Compare commits

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137 Commits
Author SHA1 Message Date
matlabbe a58ec494d1 icpCC: when force3DoF is true, set z to 0 in data conversion 2021-03-28 09:28:55 -04:00
matlabbe 69735b6271 Added removeNaNFromPointCloud for PCLPointCloud2 type 2021-03-28 00:15:47 -04:00
matlabbe d002711f21 reprocess tool: Updated usage description to upgrade db version 2021-03-27 16:21:52 -04:00
matlabbe 06e85e140c Refactored RegistrationIcp: libpointmatcher yaml config usage / integrated CCCoreLib (#704)
* Refactored RegistrationIcp so that libpointmatcher yaml can work with icp odometry (we can then avoid refiltering data with local map of F2M). All data filtering (including libpointmatcher DataFilters) are done at the beginning of the function.

* ICP: Restored ref and data scans order for libpointmatcher (seems more stable this way).

* Fixed compilation error without libpointmatcher

* CCCoreLib integration (Icp/Strategy=2). Icp/PMForce4DoF is now Icp/Force4DoF. Icp/PM is now Icp/Strategy. Icp/PMOutlierRatio is now Icp/OutlierRatio.

* Fixed build without CCCoreLib

* Cleanup RegistrationIcp from third party functions.

* Preferences: disable libpointmatcher and cccorlib options if not available
2021-03-27 15:11:20 -04:00
matlabbe c4d127cae4 Export: added more options for pose format and image file name. 2021-03-21 19:05:24 -04:00
matlabbe 21737f9937 Added description fo RGBD/Enabled parameter 2021-03-17 23:58:12 -04:00
matlabbe ccc519ec58 Export: added --output name option. 2021-03-13 20:58:10 -05:00
matlabbe 1e4b172a7d Export: added poisson polygon size option 2021-03-13 19:01:09 -05:00
matlabbe 752509fb15 Rtabmap::detectMoreLoopClosures: added clusterRadiusMin parameter and update optimized poses after each accepted loop closure (also in MainWindow) like in DbViewer. Added graph::computeMinMax(poses). OdometryInfo: added guess transform. Export: added min/max axis ranges to filter nodes before expoting clouds. 2021-03-13 18:42:13 -05:00
matlabbe f6e17be2b4 Added ViewPlane XY, XZ and YZ options to GraphViewer
Parameter RGBD/SavedLocalizationIgnored now called RGBD/StartAtOrigin (updated description, used only in localization mode)
IcpReg: if Force4DoF, set lower covariance values for roll and pitch
DbViewer: updated detectMoreLoopClosures with new minRadius option and update optimized poses between each new accepted loop closures.
MainWindow: suppressed warning if depth image is not found in current node data (when rgb is).
3D Map view: changed default map point size to 1 (was 2)
2021-03-12 17:47:36 -05:00
matlabbe da2e2f810c Updated images 2021-03-09 17:48:40 -05:00
matlabbe 5b44c557b3 Update README.md 2021-03-09 17:44:39 -05:00
matlabbe 600d68932d updated images 2021-03-09 17:43:27 -05:00
matlabbe 800d087b07 Added archive directory to put paper related scripts 2021-03-09 17:08:42 -05:00
matlabbe db43479e44 Added ORB_SLAM3 support. IMU Filter: added base frame conversion option. (#698)
Referred issues:
#655
https://github.com/introlab/rtabmap_ros/issues/492

Note: IMU not supported yet with ORB_SLAM3.

Commits:
* Added orbslam3 support. UI-Source->IMU filtering: Added base frame conversion option of IMU data to uniformize yaw initialization. Madgwick: fixed yaw initialization accordingly to Z acc.

* fixed regression build error with ORB_SLAM2

* Renamed OdometryORBSLAM2 to OdometryORBSLAM (can be 2 or 3 now)
2021-03-09 16:00:41 -05:00
matlabbe 736c8aceae Export tool: show an error if file doesn't exist 2021-03-09 14:06:33 -05:00
matlabbe 351c659beb Integrated DepthAI (gen2) (#696)
* Added OAK-D camera support (DepthAI)

* Fixed build without DepthAI dependency

* Added minimum version 2 for depthai

* fixed trusty build
2021-03-07 12:27:21 -05:00
matlabbe ab8f0e2b34 Fixed #695 (footprint not cleared correctly when GridGlobal/OccupancyThr>0) 2021-03-05 18:35:49 -05:00
matlabbe 4f46d8e904 Updated some RGBD/Proximity**** parameter descriptions. Added parameter RGBD/LoopClosureIdentityGuess. Fixed local map cleared in localization when RGBD/SavedLocalizationIgnored is true (should then assume it is starting from origin). 2021-03-04 11:26:35 -05:00
matlabbe 98c69c4578 Fixed Force4DoF param not used exception on older libpointmatcher versions 2021-03-02 17:27:25 -05:00
matlabbe 4e4207a6dd CMake: updated to support latest g2oConfig.cmake (using targets) 2021-03-02 18:17:09 +00:00
matlabbe ea4cc7cb6c Refactored how IMU is used in odometry (if guess is not set, use imu orientation for guess). Changed canProcessIMU() to canProcessAsynIMU() to make it more clear for odometry approaches able to process IMU between image frames (VIO approaches). ZedOC: fixed device closed if imu is not detected. 2021-03-01 19:27:24 -05:00
matlabbe f7bc47572b Parameters: Icp/VoxelSize default updated from 0 to 0.05 2021-03-01 11:22:40 -05:00
matlabbe d119487dd7 Coloring scan (camera projection on point cloud) (#693)
* ExportClouds: Added camera projection options

* ExportClouds: fixed ceiling/floor filtering options not saved in config

* ExportClouds: fixed colorless scan points still exported when option is unchecked.

* Export tool: added --bin, --poses, --images, --las and --cam_projection options; export with intensity with --scan option. PDALWriter: added binary option (only used for PLY an PCD formats). Rtabmap: Do graph optimization if neighbor link refined and Mem/UseOdomGravity is used.
2021-03-01 09:56:37 -05:00
matlabbe 967c57d165 Added CameraStereoZedOC (Zed Open Capture driver).
* Added CameraStereoZedOC (Zed Open Capture driver). Calibration: added stereo baseline option, show warning if fx is very different after stereo calibration.

* Fixed build without Zed Open Capture. Fixed "any" prefix added to all tools when WITH_ZEDOC=ON. UI: fixed Zed Open Capture action not disabled when not built with it.
2021-02-28 10:31:18 -05:00
matlabbe 862eb0a90a CameraStereoVideo: added resolution options for usb camera 2021-02-25 22:22:44 -05:00
matlabbe cad184e82b Added Icp/PMForce4DoF parameter (works only with libpointmatcher > April 2020). Fixed some deprecated warnings. 2021-02-24 09:43:22 -05:00
matlabbe d61e463595 Updated About dialog with opencv license 2021-02-21 13:59:36 -05:00
matlabbe 5cdb346a35 Updated opencv license to Apache2 when version >= 4.5 2021-02-21 13:03:19 -05:00
matlabbe 8696a38343 Added parameter GridGlobal/AltitudeDelta 2021-02-21 13:00:16 -05:00
matlabbe e59aad03ed Fixed android build with latest laserScanFromPointCloud changes 2021-02-19 14:25:34 +00:00
matlabbe 9bf12742b1 fixed #688 2021-02-18 21:04:00 -05:00
matlabbe bb7e9edb9b Fixed create2DMap assert on 32FC2 when subscribing 2D scans with intensity. LaserScan: fixed assert when angle_min > angle_max (with angle_increment < 0) 2021-02-16 10:47:31 -05:00
matlabbe f871e4359d Fixed optimized map cleared when optimized graph is smaller than WM (poses should still refer to nodes in WM). Removed warning about max scan points smaller than actual scan (this can happen when assembling scans for proximity detection). Lowering default Icp/PMOutlierRatio to 0.85. 2021-02-12 18:40:40 -05:00
matlabbe 03cfaf2063 DBViewer: Added option to export odometry poses 2021-02-12 11:22:02 -05:00
matlabbe 089441a496 Fixed loadScan return 2D cloud for organized PCD 2021-02-10 21:35:09 -05:00
matlabbe 481a140f84 util3d: Refactored laserScanFromPointCloud() functions to return LaserScan with correct format instead of cv::Mat. 2021-02-07 17:27:55 -05:00
matlabbe c42a4e3d7e Fixed assert when loading database having optimized poses different from the working memory (force re-update graph in this case). 2021-02-06 15:10:18 -05:00
matlabbe c1a22609f3 Extract images: added timestamp.jpg/.png filname options (to match RGBD-SLAM pose format). Fixed wrong calibration file when first node is an intermdediate node. Export poses: ignore intermediate nodes when output frame is camera or scan. 2021-02-02 09:36:12 -05:00
matlabbe b759b1b4d1 DBReader: set calibrated true when only scans in db. RegIcp: added intensity matching option when complexity is low. OdomF2M: accept first key frame on low complexity if a guess is provided. DbViewer: added gravity visualization in 3D view. 2021-02-01 11:31:45 -05:00
matlabbe 6b119c1f90 Camera test view: show intensity/rgb/normals if input scans have them 2021-01-25 17:16:46 -05:00
matlabbe 7e298e1999 CameraImages: timestamp file is optional for pose format containing stamp 2021-01-25 13:21:39 -05:00
matlabbe c9472962d7 bumpt 0.20.9 version 2021-01-24 13:48:05 -05:00
matlabbe 4d75361fe0 CameraImages: support scan only dataset. 2021-01-24 13:21:30 -05:00
matlabbe e99c658276 fixed scan-only nodes wrongly set as intermediate nodes by default 2021-01-24 11:35:48 -05:00
matlabbe 57326214f1 Fixed texture projection when fx!=fy, cx!=w/2 or cy!=h/2 2021-01-24 10:39:36 -05:00
matlabbe 47e40ef34d MainWindow: add fake frustum when only lidar is received 2021-01-22 12:51:47 -05:00
matlabbe aa31a900fb fixed trusty build (#682)
* fixed trusty build (g2o backward compatibility)
2021-01-20 22:54:48 -05:00
matlabbe 28e624e6b2 fixed g2o build with c++14 #681 2021-01-20 10:45:45 -05:00
matlabbe 731b073ed8 Cleanup ObjDeletionHandler not used. Zed: fixed assert "qual >= sl::DEPTH_MODE::NONE && qual < sl::DEPTH_MODE::LAST" with latest sdk. 2021-01-19 17:24:38 -05:00
matlabbe 5d777469ff CameraRealSense2: refactored for freezing/crash issues on stop 2021-01-18 14:58:33 -05:00
matlabbe 70e9dff7da L515: downscale depth image if it has been upscaled during registration, fixed depth not correctly scaled in IR mode 2021-01-18 11:33:10 -05:00
matlabbe 814a243693 Add boost link dir on Windows #678 2021-01-17 15:06:47 -05:00
matlabbe c49785061f Added PyDetector (#677)
* Added PyDetector. Refactored PyMatcher.

* Fixed python freezing with multi-threading
2021-01-17 01:56:27 -05:00
matlabbe 0bc483b6d3 Added pdal optional dependency (export to LAS, E57, ...) 2021-01-14 15:49:18 -05:00
matlabbe eae5f2b428 fixed #674 2021-01-11 11:38:31 -05:00
matlabbe 94cf1dfd32 Fixed zero-ed 3D words when receiving odometry's 2D keypoints > Kp/MaxFeatures and empty 3D points 2021-01-09 20:52:34 -05:00
matlabbe 1a967127d9 Bump 0.20.8 version. Parameters: updated default of Vis/CorGuessWinSize=40 (was 20), GFTT/MinDistance=7 (was 3), Optimizer/GravitySigma=0.3 if built with g2o or gtsam. Those parameters help for smooth tracking on latest sensors with higher resolution and use IMU by default if available. Updated docker jfr2018 to use original parameters. CameraStereoZed: wait for imu to be available before sending frames (Zed-m and Zed2). 2021-01-08 13:04:24 -05:00
matlabbe 792c967d46 MainWindow: added driver options to differentiate between cameras having IMU or not (D400 vs D435i, ZED vs Zedm and Zed2). Enabled imu filtering by default for Freenect driver (Kinect XBOX360). 2021-01-08 01:10:23 -05:00
matlabbe a67dbc26f2 L515 refactoring (realsense v2.41.0, firmware 1.5.3): added IR-only mode support, fixed support with latest firmware, T265+L515 working, related to #574 #614 #629. MainWindow: Selecting RealSense2, ZED sdk, K4A, Mynteye drivers automatically enable gravity optimization (with IMU filtering). 2021-01-08 00:01:08 -05:00
matlabbe f1993d9cd7 android: fixed z-fighting on some android devices 2021-01-02 18:14:55 -05:00
matlabbe da99d7e4a0 disabled osx travis build (too long to do) 2020-12-20 00:07:34 -05:00
matlabbe e896ffb5c0 Update .travis.yml 2020-12-19 23:16:28 -05:00
matlabbe 04cbf56cc0 Update .travis.yml 2020-12-19 22:37:13 -05:00
matlabbe c5051bf82a Update .travis.yml 2020-12-19 21:38:13 -05:00
matlabbe 7a9f01b9a3 Update .travis.yml 2020-12-19 12:55:12 -05:00
matlabbe 70094edb75 Update .travis.yml 2020-12-19 12:38:36 -05:00
matlabbe eb2af19a89 Update .travis.yml 2020-12-19 12:28:02 -05:00
matlabbe af227bad51 Update .travis.yml 2020-12-19 12:21:25 -05:00
matlabbe ee63ce338a Update .travis.yml 2020-12-19 12:11:19 -05:00
matlabbe 1b3a6abb82 Update .travis.yml 2020-12-19 11:48:06 -05:00
matlabbe 4a8a20c7d1 Update .travis.yml 2020-12-19 11:24:19 -05:00
matlabbe a125797e50 Update .travis.yml
Added osx
2020-12-19 11:18:20 -05:00
matlabbe a6f0877045 Parameters: added Rtabmap/ImagesAlreadyRectified to odometry parameters (to be shown with --params) 2020-12-18 17:57:43 -05:00
matlabbe b5cae38eb9 Fixed -lBoost:timer not defined when building with latest GTSAM binaries 2020-12-18 17:01:11 -05:00
matlabbe d8ebbc2645 CameraK4A: rectifying color image (this improves a lot visual odometry accuracy) 2020-12-13 15:27:17 -05:00
matlabbe d700d09339 DataRecorder tool: interface changed to use config file (#661) 2020-12-13 12:42:58 -05:00
matlabbe 3104dff006 Update README.md 2020-12-13 11:10:22 -05:00
matlabbe 839045a538 package.xml: 0.20.7 2020-12-12 19:05:06 -05:00
matlabbe a824945816 package.xml: removed libvtk-qt as there are conflicts on noetic with libpcl-dev (which is using vtk7) 2020-12-12 17:32:30 -05:00
matlabbe 1acf8ff193 RegIcp: don't assert if normals cannot be computed properly before doing complexity check, just reject the transform 2020-12-12 16:53:07 -05:00
matlabbe 51826c9a97 RegIcp: fixed KDTreeMatcherIntensity build error on Mac. 2020-12-11 17:22:29 -05:00
matlabbe 7a5d04062d vtk8: disabled vtkOutputWindow 2020-12-11 17:05:37 -05:00
matlabbe 049238dd59 Gui: added L515 icon 2020-12-11 09:56:17 -05:00
42Max42 3271723034 superpoint, fixing slow convert after cnn (#659)
* fixing slow convert after cnn

* restoring cmake
2020-12-11 09:27:18 -05:00
matlabbe da8e76ffed rtabmap-matcher: added --calibration_to option (to use a different calibration file for the second image). 2020-12-05 13:21:58 -05:00
matlabbe 3131474102 Added Db/TargetVersion parameter (#652) 2020-12-03 15:45:40 -05:00
matlabbe 3ffc8ce73f DBViewer: enabled Reject button on landmark links 2020-11-30 23:17:47 -05:00
matlabbe ee44adeb1f fixed #648 (build error without OctoMap dependency) 2020-11-30 12:33:08 -05:00
matlabbe 96c1c81e22 fixed build with older libpointmatcher versions <10300 2020-11-29 19:30:30 -05:00
matlabbe 0022b6b993 ExportCloudsDialog: added colormap option when showing scans 2020-11-28 18:02:54 -05:00
matlabbe 721e046f5d fixed build 2020-11-28 17:36:42 -05:00
matlabbe d733029565 Increased version to 0.20.7. OdometryF2M: added support for intensity field, removed ignored key frames when there is low scan complexity. RegistrationIcp: added Icp/PMMatcherIntensity, Icp/PointToPlaneGroundNormalsUp and Icp/PointToPlaneLowComplexityStrategy parameters. Rtabmap: when graph optimized from end, increased optimization error before warning that resulting map correction is not identity (this could happen with GTSAM as the root is not perfectly fixed). CloudViewer: added coordinate frame scaling option, added rainbow colormap option for scan intensity. DBViewer: fixed local proximity merged scans not shown modified after refining those links, show intensity, fixed constraints view not updated after rejecting a link. MainWindow: added intesity support with odometry scans. 2020-11-28 17:28:34 -05:00
matlabbe 7859313beb AppVeyor: updated realsense2 sdk to 2.40. CameraRealSense2: When GlobalTimeSync option is off, don't wait 35 ms for imu (and fails), just take the latest one directly (https://github.com/introlab/rtabmap/issues/614#issuecomment-732244439). 2020-11-23 11:36:27 -05:00
matlabbe 80199f23b5 RegIcp: complexity, checking if second eigen value is also under Icp/PointToPlaneMinComplexity to limit to only one axis. DbViewer: fixed refine link with scans having RGB channel. 2020-11-22 19:32:01 -05:00
matlabbe bce7ae6acd Fixed GTSAM reference frame yaw drift over time when gravity links are used 2020-11-22 16:40:30 -05:00
matlabbe f88845e138 fixed #643 2020-11-22 14:29:05 -05:00
matlabbe bdc7be40b4 Fix for previous commit https://github.com/introlab/rtabmap/commit/e4cb59b74d69887fd67700420d408db5a6850663 (otherwise imu are ignored if globalTimeSync is off) 2020-11-22 12:38:21 -05:00
matlabbe e4cb59b74d Added suggestion from https://github.com/introlab/rtabmap/issues/614#issuecomment-731769818 2020-11-22 12:32:39 -05:00
matlabbe dab407e5b9 fixed https://github.com/introlab/rtabmap/commit/ad44b65a28c0bb16add80a3d0afb9c721f84ba68#commitcomment-44427459 2020-11-22 11:10:35 -05:00
matlabbe 98a499b603 Optimizer: fall back on g2o or gtsam first if one or the other is not available (instead of going TORO). ExportClouds: added ceiling and floor filtering options. 2020-11-22 01:23:08 -05:00
matlabbe f5d7dc2814 PreferencesDialog: Added Marker/MaxRange and Marker/MinRange parameters to UI. 2020-11-21 17:23:41 -05:00
matlabbe ab1aa5578a Fixed build 2020-11-21 17:12:09 -05:00
matlabbe ccbdb586da DbViewer: Added datbabase path to window title 2020-11-21 16:37:40 -05:00
f467f2af7f Added Marker/MaxRange and Marker/MinRange parameters (#630)
* ADD 3 meter limit for marker detections

* ADD Marker/MaxRange and Marker/MinRange parameters for controlling marker detection
ADD ctags ignore

Co-authored-by: John Paul Soliva <soliva@seaos.co.jp>
Co-authored-by: Tim Fronsee <tfronsee21@gmail.com>
2020-11-21 16:18:22 -05:00
matlabbe 7c4d2bbdf4 DbViewer: before resetting all changes, added a confirmation message box! 2020-11-21 16:15:27 -05:00
matlabbe fb206b4f1e DbViewer: fixed scan disappearing after editing constraint 2020-11-21 14:35:29 -05:00
matlabbe ddecefbb9c 💄 2020-11-21 12:34:17 -05:00
matlabbe ad44b65a28 Allow partial support for AliceVision v2.3.0 (see #564 for remaining issues) 2020-11-20 13:42:56 -05:00
matlabbe fdaaa6ccfa Fixed bug L500 gyro/acc not detected (#629) 2020-11-19 13:49:10 -05:00
matlabbe 34e1af7e22 RealSense2: added error message for L515 if resolution is not 640x480 30 fps (#629) 2020-11-19 10:38:15 -05:00
matlabbe 54e2688a1d Fixed build with pcl > 1.11.1 (#641) 2020-11-14 16:52:01 -05:00
matlabbe f9abcf9e35 fixed opencv2 build 2020-11-14 14:41:37 -05:00
matlabbe 01eb57f293 CameraImages: added configForEachFrame option (added to GUI too). CameraThread: for decimation, if depth is smaller than RGB, RGB is decimated first and if the resulting RGB image is smaller than the original depth, we then decimate the depth. 2020-11-14 13:39:12 -05:00
matlabbe 7be22d1b67 Added check to make sure input odometry poses are invertible. Source/DB: added stereo to depth option. 2020-11-06 21:37:59 -05:00
matlabbe 4b527f9c36 Update .appveyor.yml 2020-11-06 18:56:32 -05:00
matlabbe 4d965c2089 Update .appveyor.yml 2020-11-06 18:18:06 -05:00
matlabbe 47cbd633c3 Update .appveyor.yml 2020-11-06 18:11:29 -05:00
matlabbe b95537a680 Added c++11 definition when latest libpointmatcher is found 2020-11-06 16:37:29 -05:00
matlabbe e102243f0e Fixed weight=-8 bug when moving rehearsed node to trash 2020-11-06 14:47:10 -05:00
matlabbe e7a2f206a0 Gui: fixed warning scan not found when uncompressing data. Don't disable Mem/UseOdomFeatures checkbox anymore in monitoring mode (ROS). 2020-11-05 15:50:05 -05:00
matlabbe d04b1a13be multiband: add multi-camera support. rtabmap-export: updated options (now supporting creating point cloud from scans). 2020-11-04 14:02:18 -05:00
matlabbe 92b1dabf1c MainWindow: avoid uncompressing images/scans if they are not shown 2020-11-03 16:12:43 -05:00
matlabbe e269067d4c Texturing: add distanceToCamPolicy option 2020-11-03 16:11:37 -05:00
matlabbe 596cd10b69 Fixed -lBoost::timer not found on ubuntu18.04/arm64 (#587) 2020-11-01 13:08:55 -05:00
matlabbe 6a730b51c7 GUI-Preferences: disabled Daisy feature option on OpenCV 2 2020-11-01 13:01:23 -05:00
matlabbe 4ecf37a3ab fixed build with OpenCV 2.4 2020-11-01 12:49:21 -05:00
matlabbe 99275fba1d Added Daisy descriptor. ORB: updated default parameters. Making ORBOctree using ORB parameters. Updated Vis/CorNNDR default from 0.6 to 0.8 (increase number of matches with binary descriptors, increase slightly feature matching time with float descriptors). Note that jfr2018 scripts have been updated to use old value 0.6. rtabmap-info: show descriptor dimension and type. 2020-11-01 11:28:59 -05:00
matlabbe 25c2a51ee3 fixed windows build 2020-10-29 18:03:36 -04:00
matlabbe 600484e12c Update .appveyor.yml
#624
2020-10-29 11:52:25 -04:00
matlabbe 8878d9fcdf Update .appveyor.yml
#624
2020-10-29 11:44:31 -04:00
matlabbe 72e1649cdd DataRecorder: added imu filtering by default 2020-10-22 18:02:24 -04:00
matlabbe afbc0edbd6 Local occupancy grid: fixed empty obstacles with scans having intensity channel when Grid/RangeMax is used. 2020-10-21 15:38:19 -04:00
matlabbe fbc30042c4 Fixed biggest index/min/max when Grid/MaxGroundHeight is set (http://official-rtab-map-forum.67519.x6.nabble.com/Comparison-between-realsense-D435-vs-T265-vs-T265-D435-dual-setup-td6456i20.html) 2020-10-18 15:56:13 -04:00
matlabbe a4da1e14b4 SIFT: fixed SIFT not extracted with OpenCV >=4.4 and >=3.4.11 when nonfree is false 2020-10-17 20:34:24 -04:00
matlabbe 3047b7da6b CameraRealSense2: update for L515 support 2020-10-17 19:57:27 -04:00
matlabbe bbb3c56008 Fixed android build 2020-10-16 14:55:50 -04:00
217 changed files with 16366 additions and 5371 deletions
+15 -1
View File
@@ -35,7 +35,7 @@ install:
# OpenCV
#- ps: wget 'http://kent.dl.sourceforge.net/project/opencvlibrary/opencv-win/3.3.1/opencv-3.3.1-vc14.exe' -outfile opencv-3.3.1-vc14.exe
#- cmd: opencv-3.3.1-vc14.exe -o"C:\Program Files" -y
- ps: wget 'http://kent.dl.sourceforge.net/project/opencvlibrary/opencv-win/2.4.13/opencv-2.4.13.6-vc14.exe' -outfile opencv-2.4.13.6-vc14.exe
- ps: $url = "https://downloads.sourceforge.net/project/opencvlibrary/opencv-win/2.4.13/opencv-2.4.13.6-vc14.exe?r=&ts="+([int64](([datetime]::UtcNow)-(get-date "1/1/1970")).TotalSeconds) ; wget $url -outfile opencv-2.4.13.6-vc14.exe
- cmd: opencv-2.4.13.6-vc14.exe -o"C:\Program Files" -y
- ECHO "Installed OpenCV:"
- ps: "ls \"C:/Program Files/opencv/build\""
@@ -115,6 +115,20 @@ install:
- cmd: yaml-cpp.exe -o"C:\Program Files" -y
- ECHO "Installed yaml-cpp:"
- ps: "ls \"C:/Program Files/yaml-cpp\""
# RealSense2
- ps: wget 'https://github.com/IntelRealSense/librealsense/releases/download/v2.40.0/Intel.RealSense.SDK-WIN10-2.40.0.2482.exe' -outfile realsense2.exe
- cmd: realsense2.exe /VERYSILENT
- ECHO "Installed RealSense2:"
- ps: "ls \"C:/Program Files (x86)/Intel RealSense SDK 2.0\""
- set PATH=%PATH%;C:\Program Files (x86)\Intel RealSense SDK 2.0\bin\x64
- set RealSense2_ROOT_DIR=C:\Program Files (x86)\Intel RealSense SDK 2.0
# Kinect 4 Azure
- ps: wget 'https://download.microsoft.com/download/3/d/6/3d6d9e99-a251-4cf3-8c6a-8e108e960b4b/Azure%20Kinect%20SDK%201.4.1.exe' -outfile azure.exe
- cmd: azure.exe /quiet
- ECHO "Installed Kinect For Azure:"
- ps: "ls \"C:/Program Files/Azure Kinect SDK v1.4.1\""
- set PATH=%PATH%;C:\Program Files\Azure Kinect SDK v1.4.1\tools
- set K4A_ROOT_DIR=C:\Program Files\Azure Kinect SDK v1.4.1
before_build:
- cd c:\projects\rtabmap\build
+2
View File
@@ -8,3 +8,5 @@ app/android/.classpath
app/android/.project
app/android/AndroidManifest.xml
app/android/res/raw/
compile_flags.txt
tags
+36 -29
View File
@@ -1,14 +1,19 @@
sudo: true
language: cpp
group: deprecated-2017Q3
compiler:
- gcc
matrix:
jobs:
include:
- dist: trusty
# - name: osx
# compiler: clang
# os: osx
# install:
# - brew install sqlite
# - brew install pcl
# - brew install opencv@3
- name: linux-trusty
compiler: gcc
os: linux
dist: trusty
install:
- sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu trusty main" > /etc/apt/sources.list.d/ros-latest.list'
- wget http://packages.ros.org/ros.key -O - | sudo apt-key add -
@@ -17,13 +22,13 @@ matrix:
- sudo apt-get -y install ros-indigo-rtabmap-ros
- sudo apt-get -y remove ros-indigo-rtabmap
script:
before_script:
- source /opt/ros/indigo/setup.bash
- mkdir -p build && cd build
- cmake ..
- make
- dist: xenial
- name: linux-xenial
compiler: gcc
os: linux
dist: xenial
install:
- sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu xenial main" > /etc/apt/sources.list.d/ros-latest.list'
- wget http://packages.ros.org/ros.key -O - | sudo apt-key add -
@@ -32,13 +37,13 @@ matrix:
- sudo apt-get -y install ros-kinetic-rtabmap-ros
- sudo apt-get -y remove ros-kinetic-rtabmap
script:
before_script:
- source /opt/ros/kinetic/setup.bash
- mkdir -p build && cd build
- cmake ..
- make
- dist: bionic
- name: linux-bionic
compiler: gcc
os: linux
dist: bionic
install:
- sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu bionic main" > /etc/apt/sources.list.d/ros-latest.list'
- wget http://packages.ros.org/ros.key -O - | sudo apt-key add -
@@ -47,13 +52,13 @@ matrix:
- sudo apt-get -y install ros-melodic-rtabmap-ros
- sudo apt-get -y remove ros-melodic-rtabmap
script:
before_script:
- source /opt/ros/melodic/setup.bash
- mkdir -p build && cd build
- cmake ..
- make
- dist: focal
- name: linux-focal
compiler: gcc
os: linux
dist: focal
install:
- sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu focal main" > /etc/apt/sources.list.d/ros-latest.list'
- wget http://packages.ros.org/ros.key -O - | sudo apt-key add -
@@ -62,11 +67,13 @@ matrix:
- sudo apt-get -y install ros-noetic-rtabmap-ros
- sudo apt-get -y remove ros-noetic-rtabmap
script:
before_script:
- source /opt/ros/noetic/setup.bash
- mkdir -p build && cd build
- cmake ..
- make
script:
- mkdir -p build && cd build
- cmake ..
- make
notifications:
email:
+190 -87
View File
@@ -21,7 +21,7 @@ SET(CMAKE_MODULE_PATH "${PROJECT_SOURCE_DIR}/cmake_modules")
#######################
SET(RTABMAP_MAJOR_VERSION 0)
SET(RTABMAP_MINOR_VERSION 20)
SET(RTABMAP_PATCH_VERSION 5)
SET(RTABMAP_PATCH_VERSION 9)
SET(RTABMAP_VERSION
${RTABMAP_MAJOR_VERSION}.${RTABMAP_MINOR_VERSION}.${RTABMAP_PATCH_VERSION})
@@ -163,8 +163,10 @@ ELSE()
option(WITH_QT "Include Qt support" ON)
ENDIF()
option(WITH_ORB_OCTREE "Include ORB Octree feature support" ON)
option(WITH_SUPERPOINT_TORCH "Include SuperPoint Torch feature support" ON)
option(WITH_PYMATCHER "Include Python3 matchers support" OFF)
option(WITH_TORCH "Include Torch support (SuperPoint)" OFF)
option(WITH_PYTHON "Include Python3 support (PyMatcher, PyDetector)" OFF)
option(WITH_PYTHON_THREADING "Use more than one Python interpreter." OFF)
option(WITH_PDAL "Include PDAL support" ON)
option(WITH_FREENECT "Include Freenect support" ON)
option(WITH_FREENECT2 "Include Freenect2 support" ON)
option(WITH_K4W2 "Include Kinect for Windows v2 support" ON)
@@ -178,13 +180,16 @@ option(WITH_CERES "Include Ceres support" ON)
option(WITH_VERTIGO "Include Vertigo support" ON)
option(WITH_CVSBA "Include cvsba support" ON)
option(WITH_POINTMATCHER "Include libpointmatcher support" ON)
option(WITH_CCCORELIB "Include CCCoreLib support" ON)
option(WITH_LOAM "Include LOAM support" ON)
option(WITH_FLYCAPTURE2 "Include FlyCapture2/Triclops support" ON)
option(WITH_ZED "Include ZED sdk support" ON)
option(WITH_ZEDOC "Include ZED Open Capture support" ON)
option(WITH_REALSENSE "Include RealSense support" ON)
option(WITH_REALSENSE_SLAM "Include RealSenseSlam support" ON)
option(WITH_REALSENSE2 "Include RealSense support" ON)
option(WITH_MYNTEYE "Include mynteye-s support" ON)
option(WITH_DEPTHAI "Include depthai-core support" ON)
option(WITH_OCTOMAP "Include Octomap support" ON)
option(WITH_CPUTSDF "Include CPUTSDF support" ON)
option(WITH_OPENCHISEL "Include open_chisel support" ON)
@@ -192,7 +197,7 @@ option(WITH_ALICE_VISION "Include AliceVision support" OFF)
option(WITH_FOVIS "Include FOVIS support" ON)
option(WITH_VISO2 "Include VISO2 support" ON)
option(WITH_DVO "Include DVO support" ON)
option(WITH_ORB_SLAM2 "Include ORB_SLAM2 support" ON)
option(WITH_ORB_SLAM "Include ORB_SLAM2 or ORB_SLAM3 support" ON)
option(WITH_OKVIS "Include OKVIS support" ON)
option(WITH_MSCKF_VIO "Include MSCKF_VIO support" OFF)
option(WITH_VINS "Include VINS-Fusion support" ON)
@@ -322,19 +327,26 @@ IF(WITH_QT)
ENDIF(QT4_FOUND OR Qt5_FOUND)
ENDIF(WITH_QT)
IF(WITH_SUPERPOINT_TORCH)
IF(WITH_TORCH)
FIND_PACKAGE(Torch QUIET)
IF(TORCH_FOUND)
MESSAGE(STATUS "Found Torch: ${TORCH_INCLUDE_DIRS}")
ENDIF(TORCH_FOUND)
ENDIF(WITH_SUPERPOINT_TORCH)
ENDIF(WITH_TORCH)
IF(WITH_PYMATCHER)
IF(WITH_PYTHON)
FIND_PACKAGE(Python3 COMPONENTS Interpreter Development)
IF(Python3_FOUND)
MESSAGE(STATUS "Found Python3")
ENDIF(Python3_FOUND)
ENDIF(WITH_PYMATCHER)
ENDIF(WITH_PYTHON)
IF(WITH_PDAL)
FIND_PACKAGE(PDAL QUIET)
IF(PDAL_FOUND)
MESSAGE(STATUS "Found PDAL ${PDAL_VERSION}: ${PDAL_INCLUDE_DIRS}")
ENDIF(PDAL_FOUND)
ENDIF(WITH_PDAL)
IF(WITH_FREENECT)
FIND_PACKAGE(Freenect QUIET)
@@ -402,7 +414,14 @@ IF(WITH_G2O)
FIND_PACKAGE(G2O QUIET)
IF(G2O_FOUND)
MESSAGE(STATUS "Found g2o: ${G2O_INCLUDE_DIRS}")
ENDIF(G2O_FOUND)
ELSE()
FIND_PACKAGE(g2o QUIET)
IF(g2o_FOUND)
SET(G2O_FOUND ${g2o_FOUND})
SET(G2O_CPP11 1)
MESSAGE(STATUS "Found g2o (targets)")
ENDIF(g2o_FOUND)
ENDIF()
ENDIF(WITH_G2O)
IF(WITH_GTSAM)
@@ -427,14 +446,28 @@ ENDIF(WITH_CVSBA)
IF(WITH_POINTMATCHER)
find_package(libpointmatcher QUIET)
IF(libpointmatcher_FOUND)
find_package(Boost COMPONENTS thread filesystem system program_options date_time REQUIRED)
if (Boost_MINOR_VERSION GREATER 47)
find_package(Boost COMPONENTS thread filesystem system program_options date_time chrono REQUIRED)
endif (Boost_MINOR_VERSION GREATER 47)
MESSAGE(STATUS "Found libpointmatcher: ${libpointmatcher_INCLUDE_DIRS}")
ENDIF(libpointmatcher_FOUND)
ENDIF(WITH_POINTMATCHER)
IF(libpointmatcher_FOUND OR GTSAM_FOUND)
find_package(Boost COMPONENTS thread filesystem system program_options date_time REQUIRED)
IF(Boost_MINOR_VERSION GREATER 47)
find_package(Boost COMPONENTS thread filesystem system program_options date_time chrono timer REQUIRED)
ENDIF(Boost_MINOR_VERSION GREATER 47)
IF(WIN32)
MESSAGE(STATUS "Boost_LIBRARY_DIRS=${Boost_LIBRARY_DIRS}")
link_directories(${Boost_LIBRARY_DIRS})
ENDIF(WIN32)
ENDIF(libpointmatcher_FOUND OR GTSAM_FOUND)
IF(WITH_CCCORELIB)
find_package(CCCoreLib QUIET)
IF(CCCoreLib_FOUND)
MESSAGE(STATUS "Found CCCoreLib: ${CCCoreLib_INCLUDE_DIRS}")
ENDIF(CCCoreLib_FOUND)
ENDIF(WITH_CCCORELIB)
IF(WITH_LOAM)
find_package(loam_velodyne QUIET)
IF(loam_velodyne_FOUND)
@@ -458,6 +491,20 @@ IF(WITH_ZED)
ENDIF(ZED_FOUND)
ENDIF(WITH_ZED)
IF(WITH_ZEDOC)
find_package(ZEDOC QUIET)
IF(ZEDOC_FOUND)
MESSAGE(STATUS "Found ZED Open Capture: ${ZEDOC_INCLUDE_DIRS}")
## look for HIDAPI
find_package(HIDAPI)
IF(HIDAPI_FOUND)
MESSAGE(STATUS "Found HIDAPI: ${HIDAPI_INCLUDE_DIRS}")
ELSE()
MESSAGE(FATAL_ERROR "HIDAPI is required to build with Zed Open Capture! Set -DWITH_ZEDOC=OFF if you don't have HIDAPI.")
ENDIF()
ENDIF(ZEDOC_FOUND)
ENDIF(WITH_ZEDOC)
IF(WITH_REALSENSE)
IF(WITH_REALSENSE_SLAM)
FIND_PACKAGE(RealSense QUIET COMPONENTS slam)
@@ -490,6 +537,13 @@ IF(WITH_MYNTEYE)
ENDIF(mynteye_FOUND)
ENDIF(WITH_MYNTEYE)
IF(WITH_DEPTHAI)
FIND_PACKAGE(depthai 2 QUIET)
IF(depthai_FOUND)
MESSAGE(STATUS "Found depthai-core (targets)")
ENDIF(depthai_FOUND)
ENDIF(WITH_DEPTHAI)
IF(WITH_OCTOMAP)
FIND_PACKAGE(octomap QUIET)
IF(octomap_FOUND)
@@ -519,9 +573,9 @@ IF(WITH_ALICE_VISION)
IF(AliceVision_FOUND)
SET(CMAKE_MODULE_PATH "${CMAKE_MODULE_PATH};/usr/local/lib/cmake/modules")
find_package(Geogram REQUIRED QUIET)
# Make sure the two following lines are also commented in AliceVision to avoid Eigen memory alignment error
#add_definitions("-DEIGEN_DONT_ALIGN_STATICALLY=1")
#add_definitions("-DEIGEN_DONT_VECTORIZE=1")
add_definitions("-DRTABMAP_ALICE_VISION_MAJOR=${AliceVision_VERSION_MAJOR}")
add_definitions("-DRTABMAP_ALICE_VISION_MINOR=${AliceVision_VERSION_MINOR}")
add_definitions("-DRTABMAP_ALICE_VISION_PATCH=${AliceVision_VERSION_PATCH}")
ENDIF(AliceVision_FOUND)
ENDIF(WITH_ALICE_VISION)
@@ -588,58 +642,53 @@ IF(WITH_FASTCV)
ENDIF(FastCV_FOUND)
ENDIF(WITH_FASTCV)
IF(WITH_ORB_SLAM2 AND NOT G2O_FOUND)
FIND_PACKAGE(ORB_SLAM2 QUIET)
IF(ORB_SLAM2_FOUND)
MESSAGE(STATUS "Found ORB_SLAM2: ${ORB_SLAM2_INCLUDE_DIRS}")
FIND_PACKAGE(Pangolin QUIET)
IF(NOT Pangolin_FOUND)
SET(ORB_SLAM2_FOUND FALSE)
MESSAGE(STATUS "Found ORB_SLAM2 but not Pangolin, disabling ORB_SLAM2.")
ELSE()
MESSAGE(STATUS "Found Pangolin: ${Pangolin_INCLUDE_DIRS}")
SET(ORB_SLAM2_INCLUDE_DIRS ${ORB_SLAM2_INCLUDE_DIRS} ${Pangolin_INCLUDE_DIRS})
SET(ORB_SLAM2_LIBRARIES ${ORB_SLAM2_LIBRARIES} ${Pangolin_LIBRARIES})
ENDIF()
ENDIF(ORB_SLAM2_FOUND)
ENDIF(WITH_ORB_SLAM2 AND NOT G2O_FOUND)
IF(WITH_ORB_SLAM AND NOT G2O_FOUND)
FIND_PACKAGE(ORB_SLAM QUIET)
IF(ORB_SLAM_FOUND)
MESSAGE(STATUS "Found ORB_SLAM${ORB_SLAM_VERSION}: ${ORB_SLAM_INCLUDE_DIRS}")
ENDIF(ORB_SLAM_FOUND)
ENDIF(WITH_ORB_SLAM AND NOT G2O_FOUND)
IF(loam_velodyne_FOUND OR PCL_VERSION VERSION_GREATER "1.9.1" OR TORCH_FOUND)
#LOAM and PCL>=1.10 require c++14
IF(NOT MSVC)
include(CheckCXXCompilerFlag)
CHECK_CXX_COMPILER_FLAG("-std=c++14" COMPILER_SUPPORTS_CXX14)
IF(COMPILER_SUPPORTS_CXX14)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++14")
ELSE()
message(STATUS "The compiler ${CMAKE_CXX_COMPILER} has no C++14 support. Please use a different C++ compiler if you want to use LOAM (set \"-DWITH_LOAM=OFF\" to build without LOAM).")
ENDIF()
ENDIF()
ELSEIF(G2O_FOUND OR
GTSAM_FOUND OR
CERES_FOUND OR
ZED_FOUND OR
ANDROID OR
RealSense_FOUND OR
realsense2_FOUND OR
ORB_SLAM2_FOUND OR
okvis_FOUND OR
open_chisel_FOUND OR
msckf_vio_FOUND OR
vins_FOUND)
#Newest versions require std11
IF(NOT MSVC)
include(CheckCXXCompilerFlag)
CHECK_CXX_COMPILER_FLAG("-std=c++11" COMPILER_SUPPORTS_CXX11)
CHECK_CXX_COMPILER_FLAG("-std=c++0x" COMPILER_SUPPORTS_CXX0X)
IF(COMPILER_SUPPORTS_CXX11)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")
ELSEIF(COMPILER_SUPPORTS_CXX0X)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++0x")
ELSE()
message(STATUS "The compiler ${CMAKE_CXX_COMPILER} has no C++11 support. Please use a different C++ compiler.")
ENDIF()
ENDIF()
IF(NOT MSVC)
IF(loam_velodyne_FOUND OR PCL_VERSION VERSION_GREATER "1.9.1" OR TORCH_FOUND OR G2O_FOUND OR CCCoreLib_FOUND)
#LOAM, PCL>=1.10, latest g2o and CCCoreLib require c++14
include(CheckCXXCompilerFlag)
CHECK_CXX_COMPILER_FLAG("-std=c++14" COMPILER_SUPPORTS_CXX14)
IF(COMPILER_SUPPORTS_CXX14)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++14")
set(CMAKE_CXX_STANDARD 14)
ELSE()
message(STATUS "The compiler ${CMAKE_CXX_COMPILER} has no C++14 support. Please use a different C++ compiler if you want to use LOAM, latest PCL or g2o.")
ENDIF()
ENDIF(loam_velodyne_FOUND OR PCL_VERSION VERSION_GREATER "1.9.1" OR TORCH_FOUND OR G2O_FOUND OR CCCoreLib_FOUND)
IF( (NOT (${CMAKE_CXX_STANDARD} STREQUAL "14")) AND (
G2O_FOUND OR
GTSAM_FOUND OR
CERES_FOUND OR
ZED_FOUND OR
ZEDOC_FOUND OR
ANDROID OR
RealSense_FOUND OR
realsense2_FOUND OR
ORB_SLAM_FOUND OR
okvis_FOUND OR
open_chisel_FOUND OR
msckf_vio_FOUND OR
vins_FOUND OR
libpointmatcher_FOUND))
#Newest versions require std11
include(CheckCXXCompilerFlag)
CHECK_CXX_COMPILER_FLAG("-std=c++11" COMPILER_SUPPORTS_CXX11)
CHECK_CXX_COMPILER_FLAG("-std=c++0x" COMPILER_SUPPORTS_CXX0X)
IF(COMPILER_SUPPORTS_CXX11)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")
ELSEIF(COMPILER_SUPPORTS_CXX0X)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++0x")
ELSE()
message(STATUS "The compiler ${CMAKE_CXX_COMPILER} has no C++11 support. Please use a different C++ compiler.")
ENDIF()
ENDIF()
ENDIF()
####### OSX BUNDLE CMAKE_INSTALL_PREFIX #######
@@ -723,9 +772,15 @@ ENDIF()
IF(NOT libpointmatcher_FOUND)
SET(POINTMATCHER "//")
ENDIF(NOT libpointmatcher_FOUND)
IF(NOT CCCoreLib_FOUND)
SET(CCCORELIB "//")
ENDIF(NOT CCCoreLib_FOUND)
IF(NOT FastCV_FOUND)
SET(FASTCV "//")
ENDIF(NOT FastCV_FOUND)
IF(NOT PDAL_FOUND)
SET(PDAL "//")
ENDIF(NOT PDAL_FOUND)
IF(NOT loam_velodyne_FOUND)
SET(LOAM "//")
ENDIF(NOT loam_velodyne_FOUND)
@@ -769,6 +824,11 @@ IF(NOT ZED_FOUND)
ELSE()
SET(CONF_DEPENDENCIES ${CONF_DEPENDENCIES} ${ZED_LIBRARIES} ${CUDA_LIBRARIES})
ENDIF()
IF(NOT ZEDOC_FOUND)
SET(ZEDOC "//")
ELSE()
SET(CONF_DEPENDENCIES ${CONF_DEPENDENCIES} ${ZEDOC_LIBRARIES})
ENDIF()
IF(NOT RealSense_FOUND)
SET(REALSENSE "//")
ELSE()
@@ -785,6 +845,9 @@ ENDIF()
IF(NOT mynteye_FOUND)
SET(MYNTEYE "//")
ENDIF(NOT mynteye_FOUND)
IF(NOT depthai_FOUND)
SET(DEPTHAI "//")
ENDIF(NOT depthai_FOUND)
IF(NOT octomap_FOUND)
SET(OCTOMAP "//")
ELSE()
@@ -833,19 +896,19 @@ IF(NOT vins_FOUND)
ELSE()
SET(CONF_DEPENDENCIES ${CONF_DEPENDENCIES} ${vins_LIBRARIES})
ENDIF()
IF(NOT ORB_SLAM2_FOUND)
SET(ORB_SLAM2 "//")
IF(NOT ORB_SLAM_FOUND)
SET(ORB_SLAM "//")
ELSE()
SET(CONF_DEPENDENCIES ${CONF_DEPENDENCIES} ${ORB_SLAM2_LIBRARIES})
SET(CONF_DEPENDENCIES ${CONF_DEPENDENCIES} ${ORB_SLAM_LIBRARIES})
ENDIF()
IF(NOT WITH_ORB_OCTREE)
SET(ORB_OCTREE "//")
ENDIF()
IF(NOT TORCH_FOUND)
SET(SUPERPOINT_TORCH "//")
SET(TORCH "//")
ENDIF()
IF(NOT Python3_FOUND)
SET(PYMATCHER "//")
SET(PYTHON "//")
ENDIF()
IF(ADD_VTK_GUI_SUPPORT_QT_TO_CONF)
SET(CONF_VTK_QT true)
@@ -1063,12 +1126,20 @@ IF(OpenCV_FOUND)
ELSE()
IF(OPENCV_XFEATURES2D_FOUND)
IF(NONFREE STREQUAL "//")
MESSAGE(STATUS " *With OpenCV ${OpenCV_VERSION} xfeatures2d = YES, nonfree = NO (License: BSD)")
IF((OpenCV_VERSION_MAJOR LESS 4) OR ((OpenCV_VERSION_MAJOR EQUAL 4) AND (OpenCV_VERSION_MINOR LESS 5)))
MESSAGE(STATUS " *With OpenCV ${OpenCV_VERSION} xfeatures2d = YES, nonfree = NO (License: BSD)")
ELSE()
MESSAGE(STATUS " *With OpenCV ${OpenCV_VERSION} xfeatures2d = YES, nonfree = NO (License: Apache 2)")
ENDIF()
ELSE()
MESSAGE(STATUS " *With OpenCV ${OpenCV_VERSION} xfeatures2d = YES, nonfree = YES (License: Non commercial)")
ENDIF()
ELSE()
MESSAGE(STATUS " *With OpenCV ${OpenCV_VERSION} xfeatures2d = NO, nonfree = NO (License: BSD)")
IF((OpenCV_VERSION_MAJOR LESS 4) OR ((OpenCV_VERSION_MAJOR EQUAL 4) AND (OpenCV_VERSION_MINOR LESS 5)))
MESSAGE(STATUS " *With OpenCV ${OpenCV_VERSION} xfeatures2d = NO, nonfree = NO (License: BSD)")
ELSE()
MESSAGE(STATUS " *With OpenCV ${OpenCV_VERSION} xfeatures2d = NO, nonfree = NO (License: Apache 2)")
ENDIF()
ENDIF()
ENDIF()
ENDIF(OpenCV_FOUND)
@@ -1100,18 +1171,18 @@ ENDIF()
IF(TORCH_FOUND)
MESSAGE(STATUS " With SupertPoint = YES (License: GPLv3) libtorch=${Torch_VERSION}")
ELSEIF(NOT WITH_SUPERPOINT_TORCH)
MESSAGE(STATUS " With SupertPoint = NO (WITH_SUPERPOINT_TORCH=OFF)")
ELSEIF(NOT WITH_TORCH)
MESSAGE(STATUS " With SupertPoint = NO (WITH_TORCH=OFF)")
ELSE()
MESSAGE(STATUS " With SupertPoint = NO (libtorch not found)")
ENDIF()
IF(Python3_FOUND)
MESSAGE(STATUS " With Python3 = YES (License: PSF)")
ELSEIF(NOT WITH_PYMATCHER)
MESSAGE(STATUS " With Python3 = NO (WITH_PYMATCHER=OFF)")
MESSAGE(STATUS " With Python${Python3_VERSION_MAJOR}.${Python3_VERSION_MINOR} = YES (License: PSF)")
ELSEIF(NOT WITH_PYTHON)
MESSAGE(STATUS " With Python3 = NO (WITH_PYTHON=OFF)")
ELSE()
MESSAGE(STATUS " With Python3 = NO (python3 not found)")
MESSAGE(STATUS " With Python3 = NO (python not found)")
ENDIF()
IF(WITH_MADGWICK)
@@ -1128,6 +1199,14 @@ ELSE()
MESSAGE(STATUS " With FastCV = NO (FastCV not found)")
ENDIF()
IF(PDAL_FOUND)
MESSAGE(STATUS " With PDAL = YES (License: BSD)")
ELSEIF(NOT WITH_PDAL)
MESSAGE(STATUS " With PDAL = NO (WITH_PDAL=OFF)")
ELSE()
MESSAGE(STATUS " With PDAL = NO (PDAL not found)")
ENDIF()
MESSAGE(STATUS "")
MESSAGE(STATUS " Solvers:")
IF(WITH_TORO)
@@ -1186,6 +1265,14 @@ ELSE()
MESSAGE(STATUS " *With libpointmatcher = NO (libpointmatcher not found)")
ENDIF()
IF(CCCoreLib_FOUND)
MESSAGE(STATUS " *With CCCoreLib = YES (License: GPLv2)")
ELSEIF(NOT WITH_POINTMATCHER)
MESSAGE(STATUS " *With CCCoreLib = NO (WITH_CCCORELIB=OFF)")
ELSE()
MESSAGE(STATUS " *With CCCoreLib = NO (CCCoreLib not found)")
ENDIF()
MESSAGE(STATUS "")
MESSAGE(STATUS " Reconstruction Approaches:")
IF(octomap_FOUND)
@@ -1213,7 +1300,7 @@ MESSAGE(STATUS " With OpenChisel = NO (open_chisel not found)")
ENDIF()
IF(AliceVision_FOUND)
MESSAGE(STATUS " With AliceVision = YES (License: MPLv2)")
MESSAGE(STATUS " With AliceVision ${AliceVision_VERSION} = YES (License: MPLv2)")
ELSEIF(NOT WITH_ALICE_VISION)
MESSAGE(STATUS " With AliceVision = NO (WITH_ALICE_VISION=OFF)")
ELSE()
@@ -1286,6 +1373,14 @@ ELSE()
MESSAGE(STATUS " With ZED = NO (ZED sdk and/or cuda not found)")
ENDIF()
IF(ZEDOC_FOUND)
MESSAGE(STATUS " With ZEDOC = YES")
ELSEIF(NOT WITH_ZEDOC)
MESSAGE(STATUS " With ZEDOC = NO (WITH_ZEDOC=OFF)")
ELSE()
MESSAGE(STATUS " With ZEDOC = NO (ZED Open Capture not found)")
ENDIF()
IF(RealSense_FOUND)
MESSAGE(STATUS " With RealSense = YES (License: Apache-2)")
IF(RealSenseSlam_FOUND)
@@ -1317,6 +1412,14 @@ ELSE()
MESSAGE(STATUS " With MyntEyeS = NO (mynteye s sdk not found)")
ENDIF()
IF(depthai_FOUND)
MESSAGE(STATUS " With DepthAI = YES (License: MIT)")
ELSEIF(NOT WITH_DEPTHAI)
MESSAGE(STATUS " With DepthAI = NO (WITH_DEPTHAI=OFF)")
ELSE()
MESSAGE(STATUS " With DepthAI = NO (depthai-core not found)")
ENDIF()
MESSAGE(STATUS "")
MESSAGE(STATUS " Odometry Approaches:")
IF(loam_velodyne_FOUND)
@@ -1375,14 +1478,14 @@ ELSE()
MESSAGE(STATUS " With VINS-Fusion = NO (VINS-Fusion not found)")
ENDIF()
IF(ORB_SLAM2_FOUND)
MESSAGE(STATUS " With ORB_SLAM2 = YES (License: GPLv3)")
ELSEIF(NOT WITH_ORB_SLAM2)
MESSAGE(STATUS " With ORB_SLAM2 = NO (WITH_ORB_SLAM2=OFF)")
IF(ORB_SLAM_FOUND)
MESSAGE(STATUS " With ORB_SLAM${ORB_SLAM_VERSION} = YES (License: GPLv3)")
ELSEIF(NOT WITH_ORB_SLAM)
MESSAGE(STATUS " With ORB_SLAM = NO (WITH_ORB_SLAM=OFF)")
ELSEIF(G2O_FOUND)
MESSAGE(STATUS " With ORB_SLAM2 = NO (WITH_G2O should be OFF as ORB_SLAM2 uses its own g2o version)")
MESSAGE(STATUS " With ORB_SLAM = NO (WITH_G2O should be OFF as ORB_SLAM uses its own g2o version)")
ELSE()
MESSAGE(STATUS " With ORB_SLAM2 = NO (ORB_SLAM2 not found, make sure environment variable ORB_SLAM2_ROOT_DIR is set)")
MESSAGE(STATUS " With ORB_SLAM = NO (ORB_SLAM2 and ORB_SLAM3 not found, make sure environment variable ORB_SLAM_ROOT_DIR is set)")
ENDIF()
MESSAGE(STATUS "Show all options with: cmake -LA | grep WITH_")
+1 -1
View File
@@ -7,7 +7,7 @@ rtabmap ![Analytics](https://ga-beacon-279122.nn.r.appspot.com/UA-56986679-3/git
[![License][license-image]][license]
Linux: [![Build Status](https://travis-ci.org/introlab/rtabmap.svg?branch=master)](https://travis-ci.org/introlab/rtabmap) Windows: [![Build status](https://ci.appveyor.com/api/projects/status/hr73xspix9oqa26h/branch/master?svg=true)](https://ci.appveyor.com/project/matlabbe/rtabmap/branch/master)
[release-image]: https://img.shields.io/badge/release-0.20.2-green.svg?style=flat
[release-image]: https://img.shields.io/badge/release-0.20.7-green.svg?style=flat
[releases]: https://github.com/introlab/rtabmap/releases
[license-image]: https://img.shields.io/badge/license-BSD-green.svg?style=flat
+18 -3
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@@ -51,15 +51,19 @@ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
@K4A@#define RTABMAP_K4A
@CVSBA@#define RTABMAP_CVSBA
@POINTMATCHER@#define RTABMAP_POINTMATCHER
@CCCORELIB@#define RTABMAP_CCCORELIB
@FASTCV@#define RTABMAP_FASTCV
@PDAL@#define RTABMAP_PDAL
@LOAM@#define RTABMAP_LOAM
@DC1394@#define RTABMAP_DC1394
@FLYCAPTURE2@#define RTABMAP_FLYCAPTURE2
@ZED@#define RTABMAP_ZED
@ZEDOC@#define RTABMAP_ZEDOC
@REALSENSE@#define RTABMAP_REALSENSE
@REALSENSESLAM@#define RTABMAP_REALSENSE_SLAM
@REALSENSE2@#define RTABMAP_REALSENSE2
@MYNTEYE@#define RTABMAP_MYNTEYE
@DEPTHAI@#define RTABMAP_DEPTHAI
@OCTOMAP@#define RTABMAP_OCTOMAP
@CPUTSDF@#define RTABMAP_CPUTSDF
@ALICE_VISION@#define RTABMAP_ALICE_VISION
@@ -70,12 +74,23 @@ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
@OKVIS@#define RTABMAP_OKVIS
@MSCKF_VIO@#define RTABMAP_MSCKF_VIO
@VINS@#define RTABMAP_VINS
@ORB_SLAM2@#define RTABMAP_ORB_SLAM2
@ORB_SLAM@#define RTABMAP_ORB_SLAM @ORB_SLAM_VERSION@
@ORB_OCTREE@#define RTABMAP_ORB_OCTREE
@SUPERPOINT_TORCH@#define RTABMAP_SUPERPOINT_TORCH
@PYMATCHER@#define RTABMAP_PYMATCHER
@TORCH@#define RTABMAP_TORCH
@PYTHON@#define RTABMAP_PYTHON
@MADGWICK@#define RTABMAP_MADGWICK
#include <pcl/pcl_config.h>
#if PCL_VERSION_COMPARE(>, 1, 11, 1)
#include <pcl/types.h>
#define RTABMAP_PCL_INDEX pcl::index_t
#elif PCL_VERSION_COMPARE(>=, 1, 10, 0)
#define RTABMAP_PCL_INDEX std::uint32_t
#else
#include <pcl/pcl_macros.h>
#define RTABMAP_PCL_INDEX pcl::uint32_t
#endif
#endif /* VERSION_H_ */
+9 -9
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@@ -308,7 +308,7 @@ int RTABMapApp::openDatabase(const std::string & databasePath, bool databaseInMe
optRefPose_ = 0;
}
cv::Mat cloudMat;
std::vector<std::vector<std::vector<unsigned int> > > polygons;
std::vector<std::vector<std::vector<RTABMAP_PCL_INDEX> > > polygons;
#if PCL_VERSION_COMPARE(>=, 1, 8, 0)
std::vector<std::vector<Eigen::Vector2f, Eigen::aligned_allocator<Eigen::Vector2f> > > texCoords;
#else
@@ -2901,8 +2901,8 @@ bool RTABMapApp::exportMesh(
// save in database
pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZRGBNormal>);
pcl::fromPCLPointCloud2(polygonMesh->cloud, *cloud);
cv::Mat cloudMat = rtabmap::compressData2(rtabmap::util3d::laserScanFromPointCloud(*cloud, rtabmap::Transform(), false)); // for database
std::vector<std::vector<std::vector<unsigned int> > > polygons(1);
cv::Mat cloudMat = rtabmap::compressData2(rtabmap::util3d::laserScanFromPointCloud(*cloud, rtabmap::Transform(), false).data()); // for database
std::vector<std::vector<std::vector<RTABMAP_PCL_INDEX> > > polygons(1);
polygons[0].resize(polygonMesh->polygons.size());
for(unsigned int p=0; p<polygonMesh->polygons.size(); ++p)
{
@@ -2918,10 +2918,10 @@ bool RTABMapApp::exportMesh(
{
pcl::PointCloud<pcl::PointNormal>::Ptr cloud(new pcl::PointCloud<pcl::PointNormal>);
pcl::fromPCLPointCloud2(textureMesh->cloud, *cloud);
cv::Mat cloudMat = rtabmap::compressData2(rtabmap::util3d::laserScanFromPointCloud(*cloud, rtabmap::Transform(), false)); // for database
cv::Mat cloudMat = rtabmap::compressData2(rtabmap::util3d::laserScanFromPointCloud(*cloud, rtabmap::Transform(), false).data()); // for database
// save in database
std::vector<std::vector<std::vector<unsigned int> > > polygons(textureMesh->tex_polygons.size());
std::vector<std::vector<std::vector<RTABMAP_PCL_INDEX> > > polygons(textureMesh->tex_polygons.size());
for(unsigned int t=0; t<textureMesh->tex_polygons.size(); ++t)
{
polygons[t].resize(textureMesh->tex_polygons[t].size());
@@ -3054,7 +3054,7 @@ bool RTABMapApp::exportMesh(
// save in database
{
cv::Mat cloudMat = rtabmap::compressData2(rtabmap::util3d::laserScanFromPointCloud(*mergedClouds)); // for database
cv::Mat cloudMat = rtabmap::compressData2(rtabmap::util3d::laserScanFromPointCloud(*mergedClouds).data()); // for database
boost::mutex::scoped_lock lock(rtabmapMutex_);
rtabmap_->getMemory()->saveOptimizedMesh(cloudMat);
success = true;
@@ -3114,7 +3114,7 @@ bool RTABMapApp::postExportation(bool visualize)
{
visualizingMesh_ = false;
cv::Mat cloudMat;
std::vector<std::vector<std::vector<unsigned int> > > polygons;
std::vector<std::vector<std::vector<RTABMAP_PCL_INDEX> > > polygons;
#if PCL_VERSION_COMPARE(>=, 1, 8, 0)
std::vector<std::vector<Eigen::Vector2f, Eigen::aligned_allocator<Eigen::Vector2f> > > texCoords;
#else
@@ -3171,7 +3171,7 @@ bool RTABMapApp::writeExportedMesh(const std::string & directory, const std::str
pcl::PolygonMesh::Ptr polygonMesh(new pcl::PolygonMesh);
pcl::TextureMesh::Ptr textureMesh(new pcl::TextureMesh);
cv::Mat cloudMat;
std::vector<std::vector<std::vector<unsigned int> > > polygons;
std::vector<std::vector<std::vector<RTABMAP_PCL_INDEX> > > polygons;
#if PCL_VERSION_COMPARE(>=, 1, 8, 0)
std::vector<std::vector<Eigen::Vector2f, Eigen::aligned_allocator<Eigen::Vector2f> > > texCoords;
#else
@@ -3186,7 +3186,7 @@ bool RTABMapApp::writeExportedMesh(const std::string & directory, const std::str
LOGI("writeExportedMesh: Found optimized mesh!");
if(textures.empty())
{
polygonMesh = rtabmap::util3d::assemblePolygonMesh(cloudMat, polygons.size() == 1?polygons[0]:std::vector<std::vector<unsigned int> >());
polygonMesh = rtabmap::util3d::assemblePolygonMesh(cloudMat, polygons.size() == 1?polygons[0]:std::vector<std::vector<RTABMAP_PCL_INDEX> >());
}
else
{
+13 -11
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@@ -57,7 +57,7 @@ enum PointCloudShaders
// PointCloud shaders
const std::string kPointCloudVertexShader =
"precision mediump float;\n"
"precision highp float;\n"
"precision mediump int;\n"
"attribute vec3 aVertex;\n"
"attribute vec3 aColor;\n"
@@ -75,7 +75,7 @@ const std::string kPointCloudVertexShader =
" vColor = aColor;\n"
"}\n";
const std::string kPointCloudLightingVertexShader =
"precision mediump float;\n"
"precision highp float;\n"
"precision mediump int;\n"
"attribute vec3 aVertex;\n"
"attribute vec3 aNormal;\n"
@@ -100,7 +100,7 @@ const std::string kPointCloudLightingVertexShader =
"}\n";
const std::string kPointCloudFragmentShader =
"precision mediump float;\n"
"precision highp float;\n"
"precision mediump int;\n"
"uniform float uGainR;\n"
"uniform float uGainG;\n"
@@ -127,7 +127,8 @@ const std::string kPointCloudBlendingFragmentShader =
" vec4 textureColor = vec4(vColor.z, vColor.y, vColor.x, 1.0);\n"
" float alpha = 1.0;\n"
" vec2 coord = uScreenScale * gl_FragCoord.xy;\n;"
" float depth = texture2D(uDepthTexture, coord).r;\n"
" vec4 depthPacked = texture2D(uDepthTexture, coord);\n"
" float depth = dot(depthPacked, 1./vec4(1.,255.,65025.,16581375.));\n"
" float num = (2.0 * uNearZ * uFarZ);\n"
" float diff = (uFarZ - uNearZ);\n"
" float add = (uFarZ + uNearZ);\n"
@@ -141,7 +142,7 @@ const std::string kPointCloudBlendingFragmentShader =
"}\n";
const std::string kPointCloudDepthPackingVertexShader =
"precision mediump float;\n"
"precision highp float;\n"
"precision mediump int;\n"
"attribute vec3 aVertex;\n"
"uniform mat4 uMVP;\n"
@@ -154,15 +155,15 @@ const std::string kPointCloudDepthPackingFragmentShader =
"precision highp float;\n"
"precision mediump int;\n"
"void main() {\n"
" float toFixed = 255.0/256.0;\n"
" vec4 enc = vec4(1.0, 255.0, 65025.0, 160581375.0) * toFixed * gl_FragCoord.z;\n"
" vec4 enc = vec4(1.,255.,65025.,16581375.) * gl_FragCoord.z;\n"
" enc = fract(enc);\n"
" enc -= enc.yzww * vec2(1./255., 0.).xxxy;\n"
" gl_FragColor = enc;\n"
"}\n";
// Texture shaders
const std::string kTextureMeshVertexShader =
"precision mediump float;\n"
"precision highp float;\n"
"precision mediump int;\n"
"attribute vec3 aVertex;\n"
"attribute vec2 aTexCoord;\n"
@@ -185,7 +186,7 @@ const std::string kTextureMeshVertexShader =
" vLightWeighting = 1.0;\n"
"}\n";
const std::string kTextureMeshLightingVertexShader =
"precision mediump float;\n"
"precision highp float;\n"
"precision mediump int;\n"
"attribute vec3 aVertex;\n"
"attribute vec3 aNormal;\n"
@@ -214,7 +215,7 @@ const std::string kTextureMeshLightingVertexShader =
" vLightWeighting=0.5;\n"
"}\n";
const std::string kTextureMeshFragmentShader =
"precision mediump float;\n"
"precision highp float;\n"
"precision mediump int;\n"
"uniform sampler2D uTexture;\n"
"uniform float uGainR;\n"
@@ -245,7 +246,8 @@ const std::string kTextureMeshBlendingFragmentShader =
" vec4 textureColor = texture2D(uTexture, vTexCoord);\n"
" float alpha = 1.0;\n"
" vec2 coord = uScreenScale * gl_FragCoord.xy;\n;"
" float depth = texture2D(uDepthTexture, coord).r;\n"
" vec4 depthPacked = texture2D(uDepthTexture, coord);\n"
" float depth = dot(depthPacked, 1./vec4(1.,255.,65025.,16581375.));\n"
" float num = (2.0 * uNearZ * uFarZ);\n"
" float diff = (uFarZ - uNearZ);\n"
" float add = (uFarZ + uNearZ);\n"
+23 -15
View File
@@ -97,6 +97,7 @@ Scene::Scene() :
g_(0.0f),
b_(0.0f),
fboId_(0),
rboId_(0),
depthTexture_(0),
screenWidth_(0),
screenHeight_(0),
@@ -176,6 +177,8 @@ void Scene::DeleteResources() {
{
glDeleteFramebuffers(1, &fboId_);
fboId_ = 0;
glDeleteRenderbuffers(1, &rboId_);
rboId_ = 0;
glDeleteTextures(1, &depthTexture_);
depthTexture_ = 0;
}
@@ -220,16 +223,23 @@ void Scene::SetupViewPort(int w, int h) {
UASSERT(gesture_camera_ != 0);
gesture_camera_->SetWindowSize(static_cast<float>(w), static_cast<float>(h));
glViewport(0, 0, w, h);
if(screenWidth_ != w || fboId_ == 0)
if(screenWidth_ != w || screenHeight_ != h || fboId_ == 0)
{
if(fboId_>0)
{
glDeleteFramebuffers(1, &fboId_);
fboId_ = 0;
glDeleteRenderbuffers(1, &rboId_);
rboId_ = 0;
glDeleteTextures(1, &depthTexture_);
depthTexture_ = 0;
}
// regenerate fbo texture
// create a framebuffer object, you need to delete them when program exits.
glGenFramebuffers(1, &fboId_);
glBindFramebuffer(GL_FRAMEBUFFER, fboId_);
// Create depth texture
glGenTextures(1, &depthTexture_);
glBindTexture(GL_TEXTURE_2D, depthTexture_);
@@ -237,16 +247,17 @@ void Scene::SetupViewPort(int w, int h) {
glTexParameterf(GL_TEXTURE_2D, GL_TEXTURE_WRAP_T, GL_CLAMP_TO_EDGE);
glTexParameterf(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_NEAREST);
glTexParameterf(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_NEAREST);
glTexImage2D(GL_TEXTURE_2D, 0, GL_DEPTH_COMPONENT, w, h, 0, GL_DEPTH_COMPONENT, GL_UNSIGNED_INT, NULL);
glTexImage2D(GL_TEXTURE_2D, 0, GL_RGBA, w, h, 0, GL_RGBA, GL_UNSIGNED_BYTE, NULL);
glBindTexture(GL_TEXTURE_2D, 0);
// regenerate fbo texture
// create a framebuffer object, you need to delete them when program exits.
glGenFramebuffers(1, &fboId_);
glBindFramebuffer(GL_FRAMEBUFFER, fboId_);
glGenRenderbuffers(1, &rboId_);
glBindRenderbuffer(GL_RENDERBUFFER, rboId_);
glRenderbufferStorage(GL_RENDERBUFFER, GL_DEPTH_COMPONENT16, w, h);
glBindRenderbuffer(GL_RENDERBUFFER, 0);
// Set the texture to be at the depth attachment point of the FBO
glFramebufferTexture2D(GL_FRAMEBUFFER, GL_DEPTH_ATTACHMENT, GL_TEXTURE_2D, depthTexture_, 0);
// Set the texture to be at the color attachment point of the FBO (we pack depth 32 bits in color)
glFramebufferTexture2D(GL_FRAMEBUFFER, GL_COLOR_ATTACHMENT0, GL_TEXTURE_2D, depthTexture_, 0);
glFramebufferRenderbuffer(GL_FRAMEBUFFER, GL_DEPTH_ATTACHMENT, GL_RENDERBUFFER, rboId_);
GLuint status = glCheckFramebufferStatus(GL_FRAMEBUFFER);
if ( status != GL_FRAMEBUFFER_COMPLETE)
@@ -464,14 +475,13 @@ int Scene::Render(const float * uvsTransformed, glm::mat4 arViewMatrix, glm::mat
// set the rendering destination to FBO
glBindFramebuffer(GL_FRAMEBUFFER, fboId_);
glColorMask(GL_FALSE, GL_FALSE, GL_FALSE, GL_FALSE);
glClearColor(1, 1, 1, 1);
glClearColor(0, 0, 0, 0);
glClear(GL_DEPTH_BUFFER_BIT | GL_COLOR_BUFFER_BIT);
if(renderBackgroundCamera)
{
PointCloudDrawable drawable(occlusionMesh);
drawable.Render(projectionMatrix, viewMatrix, true, pointSize_, false, false, 999.0f);
drawable.Render(projectionMatrix, viewMatrix, true, pointSize_, false, false, 999.0f, 0, 0, 0, 0, 0, true);
}
else
{
@@ -479,13 +489,12 @@ int Scene::Render(const float * uvsTransformed, glm::mat4 arViewMatrix, glm::mat
for(std::vector<PointCloudDrawable*>::const_iterator iter=cloudsToDraw.begin(); iter!=cloudsToDraw.end(); ++iter)
{
// set large distance to cam to use low res polygons for fast processing
(*iter)->Render(projectionMatrix, viewMatrix, meshRendering_, pointSize_, false, false, 999.0f);
(*iter)->Render(projectionMatrix, viewMatrix, meshRendering_, pointSize_, false, false, 999.0f, 0, 0, 0, 0, 0, true);
}
}
// back to normal window-system-provided framebuffer
glBindFramebuffer(GL_FRAMEBUFFER, 0); // unbind
glColorMask(GL_TRUE, GL_TRUE, GL_TRUE, GL_TRUE);
}
if(doubleTapOn_ && gesture_camera_->GetCameraType() != tango_gl::GestureCamera::kFirstPerson)
@@ -501,8 +510,7 @@ int Scene::Render(const float * uvsTransformed, glm::mat4 arViewMatrix, glm::mat
GLubyte zValue[4];
glReadPixels(doubleTapPos_.x*screenWidth_, screenHeight_-doubleTapPos_.y*screenHeight_, 1, 1, GL_RGBA, GL_UNSIGNED_BYTE, zValue);
float fromFixed = 256.0f/255.0f;
float zValueF = float(zValue[0]/255.0f)*fromFixed + float(zValue[1]/255.0f)*fromFixed/255.0f + float(zValue[2]/255.0f)*fromFixed/65025.0f + float(zValue[3]/255.0f)*fromFixed/160581375.0f;
float zValueF = float(zValue[0]/255.0f) + float(zValue[1]/255.0f)/255.0f + float(zValue[2]/255.0f)/65025.0f + float(zValue[3]/255.0f)/160581375.0f;
if(zValueF != 0.0f)
{
+1
View File
@@ -204,6 +204,7 @@ class Scene {
float g_;
float b_;
GLuint fboId_;
GLuint rboId_;
GLuint depthTexture_;
GLsizei screenWidth_;
GLsizei screenHeight_;
-13
View File
@@ -1,19 +1,6 @@
### Qt Gui stuff ###
SET(headers_ui
./ObjDeletionHandler.h
)
#This will generate moc_* for Qt
IF(QT4_FOUND)
QT4_WRAP_CPP(moc_srcs ${headers_ui})
ELSE()
QT5_WRAP_CPP(moc_srcs ${headers_ui})
ENDIF()
SET(SRC_FILES
main.cpp
${moc_srcs}
)
SET(INCLUDE_DIRS
+8 -1
View File
@@ -35,7 +35,10 @@ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#include "rtabmap/utilite/UObjDeletionThread.h"
#include "rtabmap/utilite/UFile.h"
#include "rtabmap/utilite/UConversion.h"
#include "ObjDeletionHandler.h"
#ifdef RTABMAP_PYTHON
#include "rtabmap/core/PythonInterface.h"
#endif
using namespace rtabmap;
@@ -45,6 +48,10 @@ int main(int argc, char* argv[])
ULogger::setType(ULogger::kTypeConsole);
ULogger::setLevel(ULogger::kWarning);
#ifdef RTABMAP_PYTHON
PythonInterface python; // Make sure we initialize python in main thread
#endif
/* Create tasks */
QApplication * app = new QApplication(argc, argv);
app->setStyleSheet("QMessageBox { messagebox-text-interaction-flags: 5; }"); // selectable message box
@@ -0,0 +1,22 @@
## Multi-Session Visual SLAM for Illumination Invariant Localization in Indoor Environments
* Paper: https://arxiv.org/abs/2103.03827
* 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).
![Overview](https://github.com/introlab/rtabmap/raw/master/archive/2020-IlluminationInvariant/images/fig_overview.jpg)]
## Description
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.
![All sessions](https://github.com/introlab/rtabmap/raw/master/archive/2020-IlluminationInvariant/images/fig_single_percentage.jpg)]
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.
![All sessions](https://github.com/introlab/rtabmap/raw/master/archive/2020-IlluminationInvariant/images/fig_merged_percentage.jpg)]
![All sessions](https://github.com/introlab/rtabmap/raw/master/archive/2020-IlluminationInvariant/images/fig_map_merged_999.jpg)]
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@@ -0,0 +1,135 @@
clear all
close all
pkg load signal
# rtabmap-report --loc 32 Loop/Odom_correction_norm/m Loop/Visual_inliers/ Timing/Total/ms . Keypoint/Current_frame/words
# Right-click on thr legend of the figure, copy all data to clipboard
# Paste in correction#.txt, inliers#.txt and time#.txt where # is the
# number of the descriptor used
skipFrameDir = '0';
prefix = 'Stat';
RAMaddOverhead = 1;
% Inliers_ratio = 'Loop/Visual_inliers/' ./ 'Keypoint/Current_frame/words'
% Odometry_average = 'Memory/Distance_travelled/m'(2:end) - 'Memory/Distance_travelled/m'(1:end-1)
statNames = {'Loop/Odom_correction_norm/m', 'Inliers_ratio_%', 'Timing/Total/ms', 'Memory/RAM_usage/MB', 'Memory/RAM_estimated/MB', 'Keypoint/Current_frame/words', 'Loop/Map_id/'}; % 'Odometry_average'
datasets = [ 0 1 6 7 9 12 14 11]; % 0 1 6 7 8 9 11 12
sep = [0, 1000, 3000, 5000, 7000, 9000, 12000];
sepName = {'16:51', '17:31', '17:58', '18:30', '18:59', '19:42'};
allCumResults = {};
allMaxResults = {};
for s=1:length(statNames)
avgResults = {};
maxResults = {};
totalResults = {};
absResults = {};
statName = strrep(statNames{s},'/','-');
for d=1:length(datasets)
if strcmp(statName,'Inliers_ratio_%')
data = dlmread([skipFrameDir '/' prefix num2str(datasets(d)) '-' 'Loop-Visual_inliers-' '.txt'], '\t', 1, 0, "emptyvalue", 0);
dataWords = dlmread([skipFrameDir '/' prefix num2str(datasets(d)) '-' 'Keypoint-Current_frame-words' '.txt'], '\t', 1, 0, "emptyvalue", 0);
data(:, 2:end) = data(:, 2:end) ./ dataWords(:, 2:end) * 100;
elseif strcmp(statName, 'Odometry_average')
data = dlmread([skipFrameDir '/' prefix num2str(datasets(d)) '-' 'Memory-Distance_travelled-m' '.txt'], '\t', 1, 0, "emptyvalue", 0);
else
data = dlmread([skipFrameDir '/' prefix num2str(datasets(d)) '-' statName '.txt'], '\t', 1, 0, "emptyvalue", 0);
endif
sessions = size(data,2)-1;
avgResultsTmp = zeros(sessions, length(sep)-1);
maxResultsTmp = zeros(sessions, length(sep)-1);
totalResultsTmp = zeros(sessions, length(sep)-1);
absResultsTmp = zeros(sessions, length(sep)-1);
for i = 1:sessions
for j = 1:length(sep)-1
x = data(:,1);
y = data(:,i+1);
y = y(x>=sep(j) & x<=sep(j+1), :);
x = x(x>=sep(j) & x<=sep(j+1), :);
if strcmp(statName, 'Odometry_average')
y(2:end) = y(2:end) - y(1:end-1);
y(y < 0.05) = 0;
elseif strcmp(statName, 'Loop-Map_id-')
y = y+1;
y(y>0) = 1;
end
if strcmp(statName, 'Memory-RAM_estimated-MB') && RAMaddOverhead == 1
% Valgrind estimated around 90 MB constant overhead
y = y + 90;
if datasets(d) == 7
%% 135 MB overhead for BRISK kernel
y = y + 135;
elseif datasets(d) == 11
%% 645 MB (library cuda) + 800 MB (network) for SuperPoint
y = y + 645+800;
elseif datasets(d) == 13 || datasets(d) == 14
%% 64 MB overhead for DAISY
y = y + 64;
endif
endif
nonzeros = y(y>0);
if strcmp(statName, 'Loop-Map_id-')
nonzeros = y;
end
if length(nonzeros) > 0
avgValue = sum(nonzeros)/length(nonzeros);
avgResultsTmp(i,j) = avgValue;
maxResultsTmp(i,j) = max(nonzeros);
totalResultsTmp(i,j) = length(nonzeros);
absResultsTmp(i,j) = sum(nonzeros);
endif
endfor
endfor
avgResults{1,d} = avgResultsTmp;
maxResults{1,d} = maxResultsTmp;
totalResults{1,d} = totalResultsTmp;
absResults{1,d} = absResultsTmp;
endfor
% compute cumulative results
cumResults = zeros(sessions+2, length(datasets)+1);
for d=1:length(datasets)
cumResults(1,d+1) = datasets(d);
if sum(totalResults{1,d}, 2)
cumResults(2:end-1,d+1) = sum(absResults{1,d}, 2) ./ sum(totalResults{1,d}, 2);
endif
cumResults(end,d+1) = sum(sum(absResults{1,d}(1:6,1:6).*eye(6,6))) / sum(sum(totalResults{1,d}(1:6,1:6).*eye(6,6)));
end
cumResults(2:end-1,1) = 1:sessions;
allCumResults{1,s} = statNames{s};
if strcmp(statNames{s}, 'Loop/Odom_correction_norm/m')
cumResults(2:end,2:end) = cumResults(2:end,2:end) * 1000;
allCumResults{1,s} = 'Loop/Odom_correction_norm/mm';
elseif strcmp(statNames{s}, 'Loop/Map_id/')
cumResults(2:end,2:end) = cumResults(2:end,2:end) * 100;
endif
allCumResults{2,s} = round(cumResults);
% compute max results
cumMaxResults = zeros(sessions+2, length(datasets)+1);
for d=1:length(datasets)
cumMaxResults(1,d+1) = datasets(d);
if sum(totalResults{1,d}, 2)
cumMaxResults(2:end-1,d+1) = max(maxResults{1,d}, [], 2);
endif
cumMaxResults(end,d+1) = max(max(maxResults{1,d}(1:6,1:6).*eye(6,6)));
end
cumMaxResults(2:end-1,1) = 1:sessions;
allMaxResults{1,s} = statNames{s};
allMaxResults{2,s} = cumMaxResults;
endfor % statNames
@@ -0,0 +1,235 @@
close all
clear all
pkg load signal
# rtabmap-report --loc 32 Loop/Map_id/ loc
# Right-click on thr legend of the figure, copy all data to clipboard
# Paste in data#.txt where # is the number of the descriptor used
resultsToShow = 1; % 1=single loc, 2=merged loc, 3=consecutive
skipFrameDir = '0';
datasetPrefix = 'Stat';
datasets = [0 1 6 7 9 12 14 11]; % 0 1 6 7 8 9 11 12
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'};
sep = [0, 1000, 3000, 5000, 7000, 9000, 12000];
sepName = {'16:51', '17:31', '17:58', '18:30', '18:59', '19:42'};
if resultsToShow == 3
sep = [0, 1000, 3000, 5000, 7000, 9000];
sepName = {'17:27', '17:54', '18:27', '18:56', '19:35'};
datasetPrefix = 'Consecutive'
endif
percentResults = {};
totalResults = {};
locResults = {};
figure
colors = get(gca, 'ColorOrder');
tmp=colors(3,:);
colors(3,:) = colors(5,:);
colors(5,:) = tmp;
globalSeparators = [];
globalx = [];
globaly = [];
globalc = [];
for d=1:length(datasets)
data = dlmread([skipFrameDir '/' datasetPrefix num2str(datasets(d)) '-Loop-Map_id-' '.txt'], '\t', 1, 0, "emptyvalue", NaN);
curvesBeg = 2;
curvesEnd = size(data,2)-4;
if resultsToShow == 2
curvesBeg = 8;
curvesEnd = size(data,2);
elseif resultsToShow == 3
curvesEnd = size(data,2);
endif
curves = curvesEnd - curvesBeg + 1;
percentResultsTmp = zeros(curves, length(sep)-1);
totalResultsTmp = zeros(curves, length(sep)-1);
locResultsTmp = zeros(curves, length(sep)-1);
offset = 1;
for i = 1:curves
index = i + curvesBeg - 1;
separators = [];
x_all = [];
y_all = [];
m_all = [];
previousMax = 0;
for j = 1:length(sep)-1
x = data(:,1);
y = data(:,index);
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;
m(m==2) = 3;
m(m==3) = 3;
m(m==4) = 5;
elseif i==3 %% Merged 2(2 sessions),4,6
m(m==1) = 2;
m(m==2) = 2;
m(m==4) = 6;
m(m==3) = 4;
elseif i>=4 %% Merged 1, 2(2 sessions), 3(2 sessions),4,5,6
m(m==1) = 1;
m(m==2) = 2;
m(m==3) = 2;
m(m==4) = 3;
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;
imagesc( hAxes, data, [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, 'XTickLabel', sepName, 'fontsize',7)
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+6', 'bundle', 'reduced'}, '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
+19
View File
@@ -0,0 +1,19 @@
#!/bin/bash
SKIP=0
if [ $# -eq 1 ]
then
SKIP=$1
fi
DETECTOR=(0 1 6 7 9 11 12 14) #0 1 6 7 8 9 11 12 13 14
PREFIX="/home/mathieu/workspace/rtabmap_cv_latest/bin/"
REPORT_TOOL="${PREFIX}rtabmap-report"
for d in "${DETECTOR[@]}"
do
$REPORT_TOOL --export --export_prefix "Stat$d" --loc 32 Loop/Odom_correction_norm/m Loop/Visual_inliers/ Timing/Total/ms Loop/Map_id/ Keypoint/Current_frame/words Memory/RAM_usage/MB Memory/RAM_estimated/MB Memory/Distance_travelled/m "$SKIP/$d/loc"
$REPORT_TOOL --export --export_prefix "Consecutive$d" --loc 32 Loop/Map_id/ "$SKIP/$d/consecutive_loc"
done
@@ -0,0 +1,42 @@
#!/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
SKIP=0
if [ $# -eq 2 ]
then
SKIP=$2
fi
PREFIX="/home/mathieu/workspace/rtabmap_cv_latest/bin/"
REPROCESS_TOOL="${PREFIX}rtabmap-reprocess"
DETECT_MORE_LOOP_CLOSURE_TOOL="${PREFIX}rtabmap-detectMoreLoopClosures"
[ ! -d "$SKIP" ] && mkdir $SKIP
[ ! -d "$SKIP/$TYPE" ] && mkdir $SKIP/$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"
if
echo $PARAMS
for db in "${DATABASES[@]}"
do
$REPROCESS_TOOL --skip $SKIP --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 4 --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 --uerror $PARAMS $db $SKIP/$TYPE/$db
$DETECT_MORE_LOOP_CLOSURE_TOOL --uwarn $SKIP/$TYPE/$db
done
@@ -0,0 +1,16 @@
#!/bin/bash
SKIP=0
if [ $# -eq 1 ]
then
SKIP=$1
fi
DETECTOR=(0 1 6 7 9 11 12 14)
for d in "${DETECTOR[@]}"
do
./reprocess_maps.sh $d $SKIP
./run_merge.sh $d $SKIP
done
+13
View File
@@ -0,0 +1,13 @@
#!/bin/bash
SKIP=0
if [ $# -eq 1 ]
then
SKIP=$1
fi
./reprocess_maps_all.sh $SKIP
./run_merge.sh $SKIP
./run_localization_single_all.sh $SKIP
./run_consecutive_localization_all.sh $SKIP
@@ -0,0 +1,31 @@
#!/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
SKIP=0
if [ $# -eq 2 ]
then
SKIP=$2
fi
PREFIX="/home/mathieu/workspace/rtabmap_cv_latest/bin/"
REPROCESS_TOOL="${PREFIX}rtabmap-reprocess"
SOURCE=('map_190321-164651.db' 'map_190321-172717.db' 'map_190321-175428.db' 'map_190321-182709.db' 'map_190321-185608.db')
TARGETS=($SKIP/$TYPE'/map_190321-172717.db;'$SKIP/$TYPE'/map_190321-175428.db;'$SKIP/$TYPE'/map_190321-193556.db' $SKIP/$TYPE'/map_190321-175428.db;'$SKIP/$TYPE'/map_190321-182709.db;' $SKIP/$TYPE'/map_190321-182709.db;'$SKIP/$TYPE'/map_190321-185608.db' $SKIP/$TYPE'/map_190321-185608.db;'$SKIP/$TYPE'/map_190321-193556.db' $SKIP/$TYPE'/map_190321-193556.db' )
[ ! -d "$SKIP/$TYPE/consecutive_loc" ] && mkdir $SKIP/$TYPE/consecutive_loc
for i in ${!SOURCE[@]}
do
db=${SOURCE[$i]}
loc_dbs=${TARGETS[$i]}
$REPROCESS_TOOL --Mem/IncrementalMemory false --RGBD/ProximityBySpace true --Mem/LocalizationDataSaved true --Mem/BinDataKept false --RGBD/SavedLocalizationIgnored true --uwarn "$SKIP/$TYPE/$db;$loc_dbs" $SKIP/$TYPE/consecutive_loc/loc_$db
done
@@ -0,0 +1,15 @@
#!/bin/bash
SKIP=0
if [ $# -eq 1 ]
then
SKIP=$1
fi
DETECTOR=(0 1 6 7 9 11 12 14)
for d in "${DETECTOR[@]}"
do
./run_consecutive_localization.sh $d $SKIP
done
@@ -0,0 +1,38 @@
#!/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
SKIP=0
if [ $# -eq 2 ]
then
SKIP=$2
fi
PREFIX="/home/mathieu/workspace/rtabmap_cv_latest/bin/"
REPROCESS_TOOL="${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 "$SKIP/$TYPE/loc" ] && mkdir $SKIP/$TYPE/accuracy
db=merged_9999.db
$REPROCESS_TOOL --skip $SKIP --Mem/IncrementalMemory false --RGBD/ProximityBySpace true --Mem/LocalizationDataSaved true --Mem/BinDataKept false --RGBD/SavedLocalizationIgnored true --Kp/IncrementalFlann false --Vis/MinInliers 20 --Rtabmap/PublishRAMUsage true --RGBD/ProximityOdomGuess false --Reg/RepeatOnce true --Vis/BundleAdjustment 1 --uwarn "$SKIP/$TYPE/$db;$LOCALIZATION_DATABASES" $SKIP/$TYPE/accuracy/ProxOff_DoubleRegOn_BaOn_$db
$REPROCESS_TOOL --skip $SKIP --Mem/IncrementalMemory false --RGBD/ProximityBySpace true --Mem/LocalizationDataSaved true --Mem/BinDataKept false --RGBD/SavedLocalizationIgnored true --Kp/IncrementalFlann false --Vis/MinInliers 20 --Rtabmap/PublishRAMUsage true --RGBD/ProximityOdomGuess false --Reg/RepeatOnce false --Vis/BundleAdjustment 1 --uwarn "$SKIP/$TYPE/$db;$LOCALIZATION_DATABASES" $SKIP/$TYPE/accuracy/ProxOff_DoubleRegOff_BaOn_$db
$REPROCESS_TOOL --skip $SKIP --Mem/IncrementalMemory false --RGBD/ProximityBySpace true --Mem/LocalizationDataSaved true --Mem/BinDataKept false --RGBD/SavedLocalizationIgnored true --Kp/IncrementalFlann false --Vis/MinInliers 20 --Rtabmap/PublishRAMUsage true --RGBD/ProximityOdomGuess false --Reg/RepeatOnce true --Vis/BundleAdjustment 0 --uwarn "$SKIP/$TYPE/$db;$LOCALIZATION_DATABASES" $SKIP/$TYPE/accuracy/ProxOff_DoubleRegOn_BaOff_$db
$REPROCESS_TOOL --skip $SKIP --Mem/IncrementalMemory false --RGBD/ProximityBySpace true --Mem/LocalizationDataSaved true --Mem/BinDataKept false --RGBD/SavedLocalizationIgnored true --Kp/IncrementalFlann false --Vis/MinInliers 20 --Rtabmap/PublishRAMUsage true --RGBD/ProximityOdomGuess false --Reg/RepeatOnce false --Vis/BundleAdjustment 0 --uwarn "$SKIP/$TYPE/$db;$LOCALIZATION_DATABASES" $SKIP/$TYPE/accuracy/ProxOff_DoubleRegOff_BaOff_$db
$REPROCESS_TOOL --skip $SKIP --Mem/IncrementalMemory false --RGBD/ProximityBySpace true --Mem/LocalizationDataSaved true --Mem/BinDataKept false --RGBD/SavedLocalizationIgnored true --Kp/IncrementalFlann false --Vis/MinInliers 20 --Rtabmap/PublishRAMUsage true --RGBD/ProximityOdomGuess true --Reg/RepeatOnce true --Vis/BundleAdjustment 1 --uwarn "$SKIP/$TYPE/$db;$LOCALIZATION_DATABASES" $SKIP/$TYPE/accuracy/ProxOn_DoubleRegOn_BaOn_$db
$REPROCESS_TOOL --skip $SKIP --Mem/IncrementalMemory false --RGBD/ProximityBySpace true --Mem/LocalizationDataSaved true --Mem/BinDataKept false --RGBD/SavedLocalizationIgnored true --Kp/IncrementalFlann false --Vis/MinInliers 20 --Rtabmap/PublishRAMUsage true --RGBD/ProximityOdomGuess true --Reg/RepeatOnce true --Vis/BundleAdjustment 0 --uwarn "$SKIP/$TYPE/$db;$LOCALIZATION_DATABASES" $SKIP/$TYPE/accuracy/ProxOn_DoubleRegOn_BaOff_$db
@@ -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
SKIP=0
if [ $# -eq 2 ]
then
SKIP=$2
fi
PREFIX="/home/mathieu/workspace/rtabmap_cv_latest/bin/"
REPROCESS_TOOL="${PREFIX}rtabmap-reprocess"
# '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_9999.db' 'merged_135.db' 'merged_246.db' 'merged_16.db' 'merged_9999_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_9999.db' 'merged_135.db' 'merged_246.db' 'merged_16.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 "$SKIP/$TYPE/loc" ] && mkdir $SKIP/$TYPE/loc
echo $PARAMS
for db in "${DATABASES[@]}"
do
$REPROCESS_TOOL --skip $SKIP --Mem/IncrementalMemory false --RGBD/ProximityBySpace true --Mem/LocalizationDataSaved true --Mem/BinDataKept false --RGBD/SavedLocalizationIgnored true --Kp/IncrementalFlann false --Vis/MinInliers 20 --Rtabmap/PublishRAMUsage true --RGBD/ProximityOdomGuess false --uwarn "$SKIP/$TYPE/$db;$LOCALIZATION_DATABASES" $SKIP/$TYPE/loc/loc_$db
done
@@ -0,0 +1,15 @@
#!/bin/bash
SKIP=0
if [ $# -eq 1 ]
then
SKIP=$1
fi
DETECTOR=(0 1 6 7 9 11 12 14)
for d in "${DETECTOR[@]}"
do
./run_localization_single.sh $d $SKIP
done
+38
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@@ -0,0 +1,38 @@
#!/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
SKIP=0
if [ $# -eq 2 ]
then
SKIP=$2
fi
PREFIX="/home/mathieu/workspace/rtabmap_cv_latest/bin/"
REPROCESS_TOOL="${PREFIX}rtabmap-reprocess"
DETECT_MORE_LOOP_CLOSURE_TOOL="${PREFIX}rtabmap-detectMoreLoopClosures"
DATABASES="$SKIP/$TYPE/map_190321-164651.db;$SKIP/$TYPE/map_190321-172717.db;$SKIP/$TYPE/map_190321-175428.db;$SKIP/$TYPE/map_190321-182709.db;$SKIP/$TYPE/map_190321-185608.db;$SKIP/$TYPE/map_190321-193556.db"
$REPROCESS_TOOL --uwarn --RGBD/OptimizeMaxError 0 "$DATABASES" $SKIP/$TYPE/merged_9999.db
$DETECT_MORE_LOOP_CLOSURE_TOOL $SKIP/$TYPE/merged_9999.db
#$REPROCESS_TOOL --uwarn --RGBD/OptimizeMaxError 0 --Mem/ReduceGraph true --Vis/MinInliers 60 "$DATABASES" $SKIP/$TYPE/merged_9999_reduced.db
#$DETECT_MORE_LOOP_CLOSURE_TOOL $SKIP/$TYPE/merged_9999_reduced.db
$REPROCESS_TOOL --uwarn --RGBD/OptimizeMaxError 0 "$SKIP/$TYPE/map_190321-164651.db;$SKIP/$TYPE/map_190321-193556.db" $SKIP/$TYPE/merged_16.db
$DETECT_MORE_LOOP_CLOSURE_TOOL $SKIP/$TYPE/merged_16.db
$REPROCESS_TOOL --uwarn --RGBD/OptimizeMaxError 0 "$SKIP/$TYPE/map_190321-164651.db;$SKIP/$TYPE/map_190321-175428.db;$SKIP/$TYPE/map_190321-185608.db" $SKIP/$TYPE/merged_135.db
$DETECT_MORE_LOOP_CLOSURE_TOOL $SKIP/$TYPE/merged_135.db
$REPROCESS_TOOL --uwarn --RGBD/OptimizeMaxError 0 "$SKIP/$TYPE/map_190321-172717.db;$SKIP/$TYPE/map_190321-182709.db;$SKIP/$TYPE/map_190321-193556.db" $SKIP/$TYPE/merged_246.db
$DETECT_MORE_LOOP_CLOSURE_TOOL $SKIP/$TYPE/merged_246.db
+19
View File
@@ -0,0 +1,19 @@
#!/bin/bash
SKIP=0
if [ $# -eq 1 ]
then
SKIP=$1
fi
DETECTOR=(0 1 6 7 8 9 11 12 14)
PREFIX="/home/mathieu/workspace/rtabmap_cv_latest/bin/"
REPORT_TOOL="${PREFIX}rtabmap-report"
for d in "${DETECTOR[@]}"
do
valgrind --tool=massif --time-unit=ms --detailed-freq=1 --max-snapshots=100 ${PREFIX}rtabmap-reprocess --Mem/IncrementalMemory false --Kp/IncrementalFlann false "${SKIP}/${d}/merged_9999.db;map_190321-164651.db" output.db
rm output.db
done
+234
View File
@@ -0,0 +1,234 @@
#.rst:
# FindHIDAPI
# ----------
#
# Try to find HIDAPI library, from http://www.signal11.us/oss/hidapi/
#
# Cache Variables: (probably not for direct use in your scripts)
# HIDAPI_INCLUDE_DIR
# HIDAPI_LIBRARY
#
# Non-cache variables you might use in your CMakeLists.txt:
# HIDAPI_FOUND
# HIDAPI_INCLUDE_DIRS
# HIDAPI_LIBRARIES
#
# COMPONENTS
# ^^^^^^^^^^
#
# This module respects several COMPONENTS specifying the backend you prefer:
# ``any`` (the default), ``libusb``, and ``hidraw``.
# The availablility of the latter two depends on your platform.
#
#
# IMPORTED Targets
# ^^^^^^^^^^^^^^^^
# This module defines :prop_tgt:`IMPORTED` target ``HIDAPI::hidapi`` (in all cases or
# if no components specified), ``HIDAPI::hidapi-libusb`` (if you requested the libusb component),
# and ``HIDAPI::hidapi-hidraw`` (if you requested the hidraw component),
#
# Result Variables
# ^^^^^^^^^^^^^^^^
#
# ``HIDAPI_FOUND``
# True if HIDAPI or the requested components (if any) were found.
#
# We recommend using the imported targets instead of the following.
#
# ``HIDAPI_INCLUDE_DIRS``
# ``HIDAPI_LIBRARIES``
#
# Original Author:
# 2009-2010, 2019 Ryan Pavlik <ryan.pavlik@collabora.com> <abiryan@ryand.net>
# http://academic.cleardefinition.com
#
# Copyright Iowa State University 2009-2010.
# Copyright Collabora, Ltd. 2019.
# Distributed under the Boost Software License, Version 1.0.
# (See accompanying file LICENSE_1_0.txt or copy at
# http://www.boost.org/LICENSE_1_0.txt)
cmake_policy(SET CMP0045 NEW)
cmake_policy(SET CMP0053 NEW)
cmake_policy(SET CMP0054 NEW)
set(HIDAPI_ROOT_DIR
"${HIDAPI_ROOT_DIR}"
CACHE PATH "Root to search for HIDAPI")
# Clean up components
if("${HIDAPI_FIND_COMPONENTS}")
if(WIN32 OR APPLE)
# This makes no sense on Windows or Mac, which have native APIs
list(REMOVE HIDAPI_FIND_COMPONENTS libusb)
endif()
if(NOT ${CMAKE_SYSTEM} MATCHES "Linux")
# hidraw is only on linux
list(REMOVE HIDAPI_FIND_COMPONENTS hidraw)
endif()
endif()
if(NOT "${HIDAPI_FIND_COMPONENTS}")
# Default to any
set(HIDAPI_FIND_COMPONENTS any)
endif()
# Ask pkg-config for hints
find_package(PkgConfig QUIET)
if(PKG_CONFIG_FOUND)
set(_old_prefix_path "${CMAKE_PREFIX_PATH}")
# So pkg-config uses HIDAPI_ROOT_DIR too.
if(HIDAPI_ROOT_DIR)
list(APPEND CMAKE_PREFIX_PATH ${HIDAPI_ROOT_DIR})
endif()
pkg_check_modules(PC_HIDAPI_LIBUSB QUIET hidapi-libusb)
pkg_check_modules(PC_HIDAPI_HIDRAW QUIET hidapi-hidraw)
# Restore
set(CMAKE_PREFIX_PATH "${_old_prefix_path}")
endif()
# Actually search
find_library(
HIDAPI_UNDECORATED_LIBRARY
NAMES hidapi
PATHS "${HIDAPI_ROOT_DIR}"
PATH_SUFFIXES lib)
find_library(
HIDAPI_LIBUSB_LIBRARY
NAMES hidapi hidapi-libusb
PATHS "${HIDAPI_ROOT_DIR}"
PATH_SUFFIXES lib
HINTS ${PC_HIDAPI_LIBUSB_LIBRARY_DIRS})
if(CMAKE_SYSTEM MATCHES "Linux")
find_library(
HIDAPI_HIDRAW_LIBRARY
NAMES hidapi-hidraw
HINTS ${PC_HIDAPI_HIDRAW_LIBRARY_DIRS})
endif()
find_path(
HIDAPI_INCLUDE_DIR
NAMES hidapi.h
PATHS "${HIDAPI_ROOT_DIR}"
PATH_SUFFIXES hidapi include include/hidapi
HINTS ${PC_HIDAPI_HIDRAW_INCLUDE_DIRS} ${PC_HIDAPI_LIBUSB_INCLUDE_DIRS})
find_package(Threads QUIET)
###
# Compute the "I don't care which backend" library
###
set(HIDAPI_LIBRARY)
# First, try to use a preferred backend if supplied
if("${HIDAPI_FIND_COMPONENTS}" MATCHES "libusb"
AND HIDAPI_LIBUSB_LIBRARY
AND NOT HIDAPI_LIBRARY)
set(HIDAPI_LIBRARY ${HIDAPI_LIBUSB_LIBRARY})
endif()
if("${HIDAPI_FIND_COMPONENTS}" MATCHES "hidraw"
AND HIDAPI_HIDRAW_LIBRARY
AND NOT HIDAPI_LIBRARY)
set(HIDAPI_LIBRARY ${HIDAPI_HIDRAW_LIBRARY})
endif()
# Then, if we don't have a preferred one, settle for anything.
if(NOT HIDAPI_LIBRARY)
if(HIDAPI_LIBUSB_LIBRARY)
set(HIDAPI_LIBRARY ${HIDAPI_LIBUSB_LIBRARY})
elseif(HIDAPI_HIDRAW_LIBRARY)
set(HIDAPI_LIBRARY ${HIDAPI_HIDRAW_LIBRARY})
elseif(HIDAPI_UNDECORATED_LIBRARY)
set(HIDAPI_LIBRARY ${HIDAPI_UNDECORATED_LIBRARY})
endif()
endif()
###
# Determine if the various requested components are found.
###
set(_hidapi_component_required_vars)
foreach(_comp IN LISTS HIDAPI_FIND_COMPONENTS)
if("${_comp}" STREQUAL "any")
list(APPEND _hidapi_component_required_vars HIDAPI_INCLUDE_DIR
HIDAPI_LIBRARY)
if(HIDAPI_INCLUDE_DIR AND EXISTS "${HIDAPI_LIBRARY}")
set(HIDAPI_any_FOUND TRUE)
mark_as_advanced(HIDAPI_INCLUDE_DIR)
else()
set(HIDAPI_any_FOUND FALSE)
endif()
elseif("${_comp}" STREQUAL "libusb")
list(APPEND _hidapi_component_required_vars HIDAPI_INCLUDE_DIR
HIDAPI_LIBUSB_LIBRARY)
if(HIDAPI_INCLUDE_DIR AND EXISTS "${HIDAPI_LIBUSB_LIBRARY}")
set(HIDAPI_libusb_FOUND TRUE)
mark_as_advanced(HIDAPI_INCLUDE_DIR HIDAPI_LIBUSB_LIBRARY)
else()
set(HIDAPI_libusb_FOUND FALSE)
endif()
elseif("${_comp}" STREQUAL "hidraw")
list(APPEND _hidapi_component_required_vars HIDAPI_INCLUDE_DIR
HIDAPI_HIDRAW_LIBRARY)
if(HIDAPI_INCLUDE_DIR AND EXISTS "${HIDAPI_HIDRAW_LIBRARY}")
set(HIDAPI_hidraw_FOUND TRUE)
mark_as_advanced(HIDAPI_INCLUDE_DIR HIDAPI_HIDRAW_LIBRARY)
else()
set(HIDAPI_hidraw_FOUND FALSE)
endif()
else()
message(WARNING "${_comp} is not a recognized HIDAPI component")
set(HIDAPI_${_comp}_FOUND FALSE)
endif()
endforeach()
unset(_comp)
###
# FPHSA call
###
include(FindPackageHandleStandardArgs)
find_package_handle_standard_args(
HIDAPI REQUIRED_VARS ${_hidapi_component_required_vars} THREADS_FOUND
HANDLE_COMPONENTS)
if(HIDAPI_FOUND)
set(HIDAPI_LIBRARIES "${HIDAPI_LIBRARY}")
set(HIDAPI_INCLUDE_DIRS "${HIDAPI_INCLUDE_DIR}")
if(NOT TARGET HIDAPI::hidapi)
add_library(HIDAPI::hidapi UNKNOWN IMPORTED)
set_target_properties(
HIDAPI::hidapi
PROPERTIES
IMPORTED_LINK_INTERFACE_LANGUAGES "C"
IMPORTED_LOCATION ${HIDAPI_LIBRARY})
set_property(
TARGET HIDAPI::hidapi PROPERTY IMPORTED_LINK_INTERFACE_LIBRARIES
Threads::Threads)
endif()
endif()
if(HIDAPI_libusb_FOUND AND NOT TARGET HIDAPI::hidapi-libusb)
add_library(HIDAPI::hidapi-libusb UNKNOWN IMPORTED)
set_target_properties(
HIDAPI::hidapi-libusb
PROPERTIES IMPORTED_LINK_INTERFACE_LANGUAGES "C" IMPORTED_LOCATION
${HIDAPI_LIBUSB_LIBRARY})
set_property(TARGET HIDAPI::hidapi-libusb
PROPERTY IMPORTED_LINK_INTERFACE_LIBRARIES Threads::Threads)
endif()
if(HIDAPI_hidraw_FOUND AND NOT TARGET HIDAPI::hidapi-hidraw)
add_library(HIDAPI::hidapi-hidraw UNKNOWN IMPORTED)
set_target_properties(
HIDAPI::hidapi-hidraw
PROPERTIES IMPORTED_LINK_INTERFACE_LANGUAGES "C" IMPORTED_LOCATION
${HIDAPI_HIDRAW_LIBRARY})
set_property(TARGET HIDAPI::hidapi-hidraw
PROPERTY IMPORTED_LINK_INTERFACE_LIBRARIES Threads::Threads)
endif()
+53
View File
@@ -0,0 +1,53 @@
# - Find ORB_SLAM2 OR ORB_SLAM3
#
# It sets the following variables:
# ORB_SLAM_FOUND - Set to false, or undefined, if ORB_SLAM isn't found.
# ORB_SLAM_INCLUDE_DIRS - The ORB_SLAM include directory.
# ORB_SLAM_LIBRARIES - The ORB_SLAM library to link against.
# ORB_SLAM_VERSION - The ORB_SLAM major version.
#
# Set ORB_SLAM_ROOT_DIR environment variable as the path to ORB_SLAM2 or ORB_SLAM3 root folder.
find_path(ORB_SLAM_INCLUDE_DIR NAMES System.h PATHS $ENV{ORB_SLAM_ROOT_DIR}/include)
find_library(ORB_SLAM2_LIBRARY NAMES ORB_SLAM2 PATHS $ENV{ORB_SLAM_ROOT_DIR}/lib)
find_library(ORB_SLAM3_LIBRARY NAMES ORB_SLAM3 PATHS $ENV{ORB_SLAM_ROOT_DIR}/lib)
find_path(g2o_INCLUDE_DIR NAMES g2o/core/sparse_optimizer.h PATHS $ENV{ORB_SLAM_ROOT_DIR}/Thirdparty/g2o NO_DEFAULT_PATH)
find_library(g2o_LIBRARY NAMES g2o PATHS $ENV{ORB_SLAM_ROOT_DIR}/Thirdparty/g2o/lib NO_DEFAULT_PATH)
find_library(DBoW2_LIBRARY NAMES DBoW2 PATHS $ENV{ORB_SLAM_ROOT_DIR}/Thirdparty/DBoW2/lib NO_DEFAULT_PATH)
IF(ORB_SLAM2_LIBRARY)
SET(ORB_SLAM_VERSION 2)
SET(ORB_SLAM_LIBRARY ${ORB_SLAM2_LIBRARY})
ELSEIF(ORB_SLAM3_LIBRARY)
SET(ORB_SLAM_VERSION 3)
SET(ORB_SLAM_LIBRARY ${ORB_SLAM3_LIBRARY})
ENDIF()
IF (ORB_SLAM_INCLUDE_DIR AND ORB_SLAM_LIBRARY AND DBoW2_LIBRARY AND g2o_INCLUDE_DIR AND g2o_LIBRARY)
SET(ORB_SLAM_FOUND TRUE)
SET(ORB_SLAM_INCLUDE_DIRS ${ORB_SLAM_INCLUDE_DIR} ${ORB_SLAM_INCLUDE_DIR}/CameraModels ${g2o_INCLUDE_DIR} $ENV{ORB_SLAM_ROOT_DIR})
SET(ORB_SLAM_LIBRARIES ${g2o_LIBRARY} ${ORB_SLAM_LIBRARY} ${DBoW2_LIBRARY})
ENDIF (ORB_SLAM_INCLUDE_DIR AND ORB_SLAM_LIBRARY AND DBoW2_LIBRARY AND g2o_INCLUDE_DIR AND g2o_LIBRARY)
FIND_PACKAGE(Pangolin QUIET)
IF(NOT Pangolin_FOUND)
SET(ORB_SLAM_FOUND FALSE)
MESSAGE(STATUS "Found ORB_SLAM but not Pangolin, disabling ORB_SLAM.")
ELSE()
MESSAGE(STATUS "Found Pangolin: ${Pangolin_INCLUDE_DIRS}")
SET(ORB_SLAM_INCLUDE_DIRS ${ORB_SLAM_INCLUDE_DIRS} ${Pangolin_INCLUDE_DIRS})
SET(ORB_SLAM_LIBRARIES ${ORB_SLAM_LIBRARIES} ${Pangolin_LIBRARIES})
ENDIF()
IF (ORB_SLAM_FOUND)
# show which ORB_SLAM was found only if not quiet
IF (NOT ORB_SLAM_FIND_QUIETLY)
MESSAGE(STATUS "Found ORB_SLAM${ORB_SLAM_VERSION}: ${ORB_SLAM_LIBRARIES}")
ENDIF (NOT ORB_SLAM_FIND_QUIETLY)
ELSE (ORB_SLAM_FOUND)
# fatal error if ORB_SLAM is required but not found
IF (ORB_SLAM_FIND_REQUIRED)
MESSAGE(FATAL_ERROR "Could not find ORB_SLAM")
ENDIF (ORB_SLAM_FIND_REQUIRED)
ENDIF (ORB_SLAM_FOUND)
-33
View File
@@ -1,33 +0,0 @@
# - Find ORB_SLAM2
#
# It sets the following variables:
# ORB_SLAM2_FOUND - Set to false, or undefined, if ORB_SLAM2 isn't found.
# ORB_SLAM2_INCLUDE_DIRS - The ORB_SLAM2 include directory.
# ORB_SLAM2_LIBRARIES - The ORB_SLAM2 library to link against.
#
# Set ORB_SLAM2_ROOT_DIR environment variable as the path to ORB_SLAM2 root folder.
find_path(ORB_SLAM2_INCLUDE_DIR NAMES System.h PATHS $ENV{ORB_SLAM2_ROOT_DIR}/include)
find_library(ORB_SLAM2_LIBRARY NAMES ORB_SLAM2 PATHS $ENV{ORB_SLAM2_ROOT_DIR}/lib)
find_path(g2o_INCLUDE_DIR NAMES g2o/core/sparse_optimizer.h PATHS $ENV{ORB_SLAM2_ROOT_DIR}/Thirdparty/g2o NO_DEFAULT_PATH)
find_library(g2o_LIBRARY NAMES g2o PATHS $ENV{ORB_SLAM2_ROOT_DIR}/Thirdparty/g2o/lib NO_DEFAULT_PATH)
find_library(DBoW2_LIBRARY NAMES DBoW2 PATHS $ENV{ORB_SLAM2_ROOT_DIR}/Thirdparty/DBoW2/lib NO_DEFAULT_PATH)
IF (ORB_SLAM2_INCLUDE_DIR AND ORB_SLAM2_LIBRARY AND DBoW2_LIBRARY AND g2o_INCLUDE_DIR AND g2o_LIBRARY)
SET(ORB_SLAM2_FOUND TRUE)
SET(ORB_SLAM2_INCLUDE_DIRS ${ORB_SLAM2_INCLUDE_DIR} ${g2o_INCLUDE_DIR} $ENV{ORB_SLAM2_ROOT_DIR})
SET(ORB_SLAM2_LIBRARIES ${g2o_LIBRARY} ${ORB_SLAM2_LIBRARY} ${DBoW2_LIBRARY})
ENDIF (ORB_SLAM2_INCLUDE_DIR AND ORB_SLAM2_LIBRARY AND DBoW2_LIBRARY AND g2o_INCLUDE_DIR AND g2o_LIBRARY)
IF (ORB_SLAM2_FOUND)
# show which ORB_SLAM2 was found only if not quiet
IF (NOT ORB_SLAM2_FIND_QUIETLY)
MESSAGE(STATUS "Found ORB_SLAM2: ${ORB_SLAM2_LIBRARIES}")
ENDIF (NOT ORB_SLAM2_FIND_QUIETLY)
ELSE (ORB_SLAM2_FOUND)
# fatal error if ORB_SLAM2 is required but not found
IF (ORB_SLAM2_FIND_REQUIRED)
MESSAGE(FATAL_ERROR "Could not find ORB_SLAM2")
ENDIF (ORB_SLAM2_FIND_REQUIRED)
ENDIF (ORB_SLAM2_FOUND)
+28
View File
@@ -0,0 +1,28 @@
# - Find ZED Open Capture
# This module finds zed open capture library
#
# It sets the following variables:
# ZEDOC_FOUND - Set to false, or undefined, if ZEDOC isn't found.
# ZEDOC_INCLUDE_DIRS - The ZEDOC include directory.
# ZEDOC_LIBRARIES - The ZEDOC library to link against.
find_library(ZEDOC_LIBRARY NAMES zed_open_capture PATHS $ENV{ZEDOC_ROOT_DIR}/lib)
find_path(ZEDOC_INCLUDE_DIR NAMES zed-open-capture/videocapture.hpp PATHS $ENV{ZEDOC_ROOT_DIR}/include)
IF (ZEDOC_INCLUDE_DIR AND ZEDOC_LIBRARY)
SET(ZEDOC_FOUND TRUE)
SET(ZEDOC_INCLUDE_DIRS ${ZEDOC_INCLUDE_DIR})
SET(ZEDOC_LIBRARIES ${ZEDOC_LIBRARY})
ENDIF (ZEDOC_INCLUDE_DIR AND ZEDOC_LIBRARY)
IF (ZEDOC_FOUND)
# show which ZEDOC was found only if not quiet
IF (NOT _FIND_QUIETLY)
MESSAGE(STATUS "Found ZEDOC: ${ZEDOC_LIBRARIES}")
ENDIF (NOT ZEDOC_FIND_QUIETLY)
ELSE (ZEDOC_FOUND)
# fatal error if ZEDOC is required but not found
IF (ZEDOC_FIND_REQUIRED)
MESSAGE(FATAL_ERROR "Could not find ZEDOC (Zed Open Capture)")
ENDIF (ZEDOC_FIND_REQUIRED)
ENDIF (ZEDOC_FOUND)
@@ -32,5 +32,7 @@ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#include <rtabmap/core/camera/CameraStereoImages.h>
#include <rtabmap/core/camera/CameraStereoVideo.h>
#include <rtabmap/core/camera/CameraStereoZed.h>
#include <rtabmap/core/camera/CameraStereoZedOC.h>
#include <rtabmap/core/camera/CameraStereoTara.h>
#include <rtabmap/core/camera/CameraMyntEye.h>
#include <rtabmap/core/camera/CameraDepthAI.h>
+13 -13
View File
@@ -69,9 +69,18 @@ public:
void setDistortionModel(const std::string & path);
void enableBilateralFiltering(float sigmaS, float sigmaR);
void disableBilateralFiltering() {_bilateralFiltering = false;}
void enableIMUFiltering(int filteringStrategy=1, const ParametersMap & parameters = ParametersMap());
void enableIMUFiltering(int filteringStrategy=1, const ParametersMap & parameters = ParametersMap(), bool baseFrameConversion = false);
void disableIMUFiltering();
RTABMAP_DEPRECATED(void setScanParameters(
bool fromDepth,
int downsampleStep, // decimation of the depth image in case the scan is from depth image
float rangeMin,
float rangeMax,
float voxelSize,
int normalsK,
int normalsRadius,
bool forceGroundNormalsUp) , "Use new version of this function with groundNormalsUp=0.8 for forceGroundNormalsUp=True and groundNormalsUp=0.0 for forceGroundNormalsUp=False.");
void setScanParameters(
bool fromDepth,
int downsampleStep=1, // decimation of the depth image in case the scan is from depth image
@@ -80,17 +89,7 @@ public:
float voxelSize = 0.0f,
int normalsK = 0,
int normalsRadius = 0.0f,
bool forceGroundNormalsUp = false)
{
_scanFromDepth = fromDepth;
_scanDownsampleStep=downsampleStep;
_scanRangeMin = rangeMin;
_scanRangeMax = rangeMax;
_scanVoxelSize = voxelSize;
_scanNormalsK = normalsK;
_scanNormalsRadius = normalsRadius;
_scanForceGroundNormalsUp = forceGroundNormalsUp;
}
float groundNormalsUp = 0.0f);
void postUpdate(SensorData * data, CameraInfo * info = 0) const;
@@ -119,13 +118,14 @@ private:
float _scanVoxelSize;
int _scanNormalsK;
float _scanNormalsRadius;
bool _scanForceGroundNormalsUp;
float _scanForceGroundNormalsUp;
StereoDense * _stereoDense;
clams::DiscreteDepthDistortionModel * _distortionModel;
bool _bilateralFiltering;
float _bilateralSigmaS;
float _bilateralSigmaR;
IMUFilter * _imuFilter;
bool _imuBaseFrameConversion;
};
} // namespace rtabmap
+6 -4
View File
@@ -70,6 +70,7 @@ public:
virtual void parseParameters(const ParametersMap & parameters);
virtual bool isInMemory() const {return _url.empty();}
const std::string & getUrl() const {return _url;}
const std::string & getTargetVersion() const {return _targetVersion;}
void beginTransaction() const;
void commit() const;
@@ -109,7 +110,7 @@ public:
cv::Mat load2DMap(float & xMin, float & yMin, float & cellSize) const;
void saveOptimizedMesh(
const cv::Mat & cloud,
const std::vector<std::vector<std::vector<unsigned int> > > & polygons = std::vector<std::vector<std::vector<unsigned int> > >(), // Textures -> polygons -> vertices
const std::vector<std::vector<std::vector<RTABMAP_PCL_INDEX> > > & polygons = std::vector<std::vector<std::vector<RTABMAP_PCL_INDEX> > >(), // Textures -> polygons -> vertices
#if PCL_VERSION_COMPARE(>=, 1, 8, 0)
const std::vector<std::vector<Eigen::Vector2f, Eigen::aligned_allocator<Eigen::Vector2f> > > & texCoords = std::vector<std::vector<Eigen::Vector2f, Eigen::aligned_allocator<Eigen::Vector2f> > >(), // Textures -> uv coords for each vertex of the polygons
#else
@@ -117,7 +118,7 @@ public:
#endif
const cv::Mat & textures = cv::Mat()) const; // concatenated textures (assuming square textures with all same size);
cv::Mat loadOptimizedMesh(
std::vector<std::vector<std::vector<unsigned int> > > * polygons = 0,
std::vector<std::vector<std::vector<RTABMAP_PCL_INDEX> > > * polygons = 0,
#if PCL_VERSION_COMPARE(>=, 1, 8, 0)
std::vector<std::vector<Eigen::Vector2f, Eigen::aligned_allocator<Eigen::Vector2f> > > * texCoords = 0,
#else
@@ -247,7 +248,7 @@ protected:
virtual cv::Mat load2DMapQuery(float & xMin, float & yMin, float & cellSize) const = 0;
virtual void saveOptimizedMeshQuery(
const cv::Mat & cloud,
const std::vector<std::vector<std::vector<unsigned int> > > & polygons,
const std::vector<std::vector<std::vector<RTABMAP_PCL_INDEX> > > & polygons,
#if PCL_VERSION_COMPARE(>=, 1, 8, 0)
const std::vector<std::vector<Eigen::Vector2f, Eigen::aligned_allocator<Eigen::Vector2f> > > & texCoords,
#else
@@ -255,7 +256,7 @@ protected:
#endif
const cv::Mat & textures) const = 0;
virtual cv::Mat loadOptimizedMeshQuery(
std::vector<std::vector<std::vector<unsigned int> > > * polygons,
std::vector<std::vector<std::vector<RTABMAP_PCL_INDEX> > > * polygons,
#if PCL_VERSION_COMPARE(>=, 1, 8, 0)
std::vector<std::vector<Eigen::Vector2f, Eigen::aligned_allocator<Eigen::Vector2f> > > * texCoords,
#else
@@ -300,6 +301,7 @@ private:
USemaphore _addSem;
double _emptyTrashesTime;
std::string _url;
std::string _targetVersion;
bool _timestampUpdate;
};
@@ -113,7 +113,7 @@ protected:
virtual cv::Mat load2DMapQuery(float & xMin, float & yMin, float & cellSize) const;
virtual void saveOptimizedMeshQuery(
const cv::Mat & cloud,
const std::vector<std::vector<std::vector<unsigned int> > > & polygons,
const std::vector<std::vector<std::vector<RTABMAP_PCL_INDEX> > > & polygons,
#if PCL_VERSION_COMPARE(>=, 1, 8, 0)
const std::vector<std::vector<Eigen::Vector2f, Eigen::aligned_allocator<Eigen::Vector2f> > > & texCoords,
#else
@@ -121,7 +121,7 @@ protected:
#endif
const cv::Mat & textures) const;
virtual cv::Mat loadOptimizedMeshQuery(
std::vector<std::vector<std::vector<unsigned int> > > * polygons,
std::vector<std::vector<std::vector<RTABMAP_PCL_INDEX> > > * polygons,
#if PCL_VERSION_COMPARE(>=, 1, 8, 0)
std::vector<std::vector<Eigen::Vector2f, Eigen::aligned_allocator<Eigen::Vector2f> > > * texCoords,
#else
+61 -1
View File
@@ -61,6 +61,7 @@ typedef cv::gpu::FAST_GPU CV_FAST_GPU;
namespace cv{
namespace xfeatures2d {
class FREAK;
class DAISY;
class BriefDescriptorExtractor;
#if CV_MAJOR_VERSION < 3 || (CV_MAJOR_VERSION == 4 && CV_MINOR_VERSION <= 3) || (CV_MAJOR_VERSION == 3 && (CV_MINOR_VERSION < 4 || (CV_MINOR_VERSION==4 && CV_SUBMINOR_VERSION<11)))
class SIFT;
@@ -81,6 +82,7 @@ typedef cv::SIFT CV_SIFT; // SIFT is back in features2d since 4.4.0 / 3.4.11
typedef cv::xfeatures2d::SURF CV_SURF;
typedef cv::FastFeatureDetector CV_FAST;
typedef cv::xfeatures2d::FREAK CV_FREAK;
typedef cv::xfeatures2d::DAISY CV_DAISY;
typedef cv::GFTTDetector CV_GFTT;
typedef cv::xfeatures2d::BriefDescriptorExtractor CV_BRIEF;
typedef cv::BRISK CV_BRISK;
@@ -116,7 +118,11 @@ public:
kFeatureKaze=9, //new 0.13.2
kFeatureOrbOctree=10, //new 0.19.2
kFeatureSuperPointTorch=11, //new 0.19.7
kFeatureSurfFreak=12}; //new 0.20.4
kFeatureSurfFreak=12, //new 0.20.4
kFeatureGfttDaisy=13, //new 0.20.6
kFeatureSurfDaisy=14, //new 0.20.6
kFeaturePyDetector=15}; //new 0.20.8
static std::string typeName(Type type)
{
switch(type){
@@ -146,6 +152,10 @@ public:
return "SUPERPOINT";
case kFeatureSurfFreak:
return "SURF+Freak";
case kFeatureGfttDaisy:
return "GFTT+Daisy";
case kFeatureSurfDaisy:
return "SURF+Daisy";
default:
return "Unknown";
}
@@ -563,6 +573,8 @@ private:
private:
float scaleFactor_;
int nLevels_;
int patchSize_;
int edgeThreshold_;
int fastThreshold_;
int fastMinThreshold_;
@@ -593,6 +605,54 @@ private:
bool cuda_;
};
//GFTT_DAISY
class RTABMAP_EXP GFTT_DAISY : public GFTT
{
public:
GFTT_DAISY(const ParametersMap & parameters = ParametersMap());
virtual ~GFTT_DAISY();
virtual void parseParameters(const ParametersMap & parameters);
virtual Feature2D::Type getType() const {return kFeatureGfttDaisy;}
private:
virtual cv::Mat generateDescriptorsImpl(const cv::Mat & image, std::vector<cv::KeyPoint> & keypoints) const;
private:
bool orientationNormalized_;
bool scaleNormalized_;
float patternScale_;
int nOctaves_;
#if CV_MAJOR_VERSION > 2
cv::Ptr<CV_DAISY> _daisy;
#endif
};
//SURF_DAISY
class RTABMAP_EXP SURF_DAISY : public SURF
{
public:
SURF_DAISY(const ParametersMap & parameters = ParametersMap());
virtual ~SURF_DAISY();
virtual void parseParameters(const ParametersMap & parameters);
virtual Feature2D::Type getType() const {return kFeatureSurfDaisy;}
private:
virtual cv::Mat generateDescriptorsImpl(const cv::Mat & image, std::vector<cv::KeyPoint> & keypoints) const;
private:
bool orientationNormalized_;
bool scaleNormalized_;
float patternScale_;
int nOctaves_;
#if CV_MAJOR_VERSION > 2
cv::Ptr<CV_DAISY> _daisy;
#endif
};
}
#endif /* FEATURES2D_H_ */
+6 -2
View File
@@ -35,6 +35,7 @@ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#include <rtabmap/core/Parameters.h>
#include <rtabmap/core/Link.h>
#include <rtabmap/core/GPS.h>
#include <rtabmap/core/CameraModel.h>
namespace rtabmap {
class Memory;
@@ -55,10 +56,10 @@ namespace graph {
bool RTABMAP_EXP importPoses(
const std::string & filePath,
int format, // 0=Raw, 1=RGBD-SLAM motion capture (10=without change of coordinate frame), 2=KITTI, 3=TORO, 4=g2o, 5=NewCollege(t,x,y), 6=Malaga Urban GPS, 7=St Lucia INS, 8=Karlsruhe
int format, // 0=Raw, 1=RGBD-SLAM motion capture (10=without change of coordinate frame), 2=KITTI, 3=TORO, 4=g2o, 5=NewCollege(t,x,y), 6=Malaga Urban GPS, 7=St Lucia INS, 8=Karlsruhe, 9=EuRoC MAV
std::map<int, Transform> & poses,
std::multimap<int, Link> * constraints = 0, // optional for formats 3 and 4
std::map<int, double> * stamps = 0); // optional for format 1
std::map<int, double> * stamps = 0); // optional for format 1 and 9
bool RTABMAP_EXP exportGPS(
const std::string & filePath,
@@ -326,6 +327,9 @@ std::list<std::map<int, Transform> > RTABMAP_EXP getPaths(
std::map<int, Transform> poses,
const std::multimap<int, Link> & links);
void RTABMAP_EXP computeMinMax(const std::map<int, Transform> & poses,
cv::Vec3f & min,
cv::Vec3f & max);
} /* namespace graph */
+5 -1
View File
@@ -9,7 +9,8 @@
#define IMU_H_
#include <opencv2/core/core.hpp>
#include <rtabmap/utilite/ULogger.h>
#include <rtabmap/utilite/UEvent.h>
#include <rtabmap/core/Transform.h>
namespace rtabmap {
@@ -60,6 +61,9 @@ public:
const Transform & localTransform() const {return localTransform_;}
// apply local transform rotation to data, and set Identity rotation for local transform
void convertToBaseFrame();
bool empty() const
{
return localTransform_.isNull();
+36
View File
@@ -71,11 +71,35 @@ public:
public:
LaserScan();
LaserScan(const LaserScan & data,
int maxPoints,
float maxRange,
const Transform & localTransform = Transform::getIdentity());
RTABMAP_DEPRECATED(LaserScan(const LaserScan & data,
int maxPoints,
float maxRange,
Format format,
const Transform & localTransform = Transform::getIdentity()), "Use version without \"format\" argument.");
LaserScan(const cv::Mat & data,
int maxPoints,
float maxRange,
Format format,
const Transform & localTransform = Transform::getIdentity());
RTABMAP_DEPRECATED(LaserScan(const LaserScan & data,
Format format,
float minRange,
float maxRange,
float angleMin,
float angleMax,
float angleIncrement,
const Transform & localTransform = Transform::getIdentity()), "Use version without \"format\" argument.");
LaserScan(const LaserScan & data,
float minRange,
float maxRange,
float angleMin,
float angleMax,
float angleIncrement,
const Transform & localTransform = Transform::getIdentity());
LaserScan(const cv::Mat & data,
Format format,
float minRange,
@@ -97,6 +121,7 @@ public:
float angleIncrement() const {return angleIncrement_;}
Transform localTransform() const {return localTransform_;}
bool empty() const {return data_.empty();}
bool isEmpty() const {return data_.empty();}
int size() const {return data_.cols;}
int dataType() const {return data_.type();}
@@ -113,6 +138,17 @@ public:
void clear() {data_ = cv::Mat();}
private:
void init(const cv::Mat & data,
Format format,
float minRange,
float maxRange,
float angleMin,
float angleMax,
float angleIncrement,
int maxPoints,
const Transform & localTransform = Transform::getIdentity());
private:
cv::Mat data_;
Format format_;
@@ -50,6 +50,8 @@ private:
cv::Ptr<cv::aruco::DetectorParameters> detectorParams_;
float markerLength_;
float maxDepthError_;
float maxRange_;
float minRange_;
int dictionaryId_;
cv::Ptr<cv::aruco::Dictionary> dictionary_;
#endif
+2 -2
View File
@@ -102,7 +102,7 @@ public:
cv::Mat load2DMap(float & xMin, float & yMin, float & cellSize) const;
void saveOptimizedMesh(
const cv::Mat & cloud,
const std::vector<std::vector<std::vector<unsigned int> > > & polygons = std::vector<std::vector<std::vector<unsigned int> > >(), // Textures -> polygons -> vertices
const std::vector<std::vector<std::vector<RTABMAP_PCL_INDEX> > > & polygons = std::vector<std::vector<std::vector<RTABMAP_PCL_INDEX> > >(), // Textures -> polygons -> vertices
#if PCL_VERSION_COMPARE(>=, 1, 8, 0)
const std::vector<std::vector<Eigen::Vector2f, Eigen::aligned_allocator<Eigen::Vector2f> > > & texCoords = std::vector<std::vector<Eigen::Vector2f, Eigen::aligned_allocator<Eigen::Vector2f> > >(), // Textures -> uv coords for each vertex of the polygons
#else
@@ -110,7 +110,7 @@ public:
#endif
const cv::Mat & textures = cv::Mat()) const; // concatenated textures (assuming square textures with all same size)
cv::Mat loadOptimizedMesh(
std::vector<std::vector<std::vector<unsigned int> > > * polygons = 0,
std::vector<std::vector<std::vector<RTABMAP_PCL_INDEX> > > * polygons = 0,
#if PCL_VERSION_COMPARE(>=, 1, 8, 0)
std::vector<std::vector<Eigen::Vector2f, Eigen::aligned_allocator<Eigen::Vector2f> > > * texCoords = 0,
#else
-3
View File
@@ -168,9 +168,6 @@ class RtabmapColorOcTree : public octomap::OccupancyOcTreeBase <RtabmapColorOcTr
};
class RTABMAP_EXP OctoMap {
public:
static void HSVtoRGB(float *r, float *g, float *b, float h, float s, float v);
public:
OctoMap(const ParametersMap & parameters);
OctoMap(float cellSize = 0.1f, float occupancyThr = 0.5f, bool fullUpdate = false, float updateError=0.01f);
+2 -2
View File
@@ -49,7 +49,7 @@ public:
kTypeFovis = 2,
kTypeViso2 = 3,
kTypeDVO = 4,
kTypeORBSLAM2 = 5,
kTypeORBSLAM = 5,
kTypeOkvis = 6,
kTypeLOAM = 7,
kTypeMSCKF = 8,
@@ -67,7 +67,7 @@ public:
virtual void reset(const Transform & initialPose = Transform::getIdentity());
virtual Odometry::Type getType() = 0;
virtual bool canProcessRawImages() const {return false;}
virtual bool canProcessIMU() const {return false;}
virtual bool canProcessAsyncIMU() const {return false;}
//getters
const Transform & getPose() const {return _pose;}
+3 -1
View File
@@ -84,6 +84,7 @@ public:
output.transformFiltered = transformFiltered;
output.transformGroundTruth = transformGroundTruth;
output.guessVelocity = guessVelocity;
output.guess = guess;
output.distanceTravelled = distanceTravelled;
output.memoryUsage = memoryUsage;
output.gravityRollError = gravityRollError;
@@ -111,7 +112,8 @@ public:
Transform transform;
Transform transformFiltered;
Transform transformGroundTruth;
Transform guessVelocity;
Transform guessVelocity; // deprecated, will be removed. Use guess and interval instead.
Transform guess;
float distanceTravelled;
int memoryUsage; //MB
double gravityRollError;
+47
View File
@@ -0,0 +1,47 @@
/*
Copyright (c) 2010-2021, Mathieu Labbe - IntRoLab - Universite de Sherbrooke
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
* Neither the name of the Universite de Sherbrooke nor the
names of its contributors may be used to endorse or promote products
derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY
DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef CORELIB_INCLUDE_RTABMAP_CORE_PDALWRITER_H_
#define CORELIB_INCLUDE_RTABMAP_CORE_PDALWRITER_H_
#include <pcl/point_cloud.h>
#include <pcl/point_types.h>
namespace rtabmap {
std::string getPDALSupportedWriters();
int savePDALFile(const std::string & filePath, const pcl::PointCloud<pcl::PointXYZ> & cloud, const std::vector<int> & cameraIds = std::vector<int>(), bool binary = false);
int savePDALFile(const std::string & filePath, const pcl::PointCloud<pcl::PointXYZRGB> & cloud, const std::vector<int> & cameraIds = std::vector<int>(), bool binary = false);
int savePDALFile(const std::string & filePath, const pcl::PointCloud<pcl::PointXYZRGBNormal> & cloud, const std::vector<int> & cameraIds = std::vector<int>(), bool binary = false);
int savePDALFile(const std::string & filePath, const pcl::PointCloud<pcl::PointXYZI> & cloud, const std::vector<int> & cameraIds = std::vector<int>(), bool binary = false);
int savePDALFile(const std::string & filePath, const pcl::PointCloud<pcl::PointXYZINormal> & cloud, const std::vector<int> & cameraIds = std::vector<int>(), bool binary = false);
}
#endif /* CORELIB_INCLUDE_RTABMAP_CORE_PDALWRITER_H_ */
+62 -43
View File
@@ -244,9 +244,9 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(Kp, NndrRatio, float, 0.8, "NNDR ratio (A matching pair is detected, if its distance is closer than X times the distance of the second nearest neighbor.)");
#if CV_MAJOR_VERSION > 2 && !defined(HAVE_OPENCV_XFEATURES2D)
// OpenCV>2 without xFeatures2D module doesn't have BRIEF
RTABMAP_PARAM(Kp, DetectorStrategy, int, 8, "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 Torch 12=SURF/FREAK.");
RTABMAP_PARAM(Kp, DetectorStrategy, int, 8, "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 12=SURF/FREAK 13=GFTT/DAISY 14=SURF/DAISY 15=PyDetector");
#else
RTABMAP_PARAM(Kp, DetectorStrategy, int, 6, "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 Torch 12=SURF/FREAK.");
RTABMAP_PARAM(Kp, DetectorStrategy, int, 6, "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 12=SURF/FREAK 13=GFTT/DAISY 14=SURF/DAISY 15=PyDetector");
#endif
RTABMAP_PARAM(Kp, TfIdfLikelihoodUsed, bool, true, "Use of the td-idf strategy to compute the likelihood.");
RTABMAP_PARAM(Kp, Parallelized, bool, true, "If the dictionary update and signature creation were parallelized.");
@@ -265,6 +265,7 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(DbSqlite3, JournalMode, int, 3, "0=DELETE, 1=TRUNCATE, 2=PERSIST, 3=MEMORY, 4=OFF (see sqlite3 doc : \"PRAGMA journal_mode\")");
RTABMAP_PARAM(DbSqlite3, Synchronous, int, 0, "0=OFF, 1=NORMAL, 2=FULL (see sqlite3 doc : \"PRAGMA synchronous\")");
RTABMAP_PARAM(DbSqlite3, TempStore, int, 2, "0=DEFAULT, 1=FILE, 2=MEMORY (see sqlite3 doc : \"PRAGMA temp_store\")");
RTABMAP_PARAM_STR(Db, TargetVersion, "", "Target database version for backward compatibility purpose. Only Major and minor versions are used and should be set (e.g., 0.19 vs 0.20 or 1.0 vs 2.0). Patch version is ignored (e.g., 0.20.1 and 0.20.3 will generate a 0.20 database).");
// Keypoints descriptors/detectors
RTABMAP_PARAM(SURF, Extended, bool, false, "Extended descriptor flag (true - use extended 128-element descriptors; false - use 64-element descriptors).");
@@ -295,14 +296,14 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(FAST, CV, int, 0, "Enable FastCV implementation if non-zero (and RTAB-Map is built with FastCV support). Values should be 9 and 10.");
RTABMAP_PARAM(GFTT, QualityLevel, double, 0.001, "");
RTABMAP_PARAM(GFTT, MinDistance, double, 3, "");
RTABMAP_PARAM(GFTT, MinDistance, double, 7, "");
RTABMAP_PARAM(GFTT, BlockSize, int, 3, "");
RTABMAP_PARAM(GFTT, UseHarrisDetector, bool, false, "");
RTABMAP_PARAM(GFTT, K, double, 0.04, "");
RTABMAP_PARAM(ORB, ScaleFactor, float, 1.2, "Pyramid decimation ratio, greater than 1. scaleFactor==2 means the classical pyramid, where each next level has 4x less pixels than the previous, but such a big scale factor will degrade feature matching scores dramatically. On the other hand, too close to 1 scale factor will mean that to cover certain scale range you will need more pyramid levels and so the speed will suffer.");
RTABMAP_PARAM(ORB, NLevels, int, 8, "The number of pyramid levels. The smallest level will have linear size equal to input_image_linear_size/pow(scaleFactor, nlevels).");
RTABMAP_PARAM(ORB, EdgeThreshold, int, 31, "This is size of the border where the features are not detected. It should roughly match the patchSize parameter.");
RTABMAP_PARAM(ORB, ScaleFactor, float, 2, "Pyramid decimation ratio, greater than 1. scaleFactor==2 means the classical pyramid, where each next level has 4x less pixels than the previous, but such a big scale factor will degrade feature matching scores dramatically. On the other hand, too close to 1 scale factor will mean that to cover certain scale range you will need more pyramid levels and so the speed will suffer.");
RTABMAP_PARAM(ORB, NLevels, int, 3, "The number of pyramid levels. The smallest level will have linear size equal to input_image_linear_size/pow(scaleFactor, nlevels).");
RTABMAP_PARAM(ORB, EdgeThreshold, int, 19, "This is size of the border where the features are not detected. It should roughly match the patchSize parameter.");
RTABMAP_PARAM(ORB, FirstLevel, int, 0, "It should be 0 in the current implementation.");
RTABMAP_PARAM(ORB, WTA_K, int, 2, "The number of points that produce each element of the oriented BRIEF descriptor. The default value 2 means the BRIEF where we take a random point pair and compare their brightnesses, so we get 0/1 response. Other possible values are 3 and 4. For example, 3 means that we take 3 random points (of course, those point coordinates are random, but they are generated from the pre-defined seed, so each element of BRIEF descriptor is computed deterministically from the pixel rectangle), find point of maximum brightness and output index of the winner (0, 1 or 2). Such output will occupy 2 bits, and therefore it will need a special variant of Hamming distance, denoted as NORM_HAMMING2 (2 bits per bin). When WTA_K=4, we take 4 random points to compute each bin (that will also occupy 2 bits with possible values 0, 1, 2 or 3).");
RTABMAP_PARAM(ORB, ScoreType, int, 0, "The default HARRIS_SCORE=0 means that Harris algorithm is used to rank features (the score is written to KeyPoint::score and is used to retain best nfeatures features); FAST_SCORE=1 is alternative value of the parameter that produces slightly less stable keypoints, but it is a little faster to compute.");
@@ -331,6 +332,9 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(SuperPoint, NMSRadius, int, 4, uFormat("[%s=true] Minimum distance (pixels) between keypoints.", kSuperPointNMS().c_str()));
RTABMAP_PARAM(SuperPoint, Cuda, bool, true, "Use Cuda device for Torch, otherwise CPU device is used by default.");
RTABMAP_PARAM_STR(PyDetector, Path, "", "Path to python script file (see available ones in rtabmap/corelib/src/python/*). See the header to see where the script should be copied.");
RTABMAP_PARAM(PyDetector, Cuda, bool, true, "Use cuda.");
// BayesFilter
RTABMAP_PARAM(Bayes, VirtualPlacePriorThr, float, 0.9, "Virtual place prior");
RTABMAP_PARAM_STR(Bayes, PredictionLC, "0.1 0.36 0.30 0.16 0.062 0.0151 0.00255 0.000324 2.5e-05 1.3e-06 4.8e-08 1.2e-09 1.9e-11 2.2e-13 1.7e-15 8.5e-18 2.9e-20 6.9e-23", "Prediction of loop closures (Gaussian-like, here with sigma=1.6) - Format: {VirtualPlaceProb, LoopClosureProb, NeighborLvl1, NeighborLvl2, ...}.");
@@ -343,7 +347,7 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(VhEp, RansacParam2, float, 0.99, "Fundamental matrix (see cvFindFundamentalMat()): Performance of RANSAC.");
// RGB-D SLAM
RTABMAP_PARAM(RGBD, Enabled, bool, true, "");
RTABMAP_PARAM(RGBD, Enabled, bool, true, "Activate metric SLAM. If set to false, classic RTAB-Map loop closure detection is done using only images and without any metric information.");
RTABMAP_PARAM(RGBD, LinearUpdate, float, 0.1, "Minimum linear displacement (m) to update the map. Rehearsal is done prior to this, so weights are still updated.");
RTABMAP_PARAM(RGBD, AngularUpdate, float, 0.1, "Minimum angular displacement (rad) to update the map. Rehearsal is done prior to this, so weights are still updated.");
RTABMAP_PARAM(RGBD, LinearSpeedUpdate, float, 0.0, "Maximum linear speed (m/s) to update the map (0 means not limit).");
@@ -352,7 +356,7 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(RGBD, OptimizeFromGraphEnd, bool, false, "Optimize graph from the newest node. If false, the graph is optimized from the oldest node of the current graph (this adds an overhead computation to detect to oldest node of the current graph, but it can be useful to preserve the map referential from the oldest node). Warning when set to false: when some nodes are transferred, the first referential of the local map may change, resulting in momentary changes in robot/map position (which are annoying in teleoperation).");
RTABMAP_PARAM(RGBD, OptimizeMaxError, float, 3.0, uFormat("Reject loop closures if optimization error ratio is greater than this value (0=disabled). Ratio is computed as absolute error over standard deviation of each link. This will help to detect when a wrong loop closure is added to the graph. Not compatible with \"%s\" if enabled.", kOptimizerRobust().c_str()));
RTABMAP_PARAM(RGBD, MaxLoopClosureDistance, float, 0.0, "Reject loop closures/localizations if the distance from the map is over this distance (0=disabled).");
RTABMAP_PARAM(RGBD, SavedLocalizationIgnored, bool, false, "Ignore last saved localization pose from previous session. If true, RTAB-Map won't assume it is restarting from the same place than where it shut down previously.");
RTABMAP_PARAM(RGBD, StartAtOrigin, bool, false, uFormat("If true, rtabmap will assume the robot is starting from origin of the map. If false, rtabmap will assume the robot is restarting from the last saved localization pose from previous session (the place where it shut down previously). Used only in localization mode (%s=false).", kMemIncrementalMemory().c_str()));
RTABMAP_PARAM(RGBD, GoalReachedRadius, float, 0.5, "Goal reached radius (m).");
RTABMAP_PARAM(RGBD, PlanStuckIterations, int, 0, "Mark the current goal node on the path as unreachable if it is not updated after X iterations (0=disabled). If all upcoming nodes on the path are unreachabled, the plan fails.");
RTABMAP_PARAM(RGBD, PlanLinearVelocity, float, 0, "Linear velocity (m/sec) used to compute path weights.");
@@ -361,8 +365,9 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(RGBD, MaxLocalRetrieved, unsigned int, 2, "Maximum local locations retrieved (0=disabled) near the current pose in the local map or on the current planned path (those on the planned path have priority).");
RTABMAP_PARAM(RGBD, LocalRadius, float, 10, "Local radius (m) for nodes selection in the local map. This parameter is used in some approaches about the local map management.");
RTABMAP_PARAM(RGBD, LocalImmunizationRatio, float, 0.25, "Ratio of working memory for which local nodes are immunized from transfer.");
RTABMAP_PARAM(RGBD, ScanMatchingIdsSavedInLinks, bool, true, "Save scan matching IDs in link's user data.");
RTABMAP_PARAM(RGBD, ScanMatchingIdsSavedInLinks, bool, true, "Save scan matching IDs from one-to-many proximity detection in link's user data.");
RTABMAP_PARAM(RGBD, NeighborLinkRefining, bool, false, uFormat("When a new node is added to the graph, the transformation of its neighbor link to the previous node is refined using registration approach selected (%s).", kRegStrategy().c_str()));
RTABMAP_PARAM(RGBD, LoopClosureIdentityGuess, bool, false, uFormat("Use Identity matrix as guess when computing loop closure transform, otherwise no guess is used, thus assuming that registration strategy selected (%s) can deal with transformation estimation without guess.", kRegStrategy().c_str()));
RTABMAP_PARAM(RGBD, LoopClosureReextractFeatures, bool, false, "Extract features even if there are some already in the nodes.");
RTABMAP_PARAM(RGBD, LocalBundleOnLoopClosure, bool, false, "Do local bundle adjustment with neighborhood of the loop closure.");
RTABMAP_PARAM(RGBD, CreateOccupancyGrid, bool, false, "Create local occupancy grid maps. See \"Grid\" group for parameters.");
@@ -374,12 +379,12 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(RGBD, ProximityByTime, bool, false, "Detection over all locations in STM.");
RTABMAP_PARAM(RGBD, ProximityBySpace, bool, true, "Detection over locations (in Working Memory) near in space.");
RTABMAP_PARAM(RGBD, ProximityMaxGraphDepth, int, 50, "Maximum depth from the current/last loop closure location and the local loop closure hypotheses. Set 0 to ignore.");
RTABMAP_PARAM(RGBD, ProximityMaxPaths, int, 3, "Maximum paths compared (from the most recent) for proximity detection by space. 0 means no limit.");
RTABMAP_PARAM(RGBD, ProximityPathFilteringRadius, float, 1, "Path filtering radius to reduce the number of nodes to compare in a path. A path should also be inside that radius to be considered for proximity detection.");
RTABMAP_PARAM(RGBD, ProximityPathMaxNeighbors, int, 0, "Maximum neighbor nodes compared on each path. Set to 0 to disable merging the laser scans.");
RTABMAP_PARAM(RGBD, ProximityPathRawPosesUsed, bool, true, "When comparing to a local path, merge the scan using the odometry poses (with neighbor link optimizations) instead of the ones in the optimized local graph.");
RTABMAP_PARAM(RGBD, ProximityAngle, float, 45, "Maximum angle (degrees) for visual proximity detection.");
RTABMAP_PARAM(RGBD, ProximityOdomGuess, bool, false, "Use odometry as motion guess for visual proximity detection.");
RTABMAP_PARAM(RGBD, ProximityMaxPaths, int, 3, "Maximum paths compared (from the most recent) for proximity detection. 0 means no limit.");
RTABMAP_PARAM(RGBD, ProximityPathFilteringRadius, float, 1, "Path filtering radius to reduce the number of nodes to compare in a path in one-to-many proximity detection. The nearest node in a path should be inside that radius to be considered for one-to-one proximity detection.");
RTABMAP_PARAM(RGBD, ProximityPathMaxNeighbors, int, 0, "Maximum neighbor nodes compared on each path for one-to-many proximity detection. Set to 0 to disable one-to-many proximity detection (by merging the laser scans).");
RTABMAP_PARAM(RGBD, ProximityPathRawPosesUsed, bool, true, "When comparing to a local path for one-to-many proximity detection, merge the scans using the odometry poses (with neighbor link optimizations) instead of the ones in the optimized local graph.");
RTABMAP_PARAM(RGBD, ProximityAngle, float, 45, "Maximum angle (degrees) for one-to-one proximity detection.");
RTABMAP_PARAM(RGBD, ProximityOdomGuess, bool, false, "Use odometry as motion guess for one-to-one proximity detection.");
// Graph optimization
#ifdef RTABMAP_GTSAM
@@ -407,9 +412,13 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(Optimizer, Robust, bool, false, uFormat("Robust graph optimization using Vertigo (only work for g2o and GTSAM optimization strategies). Not compatible with \"%s\" if enabled.", kRGBDOptimizeMaxError().c_str()));
RTABMAP_PARAM(Optimizer, PriorsIgnored, bool, true, "Ignore prior constraints (global pose or GPS) while optimizing. Currently only g2o and gtsam optimization supports this.");
RTABMAP_PARAM(Optimizer, LandmarksIgnored, bool, false, "Ignore landmark constraints while optimizing. Currently only g2o and gtsam optimization supports this.");
#if defined(RTABMAP_G2O) || defined(RTABMAP_GTSAM)
RTABMAP_PARAM(Optimizer, GravitySigma, float, 0.3, uFormat("Gravity sigma value (>=0, typically between 0.1 and 0.3). Optimization is done while preserving gravity orientation of the poses. This should be used only with visual/lidar inertial odometry approaches, for which we assume that all odometry poses are aligned with gravity. Set to 0 to disable gravity constraints. Currently supported only with g2o and GTSAM optimization strategies (see %s).", kOptimizerStrategy().c_str()));
#else
RTABMAP_PARAM(Optimizer, GravitySigma, float, 0.0, uFormat("Gravity sigma value (>=0, typically between 0.1 and 0.3). Optimization is done while preserving gravity orientation of the poses. This should be used only with visual/lidar inertial odometry approaches, for which we assume that all odometry poses are aligned with gravity. Set to 0 to disable gravity constraints. Currently supported only with g2o and GTSAM optimization strategies (see %s).", kOptimizerStrategy().c_str()));
#endif
#ifdef RTABMAP_ORB_SLAM2
#ifdef RTABMAP_ORB_SLAM
RTABMAP_PARAM(g2o, Solver, int, 3, "0=csparse 1=pcg 2=cholmod 3=Eigen");
#else
RTABMAP_PARAM(g2o, Solver, int, 0, "0=csparse 1=pcg 2=cholmod 3=Eigen");
@@ -451,7 +460,7 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(OdomF2M, ScanSubtractAngle, float, 45, uFormat("[Geometry] Max angle (degrees) used to filter points of a new added scan to local map (when \"%s\">0). 0 means any angle.", kOdomF2MScanSubtractRadius().c_str()).c_str());
RTABMAP_PARAM(OdomF2M, ScanRange, float, 0, "[Geometry] Distance Range used to filter points of local map (when > 0). 0 means local map is updated using time and not range.");
RTABMAP_PARAM(OdomF2M, ValidDepthRatio, float, 0.75, "If a new frame has points without valid depth, they are added to local feature map only if points with valid depth on total points is over this ratio. Setting to 1 means no points without valid depth are added to local feature map.");
#if defined(RTABMAP_G2O) || defined(RTABMAP_ORB_SLAM2)
#if defined(RTABMAP_G2O) || defined(RTABMAP_ORB_SLAM)
RTABMAP_PARAM(OdomF2M, BundleAdjustment, int, 1, "Local bundle adjustment: 0=disabled, 1=g2o, 2=cvsba, 3=Ceres.");
#else
RTABMAP_PARAM(OdomF2M, BundleAdjustment, int, 0, "Local bundle adjustment: 0=disabled, 1=g2o, 2=cvsba, 3=Ceres.");
@@ -512,12 +521,12 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(OdomViso2, BucketHeight, double, 50, "Height of bucket.");
// Odometry ORB_SLAM2
RTABMAP_PARAM_STR(OdomORBSLAM2, VocPath, "", "Path to ORB vocabulary (*.txt).");
RTABMAP_PARAM(OdomORBSLAM2, Bf, double, 0.076, "Fake IR projector baseline (m) used only when stereo is not used.");
RTABMAP_PARAM(OdomORBSLAM2, ThDepth, double, 40.0, "Close/Far threshold. Baseline times.");
RTABMAP_PARAM(OdomORBSLAM2, Fps, float, 0.0, "Camera FPS.");
RTABMAP_PARAM(OdomORBSLAM2, MaxFeatures, int, 1000, "Maximum ORB features extracted per frame.");
RTABMAP_PARAM(OdomORBSLAM2, MapSize, int, 3000, "Maximum size of the feature map (0 means infinite).");
RTABMAP_PARAM_STR(OdomORBSLAM, VocPath, "", "Path to ORB vocabulary (*.txt).");
RTABMAP_PARAM(OdomORBSLAM, Bf, double, 0.076, "Fake IR projector baseline (m) used only when stereo is not used.");
RTABMAP_PARAM(OdomORBSLAM, ThDepth, double, 40.0, "Close/Far threshold. Baseline times.");
RTABMAP_PARAM(OdomORBSLAM, Fps, float, 0.0, "Camera FPS.");
RTABMAP_PARAM(OdomORBSLAM, MaxFeatures, int, 1000, "Maximum ORB features extracted per frame.");
RTABMAP_PARAM(OdomORBSLAM, MapSize, int, 3000, "Maximum size of the feature map (0 means infinite).");
// Odometry OKVIS
RTABMAP_PARAM_STR(OdomOKVIS, ConfigPath, "", "Path of OKVIS config file.");
@@ -573,7 +582,7 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(Vis, RefineIterations, int, 5, uFormat("[%s = 0] Number of iterations used to refine the transformation found by RANSAC. 0 means that the transformation is not refined.", kVisEstimationType().c_str()));
RTABMAP_PARAM(Vis, PnPReprojError, float, 2, uFormat("[%s = 1] PnP reprojection error.", kVisEstimationType().c_str()));
RTABMAP_PARAM(Vis, PnPFlags, int, 0, uFormat("[%s = 1] PnP flags: 0=Iterative, 1=EPNP, 2=P3P", kVisEstimationType().c_str()));
#if defined(RTABMAP_G2O) || defined(RTABMAP_ORB_SLAM2)
#if defined(RTABMAP_G2O) || defined(RTABMAP_ORB_SLAM)
RTABMAP_PARAM(Vis, PnPRefineIterations, int, 0, uFormat("[%s = 1] Refine iterations. Set to 0 if \"%s\" is also used.", kVisEstimationType().c_str(), kVisBundleAdjustment().c_str()));
#else
RTABMAP_PARAM(Vis, PnPRefineIterations, int, 1, uFormat("[%s = 1] Refine iterations. Set to 0 if \"%s\" is also used.", kVisEstimationType().c_str(), kVisBundleAdjustment().c_str()));
@@ -587,9 +596,9 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(Vis, Iterations, int, 300, "Maximum iterations to compute the transform.");
#if CV_MAJOR_VERSION > 2 && !defined(HAVE_OPENCV_XFEATURES2D)
// OpenCV>2 without xFeatures2D module doesn't have BRIEF
RTABMAP_PARAM(Vis, FeatureType, int, 8, "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 Torch 12=SURF/FREAK.");
RTABMAP_PARAM(Vis, FeatureType, int, 8, "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 12=SURF/FREAK 13=GFTT/DAISY 14=SURF/DAISY 15=PyDetector");
#else
RTABMAP_PARAM(Vis, FeatureType, int, 6, "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 Torch 12=SURF/FREAK.");
RTABMAP_PARAM(Vis, FeatureType, int, 6, "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 12=SURF/FREAK 13=GFTT/DAISY 14=SURF/DAISY 15=PyDetector");
#endif
RTABMAP_PARAM(Vis, MaxFeatures, int, 1000, "0 no limits.");
RTABMAP_PARAM(Vis, MaxDepth, float, 0, "Max depth of the features (0 means no limit).");
@@ -603,21 +612,21 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(Vis, GridCols, int, 1, uFormat("Number of columns of the grid used to extract uniformly \"%s / grid cells\" features from each cell.", kVisMaxFeatures().c_str()));
RTABMAP_PARAM(Vis, CorType, int, 0, "Correspondences computation approach: 0=Features Matching, 1=Optical Flow");
RTABMAP_PARAM(Vis, CorNNType, int, 1, uFormat("[%s=0] kNNFlannNaive=0, kNNFlannKdTree=1, kNNFlannLSH=2, kNNBruteForce=3, kNNBruteForceGPU=4, BruteForceCrossCheck=5, SuperGlue=6, GMS=7. Used for features matching approach.", kVisCorType().c_str()));
RTABMAP_PARAM(Vis, CorNNDR, float, 0.6, uFormat("[%s=0] NNDR: nearest neighbor distance ratio. Used for knn features matching approach.", kVisCorType().c_str()));
RTABMAP_PARAM(Vis, CorGuessWinSize, int, 20, uFormat("[%s=0] Matching window size (pixels) around projected points when a guess transform is provided to find correspondences. 0 means disabled.", kVisCorType().c_str()));
RTABMAP_PARAM(Vis, CorNNDR, float, 0.8, uFormat("[%s=0] NNDR: nearest neighbor distance ratio. Used for knn features matching approach.", kVisCorType().c_str()));
RTABMAP_PARAM(Vis, CorGuessWinSize, int, 40, uFormat("[%s=0] Matching window size (pixels) around projected points when a guess transform is provided to find correspondences. 0 means disabled.", kVisCorType().c_str()));
RTABMAP_PARAM(Vis, CorGuessMatchToProjection, bool, false, uFormat("[%s=0] Match frame's corners to source's projected points (when guess transform is provided) instead of projected points to frame's corners.", kVisCorType().c_str()));
RTABMAP_PARAM(Vis, CorFlowWinSize, int, 16, uFormat("[%s=1] See cv::calcOpticalFlowPyrLK(). Used for optical flow approach.", kVisCorType().c_str()));
RTABMAP_PARAM(Vis, CorFlowIterations, int, 30, uFormat("[%s=1] See cv::calcOpticalFlowPyrLK(). Used for optical flow approach.", kVisCorType().c_str()));
RTABMAP_PARAM(Vis, CorFlowEps, float, 0.01, uFormat("[%s=1] See cv::calcOpticalFlowPyrLK(). Used for optical flow approach.", kVisCorType().c_str()));
RTABMAP_PARAM(Vis, CorFlowMaxLevel, int, 3, uFormat("[%s=1] See cv::calcOpticalFlowPyrLK(). Used for optical flow approach.", kVisCorType().c_str()));
#if defined(RTABMAP_G2O) || defined(RTABMAP_ORB_SLAM2)
#if defined(RTABMAP_G2O) || defined(RTABMAP_ORB_SLAM)
RTABMAP_PARAM(Vis, BundleAdjustment, int, 1, "Optimization with bundle adjustment: 0=disabled, 1=g2o, 2=cvsba, 3=Ceres.");
#else
RTABMAP_PARAM(Vis, BundleAdjustment, int, 0, "Optimization with bundle adjustment: 0=disabled, 1=g2o, 2=cvsba, 3=Ceres.");
#endif
// Features matching approaches
RTABMAP_PARAM_STR(PyMatcher, Path, "", "Path to python script file (see available ones in rtabmap/corelib/src/pymatcher/*). See the header to see where the script should be copied.");
RTABMAP_PARAM_STR(PyMatcher, Path, "", "Path to python script file (see available ones in rtabmap/corelib/src/python/*). See the header to see where the script should be copied.");
RTABMAP_PARAM(PyMatcher, Iterations, int, 20, "Sinkhorn iterations. Used by SuperGlue.");
RTABMAP_PARAM(PyMatcher, Threshold, float, 0.2, "Used by SuperGlue.");
RTABMAP_PARAM(PyMatcher, Cuda, bool, true, "Used by SuperGlue.");
@@ -628,9 +637,14 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(GMS, ThresholdFactor, double, 6.0, "The higher, the less matches.");
// ICP registration parameters
#ifdef RTABMAP_POINTMATCHER
RTABMAP_PARAM(Icp, Strategy, int, 1, "ICP implementation: 0=Point Cloud Library, 1=libpointmatcher, 2=CCCoreLib (CloudCompare).");
#else
RTABMAP_PARAM(Icp, Strategy, int, 0, "ICP implementation: 0=Point Cloud Library, 1=libpointmatcher, 2=CCCoreLib (CloudCompare).");
#endif
RTABMAP_PARAM(Icp, MaxTranslation, float, 0.2, "Maximum ICP translation correction accepted (m).");
RTABMAP_PARAM(Icp, MaxRotation, float, 0.78, "Maximum ICP rotation correction accepted (rad).");
RTABMAP_PARAM(Icp, VoxelSize, float, 0.0, "Uniform sampling voxel size (0=disabled).");
RTABMAP_PARAM(Icp, VoxelSize, float, 0.05, "Uniform sampling voxel size (0=disabled).");
RTABMAP_PARAM(Icp, DownsamplingStep, int, 1, "Downsampling step size (1=no sampling). This is done before uniform sampling.");
RTABMAP_PARAM(Icp, RangeMin, float, 0, "Minimum range filtering (0=disabled).");
RTABMAP_PARAM(Icp, RangeMax, float, 0, "Maximum range filtering (0=disabled).");
@@ -642,25 +656,28 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(Icp, Iterations, int, 30, "Max iterations.");
RTABMAP_PARAM(Icp, Epsilon, float, 0, "Set the transformation epsilon (maximum allowable difference between two consecutive transformations) in order for an optimization to be considered as having converged to the final solution.");
RTABMAP_PARAM(Icp, CorrespondenceRatio, float, 0.1, "Ratio of matching correspondences to accept the transform.");
RTABMAP_PARAM(Icp, Force4DoF, bool, false, uFormat("Limit ICP to x, y, z and yaw DoF. Available if %s > 0.", kIcpStrategy().c_str()));
#ifdef RTABMAP_POINTMATCHER
RTABMAP_PARAM(Icp, PointToPlane, bool, true, "Use point to plane ICP.");
RTABMAP_PARAM(Icp, PointToPlane, bool, true, "Use point to plane ICP.");
#else
RTABMAP_PARAM(Icp, PointToPlane, bool, false, "Use point to plane ICP.");
RTABMAP_PARAM(Icp, PointToPlane, bool, false, "Use point to plane ICP.");
#endif
RTABMAP_PARAM(Icp, PointToPlaneK, int, 5, "Number of neighbors to compute normals for point to plane if the cloud doesn't have already normals.");
RTABMAP_PARAM(Icp, PointToPlaneRadius, float, 1.0, "Search radius to compute normals for point to plane if the cloud doesn't have already normals.");
RTABMAP_PARAM(Icp, PointToPlaneMinComplexity, float, 0.02, "Minimum structural complexity (0.0=low, 1.0=high) of the scan to do point to plane registration, otherwise point to point registration is done instead.");
RTABMAP_PARAM(Icp, PointToPlaneK, int, 5, "Number of neighbors to compute normals for point to plane if the cloud doesn't have already normals.");
RTABMAP_PARAM(Icp, PointToPlaneRadius, float, 1.0, "Search radius to compute normals for point to plane if the cloud doesn't have already normals.");
RTABMAP_PARAM(Icp, PointToPlaneGroundNormalsUp, float, 0.0, "Invert normals on ground if they are pointing down (useful for ring-like 3D LiDARs). 0 means disabled, 1 means only normals perfectly aligned with -z axis. This is only done with 3D scans.");
RTABMAP_PARAM(Icp, PointToPlaneMinComplexity, float, 0.02, uFormat("Minimum structural complexity (0.0=low, 1.0=high) of the scan to do PointToPlane registration, otherwise PointToPoint registration is done instead and strategy from %s is used. This check is done only when %s=true.", kIcpPointToPlaneLowComplexityStrategy().c_str(), kIcpPointToPlane().c_str()));
RTABMAP_PARAM(Icp, PointToPlaneLowComplexityStrategy, int, 1, uFormat("If structural complexity is below %s: set to 0 to so that the transform is automatically rejected, set to 1 to limit ICP correction in axes with most constraints (e.g., for a corridor-like environment, the resulting transform will be limited in y and yaw, x will taken from the guess), set to 2 to accept \"as is\" the transform computed by PointToPoint.", kIcpPointToPlaneMinComplexity().c_str()));
RTABMAP_PARAM(Icp, OutlierRatio, float, 0.85, uFormat("Outlier ratio used with %s>0. For libpointmatcher, this parameter set TrimmedDistOutlierFilter/ratio for convenience when configuration file is not set. For CCCoreLib, this parameter set the \"finalOverlapRatio\". The value should be between 0 and 1.", kIcpStrategy().c_str()));
// libpointmatcher
#ifdef RTABMAP_POINTMATCHER
RTABMAP_PARAM(Icp, PM, bool, true, "Use libpointmatcher for ICP registration instead of PCL's implementation.");
#else
RTABMAP_PARAM(Icp, PM, bool, false, "Use libpointmatcher for ICP registration instead of PCL's implementation.");
#endif
RTABMAP_PARAM_STR(Icp, PMConfig, "", uFormat("Configuration file (*.yaml) used by libpointmatcher. Note that data filters set for libpointmatcher are done after filtering done by rtabmap (i.e., %s, %s), so make sure to disable those in rtabmap if you want to use only those from libpointmatcher. Parameters %s, %s and %s are also ignored if configuration file is set.", kIcpVoxelSize().c_str(), kIcpDownsamplingStep().c_str(), kIcpIterations().c_str(), kIcpEpsilon().c_str(), kIcpMaxCorrespondenceDistance().c_str()).c_str());
RTABMAP_PARAM(Icp, PMMatcherKnn, int, 1, "KDTreeMatcher/knn: number of nearest neighbors to consider it the reference. For convenience when configuration file is not set.");
RTABMAP_PARAM(Icp, PMMatcherEpsilon, float, 0.0, "KDTreeMatcher/epsilon: approximation to use for the nearest-neighbor search. For convenience when configuration file is not set.");
RTABMAP_PARAM(Icp, PMOutlierRatio, float, 0.95, "TrimmedDistOutlierFilter/ratio: For convenience when configuration file is not set. For kinect-like point cloud, use 0.65.");
RTABMAP_PARAM(Icp, PMMatcherIntensity, bool, false, uFormat("KDTreeMatcher: among nearest neighbors, keep only the one with the most similar intensity. This only work with %s>1.", kIcpPMMatcherKnn().c_str()));
RTABMAP_PARAM(Icp, CCSamplingLimit, unsigned int, 50000, "Maximum number of points per cloud (they are randomly resampled below this limit otherwise).");
RTABMAP_PARAM(Icp, CCFilterOutFarthestPoints, bool, false, "If true, the algorithm will automatically ignore farthest points from the reference, for better convergence.");
RTABMAP_PARAM(Icp, CCMaxFinalRMS, float, 0.2, "Maximum final RMS error.");
// Stereo disparity
RTABMAP_PARAM(Stereo, WinWidth, int, 15, "Window width.");
@@ -741,6 +758,7 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(GridGlobal, MinSize, float, 0.0, "Minimum map size (m).");
RTABMAP_PARAM(GridGlobal, Eroded, bool, false, "Erode obstacle cells.");
RTABMAP_PARAM(GridGlobal, MaxNodes, int, 0, "Maximum nodes assembled in the map starting from the last node (0=unlimited).");
RTABMAP_PARAM(GridGlobal, AltitudeDelta, float, 0, "Assemble only nodes that have the same altitude of +-delta meters of the current pose (0=disabled). This is used to generate 2D occupancy grid based on the current altitude (e.g., multi-floor building).");
RTABMAP_PARAM(GridGlobal, OccupancyThr, float, 0.5, "Occupancy threshold (value between 0 and 1).");
RTABMAP_PARAM(GridGlobal, ProbHit, float, 0.7, "Probability of a hit (value between 0.5 and 1).");
RTABMAP_PARAM(GridGlobal, ProbMiss, float, 0.4, "Probability of a miss (value between 0 and 0.5).");
@@ -753,6 +771,8 @@ class RTABMAP_EXP Parameters
RTABMAP_PARAM(Marker, VarianceLinear, float, 0.001, "Linear variance to set on marker detections.");
RTABMAP_PARAM(Marker, VarianceAngular, float, 0.01, "Angular variance to set on marker detections. Set to >=9999 to use only position (xyz) constraint in graph optimization.");
RTABMAP_PARAM(Marker, CornerRefinementMethod, int, 0, "Corner refinement method (0: None, 1: Subpixel, 2:contour, 3: AprilTag2). For OpenCV <3.3.0, this is \"doCornerRefinement\" parameter: set 0 for false and 1 for true.");
RTABMAP_PARAM(Marker, MaxRange, float, 0.0, "Maximum range in which markers will be detected. <=0 for unlimited range.");
RTABMAP_PARAM(Marker, MinRange, float, 0.0, "Miniminum range in which markers will be detected. <=0 for unlimited range.");
RTABMAP_PARAM(ImuFilter, MadgwickGain, double, 0.1, "Gain of the filter. Higher values lead to faster convergence but more noise. Lower values lead to slower convergence but smoother signal, belongs in [0, 1].");
RTABMAP_PARAM(ImuFilter, MadgwickZeta, double, 0.0, "Gyro drift gain (approx. rad/s), belongs in [-1, 1].");
@@ -840,4 +860,3 @@ private:
}
#endif /* PARAMETERS_H_ */
@@ -0,0 +1,41 @@
/*
* PythonInterface.h
*
* Created on: Jan. 14, 2021
* Author: mathieu
*/
#ifndef CORELIB_SRC_PYTHON_PYTHONINTERFACE_H_
#define CORELIB_SRC_PYTHON_PYTHONINTERFACE_H_
#include <string>
#include <rtabmap/utilite/UMutex.h>
#include <Python.h>
namespace rtabmap {
class PythonInterface
{
public:
PythonInterface();
virtual ~PythonInterface();
protected:
std::string getTraceback(); // should be called between lock() and unlock()
void lock();
void unlock();
private:
static UMutex mutex_;
static int refCount_;
protected:
static PyThreadState * mainThreadState_;
static unsigned long mainThreadID_;
PyThreadState * threadState_;
};
}
#endif /* CORELIB_SRC_PYTHON_PYTHONINTERFACE_H_ */
+11 -2
View File
@@ -56,6 +56,7 @@ protected:
virtual float getMinGeometryCorrespondencesRatioImpl() const {return _correspondenceRatio;}
private:
int _strategy;
float _maxTranslation;
float _maxRotation;
float _voxelSize;
@@ -66,16 +67,24 @@ private:
int _maxIterations;
float _epsilon;
float _correspondenceRatio;
bool _force4DoF;
bool _pointToPlane;
int _pointToPlaneK;
float _pointToPlaneRadius;
float _pointToPlaneGroundNormalsUp;
float _pointToPlaneMinComplexity;
bool _libpointmatcher;
int _pointToPlaneLowComplexityStrategy;
std::string _libpointmatcherConfig;
int _libpointmatcherKnn;
float _libpointmatcherEpsilon;
float _libpointmatcherOutlierRatio;
bool _libpointmatcherIntensity;
float _outlierRatio;
unsigned int _ccSamplingLimit;
bool _ccFilterOutFarthestPoints;
double _ccMaxFinalRMS;
void * _libpointmatcherICP;
void * _libpointmatcherICPFilters;
};
}
@@ -37,7 +37,7 @@ namespace rtabmap {
class Feature2D;
#ifdef RTABMAP_PYMATCHER
#ifdef RTABMAP_PYTHON
class PyMatcher;
#endif
@@ -105,7 +105,7 @@ private:
Feature2D * _detectorFrom;
Feature2D * _detectorTo;
#ifdef RTABMAP_PYMATCHER
#ifdef RTABMAP_PYTHON
PyMatcher * _pyMatcher;
#endif
};
+5 -3
View File
@@ -199,12 +199,13 @@ public:
std::map<int, Transform> getNodesInRadius(const Transform & pose, float radius); // If radius=0, RGBD/LocalRadius is used. Can return landmarks.
std::map<int, Transform> getNodesInRadius(int nodeId, float radius); // If nodeId==0, return poses around latest node. If radius=0, RGBD/LocalRadius is used. Can return landmarks and use landmark id (negative) as request.
int detectMoreLoopClosures(
float clusterRadius = 0.5f,
float clusterRadiusMax = 0.5f,
float clusterAngle = M_PI/6.0f,
int iterations = 1,
bool intraSession = true,
bool interSession = true,
const ProgressState * state = 0);
const ProgressState * state = 0,
float clusterRadiusMin = 0.0f);
int refineLinks();
bool addLink(const Link & link);
cv::Mat getInformation(const cv::Mat & covariance) const;
@@ -281,6 +282,7 @@ private:
bool _proximityByTime;
bool _proximityBySpace;
bool _scanMatchingIdsSavedInLinks;
bool _loopClosureIdentityGuess;
float _localRadius;
float _localImmunizationRatio;
int _proximityMaxGraphDepth;
@@ -300,7 +302,7 @@ private:
int _pathStuckIterations;
float _pathLinearVelocity;
float _pathAngularVelocity;
bool _savedLocalizationIgnored;
bool _restartAtOrigin;
bool _loopCovLimited;
bool _loopGPS;
int _maxOdomCacheSize;
@@ -140,6 +140,8 @@ private:
cv::Mat F_;
};
RTABMAP_EXP std::ostream& operator<<(std::ostream& os, const StereoCameraModel& model);
} // rtabmap
#endif /* STEREOCAMERAMODEL_H_ */
+1
View File
@@ -98,6 +98,7 @@ public:
float theta() const;
bool isInvertible() const;
Transform inverse() const;
Transform rotation() const;
Transform translation() const;
@@ -0,0 +1,83 @@
/*
Copyright (c) 2010-2021, Mathieu Labbe - IntRoLab - Universite de Sherbrooke
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
* Neither the name of the Universite de Sherbrooke nor the
names of its contributors may be used to endorse or promote products
derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY
DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#pragma once
#include "rtabmap/core/RtabmapExp.h" // DLL export/import defines
#include "rtabmap/core/StereoCameraModel.h"
#include "rtabmap/core/Camera.h"
#include "rtabmap/core/Version.h"
#ifdef RTABMAP_DEPTHAI
#ifndef DEPTHAI_OPENCV_SUPPORT
#define DEPTHAI_OPENCV_SUPPORT
#endif
#include <depthai/depthai.hpp>
#endif
namespace rtabmap
{
class RTABMAP_EXP CameraDepthAI :
public Camera
{
public:
static bool available();
public:
CameraDepthAI(
const std::string & deviceSerial = "",
int resolution = 1, // 0=720p, 1=800p, 2=400p
float imageRate=0.0f,
const Transform & localTransform = CameraModel::opticalRotation());
virtual ~CameraDepthAI();
void setOutputDepth(bool enabled, int confidence = 200);
virtual bool init(const std::string & calibrationFolder = ".", const std::string & cameraName = "");
virtual bool isCalibrated() const;
virtual std::string getSerial() const;
protected:
virtual SensorData captureImage(CameraInfo * info = 0);
private:
#ifdef RTABMAP_DEPTHAI
StereoCameraModel stereoModel_;
std::string deviceSerial_;
bool outputDepth_;
int depthConfidence_;
int resolution_;
std::shared_ptr<dai::Device> device_;
std::shared_ptr<dai::DataOutputQueue> leftQueue_;
std::shared_ptr<dai::DataOutputQueue> rightOrDepthQueue_;
#endif
};
} // namespace rtabmap
@@ -74,6 +74,11 @@ public:
_syncImageRateWithStamps = syncImageRateWithStamps;
}
void setConfigForEachFrame(bool value)
{
_hasConfigForEachFrame = value;
}
void setScanPath(
const std::string & dir,
int maxScanPts = 0,
@@ -116,12 +121,14 @@ public:
protected:
virtual SensorData captureImage(CameraInfo * info = 0);
private:
bool readPoses(
std::list<Transform> & outputPoses,
std::list<double> & stamps,
const std::string & filePath,
int format,
double maxTimeDiff) const;
std::list<Transform> & outputPoses,
std::list<double> & stamps,
const std::string & filePath,
int format,
double maxTimeDiff) const;
private:
std::string _path;
@@ -151,6 +158,7 @@ private:
bool _depthFromScanFillHolesFromBorder;
bool _filenamesAreTimestamps;
bool _hasConfigForEachFrame;
std::string _timestampsPath;
bool _syncImageRateWithStamps;
@@ -162,8 +170,10 @@ private:
std::list<double> _stamps;
std::list<Transform> odometry_;
std::list<cv::Mat> covariances_;
std::list<Transform> groundTruth_;
CameraModel _model;
std::list<CameraModel> _models;
UTimer _captureTimer;
double _captureDelay;
@@ -48,8 +48,6 @@ public:
virtual ~CameraRGBDImages();
virtual bool init(const std::string & calibrationFolder = ".", const std::string & cameraName = "");
virtual bool isCalibrated() const;
virtual std::string getSerial() const;
virtual void setStartIndex(int index) {CameraImages::setStartIndex(index);cameraDepth_.setStartIndex(index);} // negative means last
virtual void setMaxFrames(int value) {CameraImages::setMaxFrames(value);cameraDepth_.setMaxFrames(value);}
@@ -36,6 +36,7 @@ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#include <pcl/pcl_config.h>
#ifdef RTABMAP_REALSENSE2
#include <librealsense2/rs.hpp>
#include <librealsense2/hpp/rs_frame.hpp>
#endif
@@ -75,6 +76,8 @@ public:
void setEmitterEnabled(bool enabled);
void setIRFormat(bool enabled, bool useDepthInsteadOfRightImage);
void setResolution(int width, int height, int fps = 30);
void setDepthResolution(int width, int height, int fps = 30);
void setGlobalTimeSync(bool enabled);
void publishInterIMU(bool enabled);
void setDualMode(bool enabled, const Transform & extrinsics);
void setJsonConfig(const std::string & json);
@@ -84,6 +87,7 @@ public:
#ifdef RTABMAP_REALSENSE2
private:
void close();
void imu_callback(rs2::frame frame);
void pose_callback(rs2::frame frame);
void frame_callback(rs2::frame frame);
@@ -93,7 +97,7 @@ private:
Transform & pose,
unsigned int & poseConfidence,
IMU & imu,
int maxWaitTimeMs = 35) const;
int maxWaitTimeMs = 35);
#endif
protected:
@@ -101,14 +105,14 @@ protected:
private:
#ifdef RTABMAP_REALSENSE2
rs2::context * ctx_;
std::vector<rs2::device *> dev_;
rs2::context ctx_;
std::vector<rs2::device> dev_;
std::string deviceId_;
rs2::syncer * syncer_;
rs2::syncer syncer_;
float depth_scale_meters_;
rs2_intrinsics * depthIntrinsics_;
rs2_intrinsics * rgbIntrinsics_;
rs2_extrinsics * depthToRGBExtrinsics_;
rs2_intrinsics depthIntrinsics_;
rs2_intrinsics rgbIntrinsics_;
rs2_extrinsics depthToRGBExtrinsics_;
cv::Mat depthBuffer_;
cv::Mat rgbBuffer_;
CameraModel model_;
@@ -121,6 +125,7 @@ private:
UMutex imuMutex_;
double lastImuStamp_;
bool clockSyncWarningShown_;
bool imuGlobalSyncWarningShown_;
bool emitterEnabled_;
bool ir_;
@@ -130,6 +135,10 @@ private:
int cameraWidth_;
int cameraHeight_;
int cameraFps_;
int cameraDepthWidth_;
int cameraDepthHeight_;
int cameraDepthFps_;
bool globalTimeSync_;
bool publishInterIMU_;
bool dualMode_;
Transform dualExtrinsics_;
@@ -70,6 +70,8 @@ public:
virtual bool isCalibrated() const;
virtual std::string getSerial() const;
void setResolution(int width, int height) {_width=width, _height=height;}
protected:
virtual SensorData captureImage(CameraInfo * info = 0);
@@ -84,6 +86,8 @@ private:
CameraVideo::Source src_;
int usbDevice_;
int usbDevice2_;
int _width;
int _height;
};
} // namespace rtabmap
@@ -1,66 +1,83 @@
/*
Copyright (c) 2010-2016, Mathieu Labbe - IntRoLab - Universite de Sherbrooke
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
* Neither the name of the Universite de Sherbrooke nor the
names of its contributors may be used to endorse or promote products
derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY
DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef OBJDELETIONHANDLER_H_
#define OBJDELETIONHANDLER_H_
#include "rtabmap/utilite/UEventsHandler.h"
#include "rtabmap/utilite/UEvent.h"
#include <QtCore/QObject>
class ObjDeletionHandler : public QObject, public UEventsHandler
{
Q_OBJECT
public:
ObjDeletionHandler(int watchedId, QObject * receiver = 0, const char * member = 0) : _watchedId(watchedId)
{
if(receiver && member)
{
connect(this, SIGNAL(objDeletionEventReceived(int)), receiver, member);
}
}
virtual ~ObjDeletionHandler() {}
Q_SIGNALS:
void objDeletionEventReceived(int);
protected:
virtual bool handleEvent(UEvent * event)
{
if(event->getClassName().compare("UObjDeletedEvent") == 0 &&
event->getCode() == _watchedId)
{
Q_EMIT objDeletionEventReceived(_watchedId);
}
return false;
}
private:
int _watchedId;
};
#endif /* OBJDELETIONHANDLER_H_ */
/*
Copyright (c) 2010-2016, Mathieu Labbe - IntRoLab - Universite de Sherbrooke
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
* Neither the name of the Universite de Sherbrooke nor the
names of its contributors may be used to endorse or promote products
derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY
DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#pragma once
#include "rtabmap/core/RtabmapExp.h" // DLL export/import defines
#include "rtabmap/core/StereoCameraModel.h"
#include "rtabmap/core/Camera.h"
#include "rtabmap/core/Version.h"
namespace sl_oc {
namespace video {
class VideoCapture;
}
namespace sensors {
class SensorCapture;
}
}
namespace rtabmap
{
class ZedOCThread;
class RTABMAP_EXP CameraStereoZedOC :
public Camera
{
public:
static bool available();
public:
CameraStereoZedOC(
int deviceId,
int resolution = 3, // 0=HD2K, 1=HD1080, 2=HD720, 3=VGA
float imageRate=0.0f,
const Transform & localTransform = CameraModel::opticalRotation());
virtual ~CameraStereoZedOC();
virtual bool init(const std::string & calibrationFolder = ".", const std::string & cameraName = "");
virtual bool isCalibrated() const;
virtual std::string getSerial() const;
protected:
virtual SensorData captureImage(CameraInfo * info = 0);
private:
#ifdef RTABMAP_ZEDOC
sl_oc::video::VideoCapture * zed_;
sl_oc::sensors::SensorCapture * sensors_;
ZedOCThread * imuThread_;
StereoCameraModel stereoModel_;
int usbDevice_;
int resolution_;
uint64_t lastStamp_;
#endif
};
} // namespace rtabmap
@@ -97,28 +97,35 @@ void segmentObstaclesFromGround(
// cluster all surfaces for which the centroid is in the Z-range of the bigger surface
if(clusteredFlatSurfaces.size())
{
Eigen::Vector4f min,max;
Eigen::Vector4f biggestSurfaceMin,biggestSurfaceMax;
if(maxGroundHeight != 0.0f)
{
// Search for biggest surface under max ground height
size_t points = 0;
biggestFlatSurfaceIndex = -1;
for(size_t i=0;i<clusteredFlatSurfaces.size();++i)
{
Eigen::Vector4f min,max;
pcl::getMinMax3D(*cloud, *clusteredFlatSurfaces.at(i), min, max);
if(min[2]<maxGroundHeight && clusteredFlatSurfaces.size() > points)
{
points = clusteredFlatSurfaces.at(i)->size();
biggestFlatSurfaceIndex = i;
biggestSurfaceMin = min;
biggestSurfaceMax = max;
}
}
}
else
{
pcl::getMinMax3D(*cloud, *clusteredFlatSurfaces.at(biggestFlatSurfaceIndex), min, max);
pcl::getMinMax3D(*cloud, *clusteredFlatSurfaces.at(biggestFlatSurfaceIndex), biggestSurfaceMin, biggestSurfaceMax);
}
if(biggestFlatSurfaceIndex>=0)
{
ground = clusteredFlatSurfaces.at(biggestFlatSurfaceIndex);
}
ground = clusteredFlatSurfaces.at(biggestFlatSurfaceIndex);
if(!ground->empty() && (maxGroundHeight == 0.0f || min[2] < maxGroundHeight))
if(!ground->empty() && (maxGroundHeight == 0.0f || biggestSurfaceMin[2] < maxGroundHeight))
{
for(unsigned int i=0; i<clusteredFlatSurfaces.size(); ++i)
{
@@ -126,7 +133,7 @@ void segmentObstaclesFromGround(
{
Eigen::Vector4f centroid(0,0,0,1);
pcl::compute3DCentroid(*cloud, *clusteredFlatSurfaces.at(i), centroid);
if(maxGroundHeight==0.0f || centroid[2] <= maxGroundHeight || centroid[2] <= max[2]) // epsilon
if(maxGroundHeight==0.0f || centroid[2] <= maxGroundHeight || centroid[2] <= biggestSurfaceMax[2]) // epsilon
{
ground = util3d::concatenate(ground, clusteredFlatSurfaces.at(i));
}
@@ -9,6 +9,7 @@
#define CORELIB_INCLUDE_RTABMAP_CORE_IMPL_UTIL3D_SURFACE_HPP_
#include <pcl/search/kdtree.h>
#include <pcl/conversions.h>
#include <rtabmap/utilite/UConversion.h>
namespace rtabmap {
@@ -50,7 +50,6 @@ public:
virtual void reset(const Transform & initialPose = Transform::getIdentity());
const Signature & getMap() const {return *map_;}
const Signature & getLastFrame() const {return *lastFrame_;}
virtual bool canProcessIMU() const;
virtual Odometry::Type getType() {return Odometry::kTypeF2M;}
@@ -78,8 +77,7 @@ private:
Signature * map_;
Signature * lastFrame_;
int lastFrameOldestNewId_;
std::vector<std::pair<pcl::PointCloud<pcl::PointNormal>::Ptr, pcl::IndicesPtr> > scansBuffer_;
bool initGravity_;
std::vector<std::pair<pcl::PointCloud<pcl::PointXYZINormal>::Ptr, pcl::IndicesPtr> > scansBuffer_;
std::map<int, std::map<int, FeatureBA> > bundleWordReferences_; //<WordId, <FrameId, pt2D+depth>>
std::map<int, Transform> bundlePoses_;
@@ -44,7 +44,7 @@ public:
virtual void reset(const Transform & initialPose = Transform::getIdentity());
virtual Odometry::Type getType() {return Odometry::kTypeMSCKF;}
virtual bool canProcessRawImages() const {return true;}
virtual bool canProcessIMU() const {return true;}
virtual bool canProcessAsyncIMU() const {return true;}
private:
virtual Transform computeTransform(SensorData & image, const Transform & guess = Transform(), OdometryInfo * info = 0);
@@ -25,41 +25,48 @@ ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
#ifndef ODOMETRYORBSLAM2_H_
#define ODOMETRYORBSLAM2_H_
#ifndef ODOMETRYORBSLAM_H_
#define ODOMETRYORBSLAM_H_
#include <rtabmap/core/Odometry.h>
#if RTABMAP_ORB_SLAM == 3
namespace ORB_SLAM3 {
#else
namespace ORB_SLAM2 {
#endif
class System;
}
class ORBSLAM2System;
class ORBSLAMSystem;
namespace rtabmap {
class RTABMAP_EXP OdometryORBSLAM2 : public Odometry
class RTABMAP_EXP OdometryORBSLAM : public Odometry
{
public:
OdometryORBSLAM2(const rtabmap::ParametersMap & parameters = rtabmap::ParametersMap());
virtual ~OdometryORBSLAM2();
OdometryORBSLAM(const rtabmap::ParametersMap & parameters = rtabmap::ParametersMap());
virtual ~OdometryORBSLAM();
virtual void reset(const Transform & initialPose = Transform::getIdentity());
virtual Odometry::Type getType() {return Odometry::kTypeORBSLAM2;}
virtual Odometry::Type getType() {return Odometry::kTypeORBSLAM;}
virtual bool canProcessAsyncIMU() const;
private:
virtual Transform computeTransform(SensorData & image, const Transform & guess = Transform(), OdometryInfo * info = 0);
private:
#ifdef RTABMAP_ORB_SLAM2
ORBSLAM2System * orbslam2_;
#ifdef RTABMAP_ORB_SLAM
ORBSLAMSystem * orbslam_;
bool firstFrame_;
Transform originLocalTransform_;
Transform previousPose_;
bool useIMU_;
Transform imuLocalTransform_;
#endif
};
}
#endif /* ODOMETRYORBSLAM2_H_ */
#endif /* ODOMETRYORBSLAM_H_ */
@@ -46,7 +46,7 @@ public:
virtual void reset(const Transform & initialPose = Transform::getIdentity());
virtual Odometry::Type getType() {return Odometry::kTypeOkvis;}
virtual bool canProcessRawImages() const {return true;}
virtual bool canProcessIMU() const {return true;}
virtual bool canProcessAsyncIMU() const {return true;}
private:
virtual Transform computeTransform(SensorData & image, const Transform & guess = Transform(), OdometryInfo * info = 0);
@@ -43,7 +43,7 @@ public:
virtual void reset(const Transform & initialPose = Transform::getIdentity());
virtual Odometry::Type getType() {return Odometry::kTypeVINS;}
virtual bool canProcessRawImages() const {return true;}
virtual bool canProcessIMU() const {return true;}
virtual bool canProcessAsyncIMU() const {return true;}
private:
virtual Transform computeTransform(SensorData & image, const Transform & guess = Transform(), OdometryInfo * info = 0);
+2
View File
@@ -154,6 +154,8 @@ cv::Mat RTABMAP_EXP brightnessAndContrastAuto(
cv::Mat RTABMAP_EXP exposureFusion(
const std::vector<cv::Mat> & images);
void RTABMAP_EXP HSVtoRGB( float *r, float *g, float *b, float h, float s, float v );
} // namespace util3d
} // namespace rtabmap
+49 -20
View File
@@ -38,6 +38,7 @@ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#include <rtabmap/core/SensorData.h>
#include <rtabmap/core/Parameters.h>
#include <opencv2/core/core.hpp>
#include <rtabmap/core/ProgressState.h>
#include <map>
#include <list>
@@ -198,35 +199,36 @@ pcl::PointCloud<pcl::PointXYZ> RTABMAP_EXP laserScanFromDepthImages(
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PCLPointCloud2 & cloud, bool filterNaNs = true, bool is2D = false, const Transform & transform = Transform());
// return CV_32FC3 (x,y,z)
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZ> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZ> & cloud, const pcl::IndicesPtr & indices, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZ> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZ> & cloud, const pcl::IndicesPtr & indices, const Transform & transform = Transform(), bool filterNaNs = true);
// return CV_32FC6 (x,y,z,normal_x,normal_y,normal_z)
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointNormal> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointNormal> & cloud, const pcl::IndicesPtr & indices, const Transform & transform = Transform(), bool filterNaNs = true);
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZ> & cloud, const pcl::PointCloud<pcl::Normal> & normals, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointNormal> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointNormal> & cloud, const pcl::IndicesPtr & indices, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZ> & cloud, const pcl::PointCloud<pcl::Normal> & normals, const Transform & transform = Transform(), bool filterNaNs = true);
// return CV_32FC4 (x,y,z,rgb)
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZRGB> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZRGB> & cloud, const pcl::IndicesPtr & indices, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZRGB> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZRGB> & cloud, const pcl::IndicesPtr & indices, const Transform & transform = Transform(), bool filterNaNs = true);
// return CV_32FC4 (x,y,z,I)
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZI> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZI> & cloud, const pcl::IndicesPtr & indices, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZI> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZI> & cloud, const pcl::IndicesPtr & indices, const Transform & transform = Transform(), bool filterNaNs = true);
// return CV_32FC7 (x,y,z,rgb,normal_x,normal_y,normal_z)
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZRGB> & cloud, const pcl::PointCloud<pcl::Normal> & normals, const Transform & transform = Transform(), bool filterNaNs = true);
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZRGBNormal> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZRGBNormal> & cloud, const pcl::IndicesPtr & indices, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZRGB> & cloud, const pcl::PointCloud<pcl::Normal> & normals, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZRGBNormal> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZRGBNormal> & cloud, const pcl::IndicesPtr & indices, const Transform & transform = Transform(), bool filterNaNs = true);
// return CV_32FC7 (x,y,z,I,normal_x,normal_y,normal_z)
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZI> & cloud, const pcl::PointCloud<pcl::Normal> & normals, const Transform & transform = Transform(), bool filterNaNs = true);
cv::Mat RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZINormal> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZI> & cloud, const pcl::PointCloud<pcl::Normal> & normals, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZINormal> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScanFromPointCloud(const pcl::PointCloud<pcl::PointXYZINormal> & cloud, const pcl::IndicesPtr & indices, const Transform & transform = Transform(), bool filterNaNs = true);
// return CV_32FC2 (x,y)
cv::Mat RTABMAP_EXP laserScan2dFromPointCloud(const pcl::PointCloud<pcl::PointXYZ> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScan2dFromPointCloud(const pcl::PointCloud<pcl::PointXYZ> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
// return CV_32FC3 (x,y,I)
cv::Mat RTABMAP_EXP laserScan2dFromPointCloud(const pcl::PointCloud<pcl::PointXYZI> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScan2dFromPointCloud(const pcl::PointCloud<pcl::PointXYZI> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
// return CV_32FC5 (x,y,normal_x, normal_y, normal_z)
cv::Mat RTABMAP_EXP laserScan2dFromPointCloud(const pcl::PointCloud<pcl::PointNormal> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
cv::Mat RTABMAP_EXP laserScan2dFromPointCloud(const pcl::PointCloud<pcl::PointXYZ> & cloud, const pcl::PointCloud<pcl::Normal> & normals, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScan2dFromPointCloud(const pcl::PointCloud<pcl::PointNormal> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScan2dFromPointCloud(const pcl::PointCloud<pcl::PointXYZ> & cloud, const pcl::PointCloud<pcl::Normal> & normals, const Transform & transform = Transform(), bool filterNaNs = true);
// return CV_32FC6 (x,y,I,normal_x, normal_y, normal_z)
cv::Mat RTABMAP_EXP laserScan2dFromPointCloud(const pcl::PointCloud<pcl::PointXYZINormal> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
cv::Mat RTABMAP_EXP laserScan2dFromPointCloud(const pcl::PointCloud<pcl::PointXYZI> & cloud, const pcl::PointCloud<pcl::Normal> & normals, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScan2dFromPointCloud(const pcl::PointCloud<pcl::PointXYZINormal> & cloud, const Transform & transform = Transform(), bool filterNaNs = true);
LaserScan RTABMAP_EXP laserScan2dFromPointCloud(const pcl::PointCloud<pcl::PointXYZI> & cloud, const pcl::PointCloud<pcl::Normal> & normals, const Transform & transform = Transform(), bool filterNaNs = true);
pcl::PCLPointCloud2::Ptr RTABMAP_EXP laserScanToPointCloud2(const LaserScan & laserScan, const Transform & transform = Transform());
// For 2d laserScan, z is set to null.
@@ -299,6 +301,33 @@ void RTABMAP_EXP fillProjectedCloudHoles(
bool verticalDirection,
bool fillToBorder);
/**
* For each point, return pixel of the best camera (NodeID->CameraIndex)
* looking at it based on the policy and parameters
*/
std::vector<std::pair< std::pair<int, int>, pcl::PointXY> > RTABMAP_EXP projectCloudToCameras (
const pcl::PointCloud<pcl::PointXYZRGBNormal> & cloud,
const std::map<int, Transform> & cameraPoses,
const std::map<int, std::vector<CameraModel> > & cameraModels,
float maxDistance = 0.0f,
float maxAngle = 0.0f,
const std::vector<float> & roiRatios = std::vector<float>(),
bool distanceToCamPolicy = false,
const ProgressState * state = 0);
/**
* For each point, return pixel of the best camera (NodeID->CameraIndex)
* looking at it based on the policy and parameters
*/
std::vector<std::pair< std::pair<int, int>, pcl::PointXY> > RTABMAP_EXP projectCloudToCameras (
const pcl::PointCloud<pcl::PointXYZINormal> & cloud,
const std::map<int, Transform> & cameraPoses,
const std::map<int, std::vector<CameraModel> > & cameraModels,
float maxDistance = 0.0f,
float maxAngle = 0.0f,
const std::vector<float> & roiRatios = std::vector<float>(),
bool distanceToCamPolicy = false,
const ProgressState * state = 0);
bool RTABMAP_EXP isFinite(const cv::Point3f & pt);
pcl::PointCloud<pcl::PointXYZ>::Ptr RTABMAP_EXP concatenateClouds(
+108 -1
View File
@@ -56,7 +56,16 @@ LaserScan RTABMAP_EXP commonFiltering(
float voxelSize = 0.0f,
int normalK = 0,
float normalRadius = 0.0f,
bool forceGroundNormalsUp = false);
float groundNormalsUp = 0.0f);
RTABMAP_DEPRECATED(LaserScan RTABMAP_EXP commonFiltering(
const LaserScan & scan,
int downsamplingStep,
float rangeMin,
float rangeMax,
float voxelSize,
int normalK,
float normalRadius,
bool forceGroundNormalsUp), "Use version with groundNormalsUp as float. For forceGroundNormalsUp=true, set groundNormalsUp=0.8, otherwise set groundNormalsUp=0.0.");
LaserScan RTABMAP_EXP rangeFiltering(
const LaserScan & scan,
@@ -270,6 +279,20 @@ pcl::IndicesPtr RTABMAP_EXP cropBox(
const Eigen::Vector4f & max,
const Transform & transform = Transform::getIdentity(),
bool negative = false);
pcl::IndicesPtr RTABMAP_EXP cropBox(
const pcl::PointCloud<pcl::PointXYZI>::Ptr & cloud,
const pcl::IndicesPtr & indices,
const Eigen::Vector4f & min,
const Eigen::Vector4f & max,
const Transform & transform = Transform::getIdentity(),
bool negative = false);
pcl::IndicesPtr RTABMAP_EXP cropBox(
const pcl::PointCloud<pcl::PointXYZINormal>::Ptr & cloud,
const pcl::IndicesPtr & indices,
const Eigen::Vector4f & min,
const Eigen::Vector4f & max,
const Transform & transform = Transform::getIdentity(),
bool negative = false);
pcl::PointCloud<pcl::PointXYZ>::Ptr RTABMAP_EXP cropBox(
const pcl::PointCloud<pcl::PointXYZ>::Ptr & cloud,
const Eigen::Vector4f & min,
@@ -288,6 +311,18 @@ pcl::PointCloud<pcl::PointXYZRGB>::Ptr RTABMAP_EXP cropBox(
const Eigen::Vector4f & max,
const Transform & transform = Transform::getIdentity(),
bool negative = false);
pcl::PointCloud<pcl::PointXYZI>::Ptr RTABMAP_EXP cropBox(
const pcl::PointCloud<pcl::PointXYZI>::Ptr & cloud,
const Eigen::Vector4f & min,
const Eigen::Vector4f & max,
const Transform & transform = Transform::getIdentity(),
bool negative = false);
pcl::PointCloud<pcl::PointXYZINormal>::Ptr RTABMAP_EXP cropBox(
const pcl::PointCloud<pcl::PointXYZINormal>::Ptr & cloud,
const Eigen::Vector4f & min,
const Eigen::Vector4f & max,
const Transform & transform = Transform::getIdentity(),
bool negative = false);
pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr RTABMAP_EXP cropBox(
const pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr & cloud,
const Eigen::Vector4f & min,
@@ -331,6 +366,8 @@ pcl::PointCloud<pcl::PointXYZRGB>::Ptr RTABMAP_EXP removeNaNFromPointCloud(
const pcl::PointCloud<pcl::PointXYZRGB>::Ptr & cloud);
pcl::PointCloud<pcl::PointXYZI>::Ptr RTABMAP_EXP removeNaNFromPointCloud(
const pcl::PointCloud<pcl::PointXYZI>::Ptr & cloud);
pcl::PCLPointCloud2::Ptr RTABMAP_EXP removeNaNFromPointCloud(
const pcl::PCLPointCloud2::Ptr & cloud);
pcl::PointCloud<pcl::PointNormal>::Ptr RTABMAP_EXP removeNaNNormalsFromPointCloud(
@@ -393,6 +430,16 @@ pcl::IndicesPtr RTABMAP_EXP radiusFiltering(
const pcl::IndicesPtr & indices,
float radiusSearch,
int minNeighborsInRadius);
pcl::IndicesPtr RTABMAP_EXP radiusFiltering(
const pcl::PointCloud<pcl::PointXYZI>::Ptr & cloud,
const pcl::IndicesPtr & indices,
float radiusSearch,
int minNeighborsInRadius);
pcl::IndicesPtr RTABMAP_EXP radiusFiltering(
const pcl::PointCloud<pcl::PointXYZINormal>::Ptr & cloud,
const pcl::IndicesPtr & indices,
float radiusSearch,
int minNeighborsInRadius);
/**
* For convenience.
@@ -451,6 +498,12 @@ pcl::IndicesPtr RTABMAP_EXP subtractFiltering(
/**
* For convenience.
*/
pcl::PointCloud<pcl::PointXYZINormal>::Ptr RTABMAP_EXP subtractFiltering(
const pcl::PointCloud<pcl::PointXYZINormal>::Ptr & cloud,
const pcl::PointCloud<pcl::PointXYZINormal>::Ptr & substractCloud,
float radiusSearch,
float maxAngle = M_PI/4.0f,
int minNeighborsInRadius = 1);
pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr RTABMAP_EXP subtractFiltering(
const pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr & cloud,
const pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr & substractCloud,
@@ -467,6 +520,14 @@ pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr RTABMAP_EXP subtractFiltering(
* @param radiusSearch the radius in meter.
* @return the indices of the points satisfying the parameters.
*/
pcl::IndicesPtr RTABMAP_EXP subtractFiltering(
const pcl::PointCloud<pcl::PointXYZINormal>::Ptr & cloud,
const pcl::IndicesPtr & indices,
const pcl::PointCloud<pcl::PointXYZINormal>::Ptr & substractCloud,
const pcl::IndicesPtr & substractIndices,
float radiusSearch,
float maxAngle = M_PI/4.0f,
int minNeighborsInRadius = 1);
pcl::IndicesPtr RTABMAP_EXP subtractFiltering(
const pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr & cloud,
const pcl::IndicesPtr & indices,
@@ -561,6 +622,13 @@ pcl::IndicesPtr RTABMAP_EXP normalFiltering(
const Eigen::Vector4f & normal,
int normalKSearch,
const Eigen::Vector4f & viewpoint);
pcl::IndicesPtr RTABMAP_EXP normalFiltering(
const pcl::PointCloud<pcl::PointXYZI>::Ptr & cloud,
const pcl::IndicesPtr & indices,
float angleMax,
const Eigen::Vector4f & normal,
int normalKSearch,
const Eigen::Vector4f & viewpoint);
pcl::IndicesPtr RTABMAP_EXP normalFiltering(
const pcl::PointCloud<pcl::PointNormal>::Ptr & cloud,
const pcl::IndicesPtr & indices,
@@ -575,6 +643,13 @@ pcl::IndicesPtr RTABMAP_EXP normalFiltering(
const Eigen::Vector4f & normal,
int normalKSearch,
const Eigen::Vector4f & viewpoint);
pcl::IndicesPtr RTABMAP_EXP normalFiltering(
const pcl::PointCloud<pcl::PointXYZINormal>::Ptr & cloud,
const pcl::IndicesPtr & indices,
float angleMax,
const Eigen::Vector4f & normal,
int normalKSearch,
const Eigen::Vector4f & viewpoint);
/**
* For convenience.
@@ -632,6 +707,20 @@ std::vector<pcl::IndicesPtr> RTABMAP_EXP extractClusters(
int minClusterSize,
int maxClusterSize = std::numeric_limits<int>::max(),
int * biggestClusterIndex = 0);
std::vector<pcl::IndicesPtr> RTABMAP_EXP extractClusters(
const pcl::PointCloud<pcl::PointXYZI>::Ptr & cloud,
const pcl::IndicesPtr & indices,
float clusterTolerance,
int minClusterSize,
int maxClusterSize = std::numeric_limits<int>::max(),
int * biggestClusterIndex = 0);
std::vector<pcl::IndicesPtr> RTABMAP_EXP extractClusters(
const pcl::PointCloud<pcl::PointXYZINormal>::Ptr & cloud,
const pcl::IndicesPtr & indices,
float clusterTolerance,
int minClusterSize,
int maxClusterSize = std::numeric_limits<int>::max(),
int * biggestClusterIndex = 0);
pcl::IndicesPtr RTABMAP_EXP extractIndices(
const pcl::PointCloud<pcl::PointXYZ>::Ptr & cloud,
@@ -649,6 +738,14 @@ pcl::IndicesPtr RTABMAP_EXP extractIndices(
const pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr & cloud,
const pcl::IndicesPtr & indices,
bool negative);
pcl::IndicesPtr RTABMAP_EXP extractIndices(
const pcl::PointCloud<pcl::PointXYZI>::Ptr & cloud,
const pcl::IndicesPtr & indices,
bool negative);
pcl::IndicesPtr RTABMAP_EXP extractIndices(
const pcl::PointCloud<pcl::PointXYZINormal>::Ptr & cloud,
const pcl::IndicesPtr & indices,
bool negative);
pcl::PointCloud<pcl::PointXYZ>::Ptr RTABMAP_EXP extractIndices(
const pcl::PointCloud<pcl::PointXYZ>::Ptr & cloud,
@@ -671,6 +768,16 @@ pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr RTABMAP_EXP extractIndices(
const pcl::IndicesPtr & indices,
bool negative,
bool keepOrganized);
pcl::PointCloud<pcl::PointXYZI>::Ptr RTABMAP_EXP extractIndices(
const pcl::PointCloud<pcl::PointXYZI>::Ptr & cloud,
const pcl::IndicesPtr & indices,
bool negative,
bool keepOrganized);
pcl::PointCloud<pcl::PointXYZINormal>::Ptr RTABMAP_EXP extractIndices(
const pcl::PointCloud<pcl::PointXYZINormal>::Ptr & cloud,
const pcl::IndicesPtr & indices,
bool negative,
bool keepOrganized);
pcl::IndicesPtr extractPlane(
const pcl::PointCloud<pcl::PointXYZ>::Ptr & cloud,
@@ -99,6 +99,21 @@ RTABMAP_DEPRECATED(cv::Mat RTABMAP_EXP create2DMap(const std::map<int, Transform
float minMapSize = 0.0f,
float scanMaxRange = 0.0f), "Use interface with cv::Mat scans.");
/**
* Create 2d Occupancy grid (CV_8S)
* -1 = unknown
* 0 = empty space
* 100 = obstacle
* @param poses
* @param scans, should be CV_32FC2 type!
* @param viewpoints
* @param cellSize m
* @param unknownSpaceFilled if false no fill, otherwise a virtual laser sweeps the unknown space from each pose (stopping on detected obstacle)
* @param xMin
* @param yMin
* @param minMapSize minimum map size in meters
* @param scanMaxRange laser scan maximum range, would be set if unknownSpaceFilled=true
*/
cv::Mat RTABMAP_EXP create2DMap(const std::map<int, Transform> & poses,
const std::map<int, std::pair<cv::Mat, cv::Mat> > & scans, // <id, <hit, no hit> >, in /base_link frame
const std::map<int, cv::Point3f > & viewpoints, // /base_link -> /base_scan
@@ -66,12 +66,25 @@ void RTABMAP_EXP computeVarianceAndCorrespondences(
double maxCorrespondenceAngle, // <=0 means that we don't care about normal angle difference
double & variance,
int & correspondencesOut);
void RTABMAP_EXP computeVarianceAndCorrespondences(
const pcl::PointCloud<pcl::PointXYZINormal>::ConstPtr & cloudA,
const pcl::PointCloud<pcl::PointXYZINormal>::ConstPtr & cloudB,
double maxCorrespondenceDistance,
double maxCorrespondenceAngle, // <=0 means that we don't care about normal angle difference
double & variance,
int & correspondencesOut);
void RTABMAP_EXP computeVarianceAndCorrespondences(
const pcl::PointCloud<pcl::PointXYZ>::ConstPtr & cloudA,
const pcl::PointCloud<pcl::PointXYZ>::ConstPtr & cloudB,
double maxCorrespondenceDistance,
double & variance,
int & correspondencesOut);
void RTABMAP_EXP computeVarianceAndCorrespondences(
const pcl::PointCloud<pcl::PointXYZI>::ConstPtr & cloudA,
const pcl::PointCloud<pcl::PointXYZI>::ConstPtr & cloudB,
double maxCorrespondenceDistance,
double & variance,
int & correspondencesOut);
Transform RTABMAP_EXP icp(
const pcl::PointCloud<pcl::PointXYZ>::ConstPtr & cloud_source,
@@ -82,6 +95,15 @@ Transform RTABMAP_EXP icp(
pcl::PointCloud<pcl::PointXYZ> & cloud_source_registered,
float epsilon = 0.0f,
bool icp2D = false);
Transform RTABMAP_EXP icp(
const pcl::PointCloud<pcl::PointXYZI>::ConstPtr & cloud_source,
const pcl::PointCloud<pcl::PointXYZI>::ConstPtr & cloud_target,
double maxCorrespondenceDistance,
int maximumIterations,
bool & hasConverged,
pcl::PointCloud<pcl::PointXYZI> & cloud_source_registered,
float epsilon = 0.0f,
bool icp2D = false);
Transform RTABMAP_EXP icpPointToPlane(
const pcl::PointCloud<pcl::PointNormal>::ConstPtr & cloud_source,
@@ -92,6 +114,15 @@ Transform RTABMAP_EXP icpPointToPlane(
pcl::PointCloud<pcl::PointNormal> & cloud_source_registered,
float epsilon = 0.0f,
bool icp2D = false);
Transform RTABMAP_EXP icpPointToPlane(
const pcl::PointCloud<pcl::PointXYZINormal>::ConstPtr & cloud_source,
const pcl::PointCloud<pcl::PointXYZINormal>::ConstPtr & cloud_target,
double maxCorrespondenceDistance,
int maximumIterations,
bool & hasConverged,
pcl::PointCloud<pcl::PointXYZINormal> & cloud_source_registered,
float epsilon = 0.0f,
bool icp2D = false);
} // namespace util3d
} // namespace rtabmap
+45 -14
View File
@@ -39,6 +39,7 @@ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#include <rtabmap/core/CameraModel.h>
#include <rtabmap/core/ProgressState.h>
#include <rtabmap/core/LaserScan.h>
#include <rtabmap/core/Version.h>
#include <set>
#include <list>
@@ -148,7 +149,8 @@ pcl::TextureMesh::Ptr RTABMAP_EXP createTextureMesh(
int minClusterSize = 50, // minimum size of polygons clusters textured
const std::vector<float> & roiRatios = std::vector<float>(), // [left, right, top, bottom] region of interest (in ratios) of the image projected.
const ProgressState * state = 0,
std::vector<std::map<int, pcl::PointXY> > * vertexToPixels = 0);
std::vector<std::map<int, pcl::PointXY> > * vertexToPixels = 0, // For each point, we have a list of cameras with corresponding pixel in it. Beware that the camera ids don't correspond to pose ids, they are indexes from 0 to total camera models and texture's materials.
bool distanceToCamPolicy = false);
pcl::TextureMesh::Ptr RTABMAP_EXP createTextureMesh(
const pcl::PolygonMesh::Ptr & mesh,
const std::map<int, Transform> & poses,
@@ -160,7 +162,8 @@ pcl::TextureMesh::Ptr RTABMAP_EXP createTextureMesh(
int minClusterSize = 50, // minimum size of polygons clusters textured
const std::vector<float> & roiRatios = std::vector<float>(), // [left, right, top, bottom] region of interest (in ratios) of the image projected.
const ProgressState * state = 0,
std::vector<std::map<int, pcl::PointXY> > * vertexToPixels = 0);
std::vector<std::map<int, pcl::PointXY> > * vertexToPixels = 0, // For each point, we have a list of cameras with corresponding pixel in it. Beware that the camera ids don't correspond to pose ids, they are indexes from 0 to total camera models and texture's materials.
bool distanceToCamPolicy = false);
/**
* Remove not textured polygon clusters. If minClusterSize<0, only the largest cluster is kept.
@@ -175,18 +178,18 @@ pcl::TextureMesh::Ptr RTABMAP_EXP concatenateTextureMeshes(
void RTABMAP_EXP concatenateTextureMaterials(
pcl::TextureMesh & mesh, const cv::Size & imageSize, int textureSize, int maxTextures, float & scale, std::vector<bool> * materialsKept=0);
std::vector<std::vector<unsigned int> > RTABMAP_EXP convertPolygonsFromPCL(
std::vector<std::vector<RTABMAP_PCL_INDEX> > RTABMAP_EXP convertPolygonsFromPCL(
const std::vector<pcl::Vertices> & polygons);
std::vector<std::vector<std::vector<unsigned int> > > RTABMAP_EXP convertPolygonsFromPCL(
std::vector<std::vector<std::vector<RTABMAP_PCL_INDEX> > > RTABMAP_EXP convertPolygonsFromPCL(
const std::vector<std::vector<pcl::Vertices> > & polygons);
std::vector<pcl::Vertices> RTABMAP_EXP convertPolygonsToPCL(
const std::vector<std::vector<unsigned int> > & polygons);
const std::vector<std::vector<RTABMAP_PCL_INDEX> > & polygons);
std::vector<std::vector<pcl::Vertices> > RTABMAP_EXP convertPolygonsToPCL(
const std::vector<std::vector<std::vector<unsigned int> > > & tex_polygons);
const std::vector<std::vector<std::vector<RTABMAP_PCL_INDEX> > > & tex_polygons);
pcl::TextureMesh::Ptr RTABMAP_EXP assembleTextureMesh(
const cv::Mat & cloudMat,
const std::vector<std::vector<std::vector<unsigned int> > > & polygons,
const std::vector<std::vector<std::vector<RTABMAP_PCL_INDEX> > > & polygons,
#if PCL_VERSION_COMPARE(>=, 1, 8, 0)
const std::vector<std::vector<Eigen::Vector2f, Eigen::aligned_allocator<Eigen::Vector2f> > > & texCoords,
#else
@@ -197,7 +200,7 @@ pcl::TextureMesh::Ptr RTABMAP_EXP assembleTextureMesh(
pcl::PolygonMesh::Ptr RTABMAP_EXP assemblePolygonMesh(
const cv::Mat & cloudMat,
const std::vector<std::vector<unsigned int> > & polygons);
const std::vector<std::vector<RTABMAP_PCL_INDEX> > & polygons);
/**
* Merge all textures in the mesh into "textureCount" textures of size "textureSize".
@@ -263,8 +266,9 @@ bool RTABMAP_EXP multiBandTexturing(
int textureSize = 8192,
const std::string & textureFormat = "jpg", // png, jpg
const std::map<int, std::map<int, cv::Vec4d> > & gains = std::map<int, std::map<int, cv::Vec4d> >(), // optional output of util3d::mergeTextures()
const std::map<int, std::map<int, cv::Mat> > & blendingGains = std::map<int, std::map<int, cv::Mat> >(), // optional output of util3d::mergeTextures()
const std::pair<float, float> & contrastValues = std::pair<float, float>(0,0)); // optional output of util3d::mergeTextures()
const std::map<int, std::map<int, cv::Mat> > & blendingGains = std::map<int, std::map<int, cv::Mat> >(), // optional output of util3d::mergeTextures()
const std::pair<float, float> & contrastValues = std::pair<float, float>(0,0), // optional output of util3d::mergeTextures()
bool gainRGB = true);
cv::Mat RTABMAP_EXP computeNormals(
const cv::Mat & laserScan,
@@ -354,6 +358,12 @@ float RTABMAP_EXP computeNormalsComplexity(
bool is2d = false,
cv::Mat * pcaEigenVectors = 0,
cv::Mat * pcaEigenValues = 0);
float RTABMAP_EXP computeNormalsComplexity(
const pcl::PointCloud<pcl::PointXYZINormal> & cloud,
const Transform & t = Transform::getIdentity(),
bool is2d = false,
cv::Mat * pcaEigenVectors = 0,
cv::Mat * pcaEigenValues = 0);
float RTABMAP_EXP computeNormalsComplexity(
const pcl::PointCloud<pcl::PointXYZRGBNormal> & cloud,
const Transform & t = Transform::getIdentity(),
@@ -383,18 +393,39 @@ pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr RTABMAP_EXP mls(
float dilationVoxelSize = 1.0f, // VOXEL_GRID_DILATION
int dilationIterations = 0); // VOXEL_GRID_DILATION
LaserScan RTABMAP_EXP adjustNormalsToViewPoint(
RTABMAP_DEPRECATED(LaserScan RTABMAP_EXP adjustNormalsToViewPoint(
const LaserScan & scan,
const Eigen::Vector3f & viewpoint,
bool forceGroundNormalsUp);
bool forceGroundNormalsUp), "Use version with groundNormalsUp as float. For forceGroundNormalsUp=true, set groundNormalsUp to 0.8f, otherwise set groundNormalsUp to 0.0f.");
LaserScan RTABMAP_EXP adjustNormalsToViewPoint(
const LaserScan & scan,
const Eigen::Vector3f & viewpoint = Eigen::Vector3f(0,0,0),
float groundNormalsUp = 0.0f);
RTABMAP_DEPRECATED(void RTABMAP_EXP adjustNormalsToViewPoint(
pcl::PointCloud<pcl::PointNormal>::Ptr & cloud,
const Eigen::Vector3f & viewpoint,
bool forceGroundNormalsUp), "Use version with groundNormalsUp as float. For forceGroundNormalsUp=true, set groundNormalsUp to 0.8f, otherwise set groundNormalsUp to 0.0f.");
void RTABMAP_EXP adjustNormalsToViewPoint(
pcl::PointCloud<pcl::PointNormal>::Ptr & cloud,
const Eigen::Vector3f & viewpoint = Eigen::Vector3f(0,0,0),
bool forceGroundNormalsUp = false);
float groundNormalsUp = 0.0f);
RTABMAP_DEPRECATED(void RTABMAP_EXP adjustNormalsToViewPoint(
pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr & cloud,
const Eigen::Vector3f & viewpoint,
bool forceGroundNormalsUp), "Use version with groundNormalsUp as float. For forceGroundNormalsUp=true, set groundNormalsUp to 0.8f, otherwise set groundNormalsUp to 0.0f.");
void RTABMAP_EXP adjustNormalsToViewPoint(
pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr & cloud,
const Eigen::Vector3f & viewpoint = Eigen::Vector3f(0,0,0),
bool forceGroundNormalsUp = false);
float groundNormalsUp = 0.0f);
RTABMAP_DEPRECATED(void RTABMAP_EXP adjustNormalsToViewPoint(
pcl::PointCloud<pcl::PointXYZINormal>::Ptr & cloud,
const Eigen::Vector3f & viewpoint,
bool forceGroundNormalsUp), "Use version with groundNormalsUp as float. For forceGroundNormalsUp=true, set groundNormalsUp to 0.8f, otherwise set groundNormalsUp to 0.0f.");
void RTABMAP_EXP adjustNormalsToViewPoint(
pcl::PointCloud<pcl::PointXYZINormal>::Ptr & cloud,
const Eigen::Vector3f & viewpoint = Eigen::Vector3f(0,0,0),
float groundNormalsUp = 0.0f);
void RTABMAP_EXP adjustNormalsToViewPoints(
const std::map<int, Transform> & poses,
const pcl::PointCloud<pcl::PointXYZ>::Ptr & rawCloud,

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