merged_16.db
|
||||
|
||||
rtabmap-reprocess --uwarn --RGBD/OptimizeMaxError 10 "$DATA/$TYPE/map_190321-164651.db;$DATA/$TYPE/map_190321-175428.db;$DATA/$TYPE/map_190321-185608.db" $DATA/$TYPE/merged_135.db
|
||||
|
||||
rtabmap-reprocess --uwarn --RGBD/OptimizeMaxError 10 "$DATA/$TYPE/map_190321-172717.db;$DATA/$TYPE/map_190321-182709.db;$DATA/$TYPE/map_190321-193556.db" $DATA/$TYPE/merged_246.db
|
||||
|
||||
# Reduced graph
|
||||
rtabmap-reprocess --uwarn --RGBD/OptimizeMaxError 10 -gt --Mem/ReduceGraph true --Vis/MinInliers $MIN_INLIERS $DATA/$TYPE/merged_123456_gt.db $DATA/$TYPE/merged_123456_reduced.db
|
||||
|
||||
|
||||
19
archive/2022-IlluminationInvariant/scripts/valgrind.sh
Normal file
19
archive/2022-IlluminationInvariant/scripts/valgrind.sh
Normal file
@@ -0,0 +1,19 @@
|
||||
#!/bin/bash
|
||||
|
||||
if [ $# -lt 1 ]
|
||||
then
|
||||
echo "No arguments supplied. It should be the data directory (where the reprocessed map databases are saved)."
|
||||
exit
|
||||
fi
|
||||
DATA=$1
|
||||
|
||||
DETECTOR=(0 1 6 7 9 14 11 111)
|
||||
|
||||
source rtabmap_latest.bash
|
||||
|
||||
for d in "${DETECTOR[@]}"
|
||||
do
|
||||
valgrind --tool=massif --time-unit=ms --detailed-freq=1 --max-snapshots=100 rtabmap-reprocess --Mem/IncrementalMemory false --Kp/IncrementalFlann false "${DATA}/${d}/map_190321-164651.db;loc_190321-165128.db" output.db
|
||||
rm output.db
|
||||
done
|
||||
|
||||
108
archive/2022-IlluminationInvariant/showLoopOverTime.m
Executable file
108
archive/2022-IlluminationInvariant/showLoopOverTime.m
Executable file
@@ -0,0 +1,108 @@
|
||||
##close all
|
||||
##clear all
|
||||
|
||||
%% Use Export Poses in TORO format, then copy columns
|
||||
load vertexes.txt;
|
||||
load edges.txt;
|
||||
|
||||
set(0,'defaultAxesFontName', 'Times')
|
||||
set(0,'defaultTextFontName', 'Times')
|
||||
|
||||
%matlab indexes % rtabmap indexes
|
||||
endMap1 = 201; % ID=206
|
||||
endMap2 = 401; % ID=411
|
||||
endMap3 = 604; % ID=621
|
||||
endMap4 = 794; % ID=814
|
||||
endMap5 = 968; % ID=990
|
||||
endMap6 = 1201; % ID=1230
|
||||
|
||||
%% 3D
|
||||
|
||||
t = vertexes(:,1);
|
||||
|
||||
##figure
|
||||
##plot3(vertexes(1:endMap1,2), vertexes(1:endMap1,3), vertexes(1:endMap1,1))
|
||||
##hold on
|
||||
##plot3(vertexes(endMap1+1:endMap2,2), vertexes(endMap1+1:endMap2,3), vertexes(endMap1+1:endMap2,1))
|
||||
##plot3(vertexes(endMap2+1:endMap3,2), vertexes(endMap2+1:endMap3,3), vertexes(endMap2+1:endMap3,1))
|
||||
##plot3(vertexes(endMap3+1:endMap4,2), vertexes(endMap3+1:endMap4,3), vertexes(endMap3+1:endMap4,1))
|
||||
##plot3(vertexes(endMap4+1:endMap5,2), vertexes(endMap4+1:endMap5,3), vertexes(endMap4+1:endMap5,1))
|
||||
##plot3(vertexes(endMap5+1:end,2), vertexes(endMap5+1:end,3), vertexes(endMap5+1:end,1))
|
||||
|
||||
mapIds = zeros(vertexes(end,1), 2); % matlab index to vertexes, map id
|
||||
for i=1:size(vertexes,1)
|
||||
mapIds(vertexes(i,1),1) = i;
|
||||
if i <= endMap1
|
||||
mapIds(vertexes(i,1),2) = 1;
|
||||
elseif i<=endMap2
|
||||
mapIds(vertexes(i,1),2) = 2;
|
||||
elseif i<=endMap3
|
||||
mapIds(vertexes(i,1),2) = 3;
|
||||
elseif i<=endMap4
|
||||
mapIds(vertexes(i,1),2) = 4;
|
||||
elseif i<=endMap5
|
||||
mapIds(vertexes(i,1),2) = 5;
|
||||
else
|
||||
mapIds(vertexes(i,1),2) = 6;
|
||||
end
|
||||
|
||||
end
|
||||
|
||||
##interLoopClosures = 0;
|
||||
##intraLoopClosures = 0;
|
||||
##
|
||||
##for i=1:size(edges, 1)
|
||||
## if edges(i,2) > edges(i,1)+1
|
||||
## x = [vertexes(mapIds(edges(i,1),1), 2) vertexes(mapIds(edges(i,2),1), 2)];
|
||||
## y = [vertexes(mapIds(edges(i,1),1), 3) vertexes(mapIds(edges(i,2),1), 3)];
|
||||
## t = [vertexes(mapIds(edges(i,1),1), 1) vertexes(mapIds(edges(i,2),1), 1)];
|
||||
## if mapIds(edges(i,1),2) ~= mapIds(edges(i,2),2)
|
||||
## plot3(x,y,t, 'g')
|
||||
## interLoopClosures = interLoopClosures+1;
|
||||
## else
|
||||
## plot3(x,y,t, 'r')
|
||||
## intraLoopClosures = intraLoopClosures + 1;
|
||||
## end
|
||||
## end
|
||||
##end
|
||||
##xlabel('x')
|
||||
##ylabel('y')
|
||||
##zlabel('Node indexes')
|
||||
##
|
||||
##interLoopClosures
|
||||
##intraLoopClosures
|
||||
|
||||
%% 2D
|
||||
figure
|
||||
hold on
|
||||
plot([-8 6], [vertexes(endMap1,1) vertexes(endMap1,1)], 'k:')
|
||||
plot([-8 6], [vertexes(endMap2,1) vertexes(endMap2,1)], 'k:')
|
||||
plot([-8 6], [vertexes(endMap3,1) vertexes(endMap3,1)], 'k:')
|
||||
plot([-8 6], [vertexes(endMap4,1) vertexes(endMap4,1)], 'k:')
|
||||
plot([-8 6], [vertexes(endMap5,1) vertexes(endMap5,1)], 'k:')
|
||||
|
||||
colors = {'r:', 'g:', 'c:', 'y:', 'm:', 'c'};
|
||||
|
||||
for i=1:size(edges, 1)
|
||||
if edges(i,2) > edges(i,1)+1
|
||||
y = [vertexes(mapIds(edges(i,1),1), 3) vertexes(mapIds(edges(i,2),1), 3)];
|
||||
t = [vertexes(mapIds(edges(i,1),1), 1) vertexes(mapIds(edges(i,2),1), 1)];
|
||||
mapId = mapIds(edges(i,1),2);
|
||||
if mapId ~= mapIds(edges(i,2),2) && (mapId == 1 || mapIds(edges(i,2),2) == 1)
|
||||
plot(y,t, 'r')
|
||||
else
|
||||
%plot(y,t, 'r')
|
||||
end
|
||||
end
|
||||
end
|
||||
|
||||
curveColor = 'b'
|
||||
plot(vertexes(1:endMap1,3), vertexes(1:endMap1,1), curveColor)
|
||||
plot(vertexes(endMap1+1:endMap2,3), vertexes(endMap1+1:endMap2,1), curveColor)
|
||||
plot(vertexes(endMap2+1:endMap3,3), vertexes(endMap2+1:endMap3,1), curveColor)
|
||||
plot(vertexes(endMap3+1:endMap4,3), vertexes(endMap3+1:endMap4,1), curveColor)
|
||||
plot(vertexes(endMap4+1:endMap5,3), vertexes(endMap4+1:endMap5,1), curveColor)
|
||||
plot(vertexes(endMap5+1:end,3), vertexes(endMap5+1:end,1), 'k')
|
||||
|
||||
xlabel('y')
|
||||
ylabel('Node indexes')
|
||||
Reference in New Issue
Block a user