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* added doc and tests for util2d.h * updated cmake-ros ci * Added util3d.h doc and tests * util3d_transforms.h: Added doc and tests * util3d_filtering.h: started doc and test * util3d_filtering.h: more tests and doc * Added more doc/tests * finished util3d_filtering doc and tests * added test for util2d::depthBleedingFiltering * Added util3d_registration tests * Added util3d_features.h doc/tests * added doc/tests for util3d_correspondences.h * added doc/gtest for util3d_mapping.h (missing hpp functions) * finished testing util3d_mapping.hpp * Added util3d_motion_estimation.h tests (2D->3D done) * finished util3d_motion_estimation.h tests * minimal util3d_surface.h * Added Transform and VisualWord tests * Added doc for CameraModel and StereoCameraModel * Added more logs in ros ci * Passing tests on fical * improved all devcontainer * added devcontainer kilted, fixed source setup.bash, removed ldconfig in ros-cmake workflow * cleanup * source ros * Added utilite tests * Added testing to appveyor, github actions cancellable on re-commit on same branch * appveyor testing without all targets * appveyor: specifying ALL_BUILD target * Fixed Util2dTest.NMSImageBoundsRespected test * Fixing PCL Indices error on old pcl * Added VWDictionary tests and doc. Fixed LSH not working (fix from https://github.com/flann-lib/flann/pull/472 * fixing some appveyor CI errors, added test to check dictionary serialization against all type * Added StereoDense, StereoBM and StereoSGBM doc and tests * Added Stereo tests * Added CameraModel and StereoCameraModel tests * Added doc and test for Statistics * Added doc/tests for Signature * Added doc/test for SensorEvent, added doc for SensorCaptureInfo * Added doc to SensorData * Added SensorData tests * Added SensorCapture and SensorCaptureThread doc and tests * fixed sensordata test * updated SSC test and doc * Added doc and tests for BayesFilter class * Enabled testing on mac, updated windows testing like on linux * added test_link * fixed unresolved on windows * fixed ThreadHandle error on macos ci * Added GPS and GeodeticCoords tests * Added tests for compression * Added Odometry tests (base class only) * Added DBDriver tests * Added coverage report * uniformized test names * fixing concurancy and coverage ci * dont built tools, examples and app for coverage build * fixed report tool rebuilt without qt compilation error * updated coverage option * updated coverage config * added doc CI job * fixing windows and mac ci errors * Added DBDriverSqlite3 tests * Added IMU tests * Added Graph tests * fixing flaky macos test * Added IMUThread and IMUFilter tests * Added Landmarks tests * Added LASWriter tests * fixing seed flaky test * fixing flaky macos timing tests * Added LocalGrid tests * Added LocalGridMaker tests * fixing ci errors * Added GlobalMap tests * Added doc for EnvSensor * Added Features2D tests * Added Registration tests * Added RegistrationVis tests * Added doc for Rtabmap and Memory classes * Added Memory and Rtabmap tests * making some tests less flaky * lcov 1.14 support * updated compatible tool arguments * Added integration tests (RGB-D, Stereo, Lidar2d, Lidar3d) * More octomap checks * Refactored how/when python interpretor is created to simplify library usage * Added python tests * fixed some flaky tests * suppressed some third party related warnings * fixed ceres tests * more flaky fixes * Fixing tests without libpointmatcher * Added RANSAC rejection filter to PCL ICP * fixing multi platform flakiness * Added test to detect regression * Fixing windows pcl link error * fixed some macos flakiness * bigger 2D2D registration error on opencv 4.6.0 * flakiness * fixing flaky tests on windows and mac * flaky thread test on slow mac VM * windows slow test * fixing more ci erros * fxing temp dir on windows * Added Optimizer tests and discovered some bugs (fixed) * fixing flaky tests in mac and windows * Added Optimizer doc * Added GTSAM BA, updated Ceres to use g2o ba parameters. Renamed g2o's ba related parameters to Optimizer group and used by both gtsam and ceres. * fixing build without gtsam * fixing home dir * fixing python ci isssues * Added multicam ba tests * Added Ceres multicam BA support * Aligned BundleAdjustment parameters with Optimizer/Strategy to avoid confusion in the code * Added BA integration test * Added robust graph optimization integration test * Added loop3it test * Added stereo20Hz test * Added smartfactor gtsam * Fixed bugged check and warn if python didn't return any descriptors * Fixing gtsam version build issues * fixing tilt on windows ci * loosing ceres integration test for ci * mac ci flakiness * updating missing param in gui * updating test bound for mac * added appearance-based tests, set min gftt quality to quality level * testing more stuff * improving features2d tests * ci flakiness * fixing flaky ci * ci fixes * flaky fixes * Added RegistrationIcp tests * Added icp integration test with real-worl corridor like env * intermediate nodes * fixing enum * Updated test to catch #1714 * Fixed 2d corridor failing on pcl * flaky pnp test * flaky brisk test * Set rtabmap_integration test as long * updating loop closure test * flaky ci tests * TEsting roundtrip g2o/toro save/load * loosing test bound * fixed cuda capable checks * flaky tests * Debugging test hanging * more debugging stuff * updating limit * windows: disabled cuda on ci to avoid incompatible driver issue. Fixing a bad test mem allocation * trying fixing cuda hanging issue * fixing ci flakyness * flaky tests * Updated BOW flaky tests by checking min precision/recall instead of recall@100precision. Fixed signature test * CameraModel::load() test initRectificationMap param * test dbdriver load dictionary idsOnly * Memory: test keepLinkedInDb param * added dummyDictionary tests * test intermediate nodes count * Added MarkerDetector tests * reverted breaking change of UMutex and USemaphore * Features2d: fixed compiltion warnings with clang about override * clang warnings * fixing test build with pcl 1.8 * g2o and gtsam build errors on android * opencv5 test fixes * disabled testing for ios and android builds * normalized endline characters for easier diff * added LF CRLF rule * bump 0.23.10. fixing doc version * Publish rtabmap website doc from ci * fixing MSCVC build error * macos icp flaky test * fixing ceres macos test bound * ficing more flaky tests * fixing opencv5 related test errors. Also fixed an actual bug in ENU_WGS84ToGeocentric_WGS84() * added comment about mrpt change * removed rosdoc2 (will add it for rtabmap_ros later) * fixing website style * updated download links * locally deployable website with api * sweep doxygen issues * improved/revised doxygen main pages * removed examples empty page * Updated doxygen style * more concise doxygen groups * added api link on main readme * fixing utilite test error * fixing CommonFilteringGroundNormalsUp test * updated precisionRecall test bounds for Freak and brief descriptors * fixing scale check in ba tests * disabled tests on windows cuda build (missing dlls amd runner cannot test cuda anyway) * ceres: missing suitesparse dep in windows ci * adjusting recall thr for fast/freak * ficing more flaky tests * fixing flaky tests * disabled coverage in ros ci * Enable integration tests for ros ci jobs * loosing up some threshold for failing tests * trigger cache * fixing test data in ros ci. Updated flaky test for mac * slaking some test limit * Fixed rtabmap-detectMoreLoopClosures inverted output value * loosing up sift recall on mac * optimizer re-ordered distribution for reproducible results (mac g2o) * macos dump test crash log * combining all tests to save time on shared library reload. Also fixed Logs with missing arguments. * Added ENABLE_FORMAT_ERRORS cmake option * do test only one time * fixed all format warnings * format security android build errors * less verbose tests * updated ImuUThread test * fixed a log * Fixed libpointmatcher 2d normals eigen issue * Fixing libpointmatcher conversion issues * fixing libpointmatcher test on windows ci * cleanup comments, relax some test thr * disabled sequoia-intel ci build (too flaky, would need extensive testing directly on that machine)
886 lines
28 KiB
C++
886 lines
28 KiB
C++
/*
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Copyright (c) 2010-2016, Mathieu Labbe - IntRoLab - Universite de Sherbrooke
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All rights reserved.
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Redistribution and use in source and binary forms, with or without
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modification, are permitted provided that the following conditions are met:
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* Redistributions of source code must retain the above copyright
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notice, this list of conditions and the following disclaimer.
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* Redistributions in binary form must reproduce the above copyright
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notice, this list of conditions and the following disclaimer in the
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documentation and/or other materials provided with the distribution.
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* Neither the name of the Universite de Sherbrooke nor the
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names of its contributors may be used to endorse or promote products
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derived from this software without specific prior written permission.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
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ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
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WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY
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DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
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(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
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ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*/
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#include <rtabmap/core/SensorEvent.h>
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#include "rtabmap/core/DBReader.h"
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#include "rtabmap/core/DBDriver.h"
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#include <rtabmap/utilite/ULogger.h>
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#include <rtabmap/utilite/UFile.h>
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#include <rtabmap/utilite/UStl.h>
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#include <rtabmap/utilite/UConversion.h>
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#include <rtabmap/utilite/UEventsManager.h>
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#include "rtabmap/core/RtabmapEvent.h"
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#include "rtabmap/core/OdometryEvent.h"
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#include "rtabmap/core/util3d.h"
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#include "rtabmap/core/Compression.h"
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namespace rtabmap {
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DBReader::DBReader(const std::string & databasePath,
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float frameRate,
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bool odometryIgnored,
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bool ignoreGoalDelay,
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bool goalsIgnored,
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int startId,
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const std::vector<unsigned int> & cameraIndices,
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int stopId,
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bool intermediateNodesIgnored,
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bool landmarksIgnored,
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bool featuresIgnored,
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int startMapId,
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int stopMapId,
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bool priorsIgnored,
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bool imuIgnored,
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bool intermediateNodesAreNormalNodes,
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const std::vector<Transform> & cameraLocalTransformOverrides) :
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Camera(frameRate),
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_paths(uSplit(databasePath, ';')),
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_odometryIgnored(odometryIgnored),
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_ignoreGoalDelay(ignoreGoalDelay),
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_goalsIgnored(goalsIgnored),
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_startId(startId),
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_stopId(stopId),
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_cameraIndices(cameraIndices),
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_intermediateNodesIgnored(intermediateNodesIgnored),
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_intermediateNodesAreNormalNodes(intermediateNodesAreNormalNodes),
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_landmarksIgnored(landmarksIgnored),
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_featuresIgnored(featuresIgnored),
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_priorsIgnored(priorsIgnored),
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_imuIgnored(imuIgnored),
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_startMapId(startMapId),
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_stopMapId(stopMapId),
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_cameraLocalTransformOverrides(cameraLocalTransformOverrides),
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_dbDriver(0),
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_currentId(_ids.end()),
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_previousMapId(-1),
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_previousStamp(0),
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_previousMapID(0),
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_calibrated(false)
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{
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checkArguments();
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}
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DBReader::DBReader(const std::list<std::string> & databasePaths,
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float frameRate,
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bool odometryIgnored,
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bool ignoreGoalDelay,
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bool goalsIgnored,
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int startId,
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const std::vector<unsigned int> & cameraIndices,
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int stopId,
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bool intermediateNodesIgnored,
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bool landmarksIgnored,
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bool featuresIgnored,
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int startMapId,
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int stopMapId,
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bool priorsIgnored,
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bool imuIgnored,
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bool intermediateNodesAreNormalNodes,
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const std::vector<Transform> & cameraLocalTransformOverrides) :
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Camera(frameRate),
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_paths(databasePaths),
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_odometryIgnored(odometryIgnored),
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_ignoreGoalDelay(ignoreGoalDelay),
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_goalsIgnored(goalsIgnored),
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_startId(startId),
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_stopId(stopId),
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_cameraIndices(cameraIndices),
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_intermediateNodesIgnored(intermediateNodesIgnored),
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_intermediateNodesAreNormalNodes(intermediateNodesAreNormalNodes),
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_landmarksIgnored(landmarksIgnored),
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_featuresIgnored(featuresIgnored),
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_priorsIgnored(priorsIgnored),
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_imuIgnored(imuIgnored),
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_startMapId(startMapId),
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_stopMapId(stopMapId),
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_cameraLocalTransformOverrides(cameraLocalTransformOverrides),
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_dbDriver(0),
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_currentId(_ids.end()),
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_previousMapId(-1),
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_previousStamp(0),
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_previousMapID(0),
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_calibrated(false)
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{
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checkArguments();
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}
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void DBReader::checkArguments()
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{
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if(_stopId>0 && _stopId<_startId)
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{
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_stopId = _startId;
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}
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if(_stopMapId>-1 && _stopMapId<_startMapId)
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{
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_stopMapId = _startMapId;
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}
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if(!_cameraLocalTransformOverrides.empty())
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{
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if(!_cameraIndices.empty() &&
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_cameraIndices.size() != _cameraLocalTransformOverrides.size())
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{
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UERROR("Camera local transform overrides (%d) are not the same size than the camera indices (%d). The overrides are ignored.",
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(int)_cameraLocalTransformOverrides.size(),
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(int)_cameraIndices.size());
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_cameraLocalTransformOverrides.clear();
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}
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for(size_t i=0; i<_cameraLocalTransformOverrides.size(); ++i)
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{
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if(_cameraLocalTransformOverrides[i].isNull())
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{
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UERROR("Camera local transform overrides vector cannot contains null transforms! Clearing overrides.");
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_cameraLocalTransformOverrides.clear();
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break;
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}
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}
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}
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}
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DBReader::~DBReader()
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{
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if(_dbDriver)
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{
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_dbDriver->closeConnection();
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delete _dbDriver;
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}
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}
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bool DBReader::init(
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const std::string &,
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const std::string &)
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{
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if(_dbDriver)
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{
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_dbDriver->closeConnection();
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delete _dbDriver;
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_dbDriver = 0;
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}
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_ids.clear();
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_currentId=_ids.end();
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_previousMapId = -1;
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_previousInfMatrix = cv::Mat();
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_previousStamp = 0;
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_previousMapID = 0;
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_calibrated = false;
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if(_paths.size() == 0)
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{
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UERROR("No database path set...");
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return false;
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}
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std::string path = _paths.front();
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if(!UFile::exists(path))
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{
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UERROR("Database path does not exist (%s)", path.c_str());
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return false;
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}
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rtabmap::ParametersMap parameters;
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parameters.insert(rtabmap::ParametersPair(rtabmap::Parameters::kDbSqlite3InMemory(), "false"));
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_dbDriver = DBDriver::create(parameters);
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if(!_dbDriver)
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{
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UERROR("Driver doesn't exist.");
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return false;
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}
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if(!_dbDriver->openConnection(path))
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{
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UERROR("Can't open database %s", path.c_str());
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delete _dbDriver;
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_dbDriver = 0;
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return false;
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}
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_dbDriver->getAllNodeIds(_ids);
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_currentId = _ids.begin();
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if(_startId>0 && _ids.size())
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{
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std::set<int>::iterator iter = _ids.find(_startId);
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if(iter == _ids.end())
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{
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UWARN("Start index is too high (%d), the last ID in database is %d. Starting from beginning...", _startId, *_ids.rbegin());
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}
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else
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{
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_currentId = iter;
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}
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}
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if(_ids.size())
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{
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std::vector<CameraModel> models;
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std::vector<StereoCameraModel> stereoModels;
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if(_dbDriver->getCalibration(*_ids.begin(), models, stereoModels))
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{
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if(models.size())
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{
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if(models.at(0).isValidForProjection())
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{
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_calibrated = true;
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}
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else if(models.at(0).fx() && models.at(0).fy() && models.at(0).imageWidth() == 0)
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{
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// backward compatibility for databases not saving cx,cy and imageSize
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SensorData data;
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_dbDriver->getNodeData(*_ids.begin(), data, true, false, false, false);
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cv::Mat rgb;
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data.uncompressData(&rgb, 0); // this will update camera models if old format
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if(data.cameraModels().size() && data.cameraModels().at(0).isValidForProjection())
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{
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_calibrated = true;
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}
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}
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}
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else if(stereoModels.size() && stereoModels.at(0).isValidForProjection())
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{
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_calibrated = true;
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}
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else
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{
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Signature * s = _dbDriver->loadSignature(*_ids.begin());
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_dbDriver->loadNodeData(*s);
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if( s->sensorData().imageCompressed().empty() &&
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s->getWords().empty() &&
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!s->sensorData().laserScanCompressed().empty())
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{
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_calibrated = true; // only scans
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}
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delete s;
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}
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}
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}
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else
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{
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_calibrated = true; // database is empty, make sure calibration warning is not shown.
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}
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_timer.start();
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return true;
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}
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bool DBReader::isCalibrated() const
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{
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return _calibrated;
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}
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std::string DBReader::getSerial() const
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{
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return "DBReader";
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}
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bool DBReader::getPose(double stamp, Transform & pose, cv::Mat & covariance, double maxWaitTime)
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{
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UERROR("DBReader only provides pose when capturing data, it cannot provide asynchronous pose.");
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return false;
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}
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SensorData DBReader::captureImage(SensorCaptureInfo * info)
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{
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SensorData data = this->getNextData(info);
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if(data.id()>0 && _stopId>0 && data.id() > _stopId)
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{
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UINFO("Last ID %d has been reached! Ignoring", _stopId);
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return SensorData();
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}
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if(data.id() == 0)
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{
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UINFO("no more images...");
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while(_paths.size() > 1 && data.id() == 0)
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{
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_paths.pop_front();
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UWARN("Loading next database \"%s\"...", _paths.front().c_str());
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if(!this->init())
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{
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UERROR("Failed to initialize the next database \"%s\"", _paths.front().c_str());
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return data;
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}
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else
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{
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data = this->getNextData(info);
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}
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}
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}
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if(data.id())
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{
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std::string goalId;
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double previousStamp = data.stamp();
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if(previousStamp == 0)
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{
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data.setStamp(UTimer::now());
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}
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if(!_goalsIgnored &&
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data.userDataRaw().type() == CV_8SC1 &&
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data.userDataRaw().cols >= 7 && // including null str ending
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data.userDataRaw().rows == 1 &&
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memcmp(data.userDataRaw().data, "GOAL:", 5) == 0)
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{
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//GOAL format detected, remove it from the user data and send it as goal event
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std::string goalStr = (const char *)data.userDataRaw().data;
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if(!goalStr.empty())
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{
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std::list<std::string> strs = uSplit(goalStr, ':');
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if(strs.size() == 2)
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{
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goalId = *strs.rbegin();
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data.setUserData(cv::Mat());
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double delay = 0.0;
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if(!_ignoreGoalDelay && _currentId != _ids.end())
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{
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// get stamp for the next signature to compute the delay
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// that was used originally for planning
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int weight;
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std::string label;
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double stamp;
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int mapId;
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Transform localTransform, pose, groundTruth;
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std::vector<float> velocity;
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GPS gps;
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EnvSensors sensors;
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_dbDriver->getNodeInfo(*_currentId, pose, mapId, weight, label, stamp, groundTruth, velocity, gps, sensors);
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if(previousStamp && stamp && stamp > previousStamp)
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{
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delay = stamp - previousStamp;
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}
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}
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if(delay > 0.0)
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{
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UWARN("Goal \"%s\" detected, posting it! Waiting %f seconds before sending next data...",
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goalId.c_str(), delay);
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}
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else
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{
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UWARN("Goal \"%s\" detected, posting it!", goalId.c_str());
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}
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if(uIsInteger(goalId))
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{
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UEventsManager::post(new RtabmapEventCmd(RtabmapEventCmd::kCmdGoal, atoi(goalId.c_str())));
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}
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else
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{
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UEventsManager::post(new RtabmapEventCmd(RtabmapEventCmd::kCmdGoal, goalId));
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}
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if(delay > 0.0)
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{
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uSleep(delay*1000);
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}
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}
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}
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}
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}
|
|
return data;
|
|
}
|
|
|
|
SensorData DBReader::getNextData(SensorCaptureInfo * info)
|
|
{
|
|
SensorData data;
|
|
if(_dbDriver)
|
|
{
|
|
while(_currentId != _ids.end())
|
|
{
|
|
std::list<int> signIds;
|
|
signIds.push_back(*_currentId);
|
|
std::list<Signature *> signatures;
|
|
_dbDriver->loadSignatures(signIds, signatures);
|
|
if(signatures.empty())
|
|
{
|
|
return data;
|
|
}
|
|
_dbDriver->loadNodeData(signatures);
|
|
Signature * s = signatures.front();
|
|
|
|
if(_intermediateNodesIgnored && s->getWeight() == -1)
|
|
{
|
|
UDEBUG("Ignoring node %d (intermediate nodes ignored)", s->id());
|
|
++_currentId;
|
|
delete s;
|
|
continue;
|
|
}
|
|
|
|
if(s->mapId() < _startMapId || (_stopMapId>=0 && s->mapId() > _stopMapId))
|
|
{
|
|
UDEBUG("Ignoring node %d (map id=%d, min=%d max=%d)", s->id(), s->mapId(), _startMapId, _stopMapId);
|
|
++_currentId;
|
|
delete s;
|
|
continue;
|
|
}
|
|
|
|
data = s->sensorData();
|
|
|
|
// info
|
|
Transform pose = s->getPose();
|
|
Transform globalPose;
|
|
cv::Mat globalPoseCov;
|
|
|
|
std::multimap<int, Link> priorLinks;
|
|
if(!_priorsIgnored)
|
|
{
|
|
_dbDriver->loadLinks(*_currentId, priorLinks, Link::kPosePrior);
|
|
if( priorLinks.size() &&
|
|
!priorLinks.begin()->second.transform().isNull() &&
|
|
priorLinks.begin()->second.infMatrix().cols == 6 &&
|
|
priorLinks.begin()->second.infMatrix().rows == 6)
|
|
{
|
|
globalPose = priorLinks.begin()->second.transform();
|
|
globalPoseCov = priorLinks.begin()->second.infMatrix().inv();
|
|
if(data.gps().stamp() != 0.0 &&
|
|
globalPoseCov.at<double>(3,3)>=9999 &&
|
|
globalPoseCov.at<double>(4,4)>=9999 &&
|
|
globalPoseCov.at<double>(5,5)>=9999)
|
|
{
|
|
// clear global pose as GPS was used for prior
|
|
globalPose.setNull();
|
|
}
|
|
}
|
|
}
|
|
|
|
Transform gravityTransform;
|
|
if(!_imuIgnored)
|
|
{
|
|
std::multimap<int, Link> gravityLinks;
|
|
_dbDriver->loadLinks(*_currentId, gravityLinks, Link::kGravity);
|
|
if( gravityLinks.size() &&
|
|
!gravityLinks.begin()->second.transform().isNull() &&
|
|
gravityLinks.begin()->second.infMatrix().cols == 6 &&
|
|
gravityLinks.begin()->second.infMatrix().rows == 6)
|
|
{
|
|
gravityTransform = gravityLinks.begin()->second.transform();
|
|
}
|
|
}
|
|
|
|
Landmarks landmarks;
|
|
if(!_landmarksIgnored)
|
|
{
|
|
std::multimap<int, Link> landmarkLinks;
|
|
_dbDriver->loadLinks(*_currentId, landmarkLinks, Link::kLandmark);
|
|
for(std::multimap<int, Link>::iterator iter=landmarkLinks.begin(); iter!=landmarkLinks.end(); ++iter)
|
|
{
|
|
cv::Mat landmarkSize = iter->second.uncompressUserDataConst();
|
|
landmarks.insert(std::make_pair(-iter->first,
|
|
Landmark(-iter->first,
|
|
!landmarkSize.empty() && landmarkSize.type() == CV_32FC1 && landmarkSize.total()==1?landmarkSize.at<float>(0,0):0.0f,
|
|
iter->second.transform(),
|
|
iter->second.infMatrix().inv())));
|
|
}
|
|
}
|
|
|
|
cv::Mat infMatrix = cv::Mat::eye(6,6,CV_64FC1);
|
|
if(!_odometryIgnored)
|
|
{
|
|
std::multimap<int, Link> links;
|
|
_dbDriver->loadLinks(*_currentId, links, Link::kNeighbor);
|
|
if(links.size() && links.begin()->first < *_currentId)
|
|
{
|
|
// assume the first is the backward neighbor, take its variance
|
|
infMatrix = links.begin()->second.infMatrix();
|
|
_previousInfMatrix = infMatrix;
|
|
}
|
|
else
|
|
{
|
|
if(_previousMapId != s->mapId())
|
|
{
|
|
// first node, set high variance to make rtabmap trigger a new map
|
|
infMatrix /= 9999.0;
|
|
UDEBUG("First node of map %d, variance set to 9999", s->mapId());
|
|
}
|
|
else
|
|
{
|
|
// In case the graph was reduced, look for forward neighbor link from previous id
|
|
bool covAdded = false;
|
|
if(_currentId != _ids.begin()) {
|
|
std::set<int>::iterator previousId = _currentId;
|
|
--previousId;
|
|
std::multimap<int, Link> previousLinks;
|
|
_dbDriver->loadLinks(*previousId, previousLinks, Link::kNeighbor);
|
|
if(previousLinks.size() && previousLinks.rbegin()->first == *_currentId)
|
|
{
|
|
// assume the last is the forward neighbor pointing to current ID, take its covariance
|
|
infMatrix = previousLinks.rbegin()->second.infMatrix();
|
|
_previousInfMatrix = infMatrix;
|
|
covAdded = true;
|
|
}
|
|
}
|
|
|
|
if(!covAdded) {
|
|
// if localization data saved in database, covariance will be set in a prior link
|
|
_dbDriver->loadLinks(*_currentId, links, Link::kPosePrior);
|
|
if(links.size())
|
|
{
|
|
// assume the first is the backward neighbor, take its variance
|
|
infMatrix = links.begin()->second.infMatrix();
|
|
_previousInfMatrix = infMatrix;
|
|
}
|
|
else
|
|
{
|
|
if(_previousInfMatrix.empty())
|
|
{
|
|
_previousInfMatrix = cv::Mat::eye(6,6,CV_64FC1);
|
|
}
|
|
// we have a node not linked to map, use last variance
|
|
UWARN("The node loaded (%d) doesn't have neighbor, re-using the covariance of the previous link for odometry.", s->id());
|
|
infMatrix = _previousInfMatrix;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
_previousMapId = s->mapId();
|
|
}
|
|
else
|
|
{
|
|
pose.setNull();
|
|
}
|
|
|
|
int seq = *_currentId;
|
|
++_currentId;
|
|
|
|
// Frame rate
|
|
if(this->getImageRate() < 0.0f)
|
|
{
|
|
if(s->getStamp() == 0)
|
|
{
|
|
UERROR("The option to use database stamps is set (framerate<0), but there are no stamps saved in the database! Aborting...");
|
|
delete s;
|
|
return data;
|
|
}
|
|
else if(_previousMapID == s->mapId() && _previousStamp > 0)
|
|
{
|
|
float ratio = -this->getImageRate();
|
|
int sleepTime = 1000.0*(s->getStamp()-_previousStamp)/ratio - 1000.0*_timer.getElapsedTime();
|
|
double stamp = s->getStamp();
|
|
if(sleepTime > 10000)
|
|
{
|
|
UWARN("Detected long delay (%d sec, stamps = %f vs %f). Waiting a maximum of 10 seconds.",
|
|
sleepTime/1000, _previousStamp, s->getStamp());
|
|
sleepTime = 10000;
|
|
stamp = _previousStamp+10;
|
|
}
|
|
if(sleepTime > 2)
|
|
{
|
|
uSleep(sleepTime-2);
|
|
}
|
|
|
|
// Add precision at the cost of a small overhead
|
|
while(_timer.getElapsedTime() < (stamp-_previousStamp)/ratio-0.000001)
|
|
{
|
|
//
|
|
}
|
|
|
|
double slept = _timer.getElapsedTime();
|
|
_timer.start();
|
|
UDEBUG("slept=%fs vs target=%fs (ratio=%f)", slept, (stamp-_previousStamp)/ratio, ratio);
|
|
}
|
|
_previousStamp = s->getStamp();
|
|
_previousMapID = s->mapId();
|
|
}
|
|
|
|
data.uncompressData();
|
|
std::map<int, int> cameraOldNewIndices;
|
|
std::vector<CameraModel> dbModels = data.cameraModels();
|
|
if(dbModels.empty() && !data.stereoCameraModels().empty())
|
|
{
|
|
for(size_t i=0; i<data.stereoCameraModels().size(); ++i)
|
|
{
|
|
dbModels.push_back(data.stereoCameraModels()[i].left());
|
|
}
|
|
}
|
|
|
|
if(!_cameraLocalTransformOverrides.empty() &&
|
|
!_cameraIndices.empty() &&
|
|
_cameraIndices.size() != _cameraLocalTransformOverrides.size())
|
|
{
|
|
UERROR("Camera local transform overrides (%d) are not the same size than the camera indices (%d). The overrides are ignored.",
|
|
(int)_cameraLocalTransformOverrides.size(),
|
|
(int)_cameraIndices.size());
|
|
_cameraLocalTransformOverrides.clear();
|
|
}
|
|
|
|
std::vector<Transform> combinedLocalTransforms;
|
|
if(dbModels.size() > 1 && !_cameraIndices.empty())
|
|
{
|
|
// update images and local transforms
|
|
cv::Mat combinedImages;
|
|
cv::Mat combinedDepthImages;
|
|
cv::Mat combinedDepthConfidenceImages;
|
|
std::vector<CameraModel> combinedModels;
|
|
std::vector<StereoCameraModel> combinedStereoModels;
|
|
for(size_t i=0; i<_cameraIndices.size(); ++i)
|
|
{
|
|
UASSERT_MSG(_cameraIndices[i] < dbModels.size(), uFormat("DBReader: camera index %ld is not valid (should be between 0 and %ld)",
|
|
(long)_cameraIndices[i], dbModels.size()-1).c_str());
|
|
|
|
int addedCameras = std::max(combinedModels.size(), combinedStereoModels.size());
|
|
|
|
int subImageWidth = data.imageRaw().cols/dbModels.size();
|
|
UASSERT(!data.imageRaw().empty() &&
|
|
data.imageRaw().cols % dbModels.size() == 0 &&
|
|
(int)_cameraIndices[i]*subImageWidth < data.imageRaw().cols);
|
|
if(combinedImages.empty())
|
|
{
|
|
// initialize with first camera
|
|
combinedImages = cv::Mat(data.imageRaw().rows, subImageWidth*(_cameraIndices.size()-i), data.imageRaw().type());
|
|
}
|
|
|
|
cv::Mat fromROI = cv::Mat(data.imageRaw(), cv::Rect(_cameraIndices[i]*subImageWidth, 0, subImageWidth, data.imageRaw().rows));
|
|
cv::Mat toROI = cv::Mat(combinedImages, cv::Rect(addedCameras*subImageWidth, 0, subImageWidth, combinedImages.rows));
|
|
fromROI.copyTo(toROI);
|
|
|
|
cv::Mat depth;
|
|
if(!data.depthOrRightRaw().empty())
|
|
{
|
|
subImageWidth = data.depthOrRightRaw().cols/dbModels.size();
|
|
UASSERT(data.depthOrRightRaw().cols % dbModels.size() == 0 &&
|
|
subImageWidth == data.depthOrRightRaw().cols/(int)dbModels.size() &&
|
|
(int)_cameraIndices[i]*subImageWidth < data.depthOrRightRaw().cols);
|
|
if(combinedDepthImages.empty())
|
|
{
|
|
// initialize with first camera
|
|
combinedDepthImages = cv::Mat(data.depthOrRightRaw().rows, subImageWidth*(_cameraIndices.size()-i), data.depthOrRightRaw().type());
|
|
}
|
|
fromROI = cv::Mat(data.depthOrRightRaw(), cv::Rect(_cameraIndices[i]*subImageWidth, 0, subImageWidth, data.depthOrRightRaw().rows));
|
|
toROI = cv::Mat(combinedDepthImages, cv::Rect(addedCameras*subImageWidth, 0, subImageWidth, combinedDepthImages.rows));
|
|
fromROI.copyTo(toROI);
|
|
|
|
if(!data.depthConfidenceRaw().empty())
|
|
{
|
|
UASSERT(data.depthConfidenceRaw().size() == data.depthOrRightRaw().size());
|
|
if(combinedDepthConfidenceImages.empty())
|
|
{
|
|
combinedDepthConfidenceImages = cv::Mat(data.depthConfidenceRaw().rows, subImageWidth*(_cameraIndices.size()-i), data.depthConfidenceRaw().type());
|
|
}
|
|
fromROI = cv::Mat(data.depthConfidenceRaw(), cv::Rect(_cameraIndices[i]*subImageWidth, 0, subImageWidth, data.depthConfidenceRaw().rows));
|
|
toROI = cv::Mat(combinedDepthConfidenceImages, cv::Rect(addedCameras*subImageWidth, 0, subImageWidth, combinedDepthConfidenceImages.rows));
|
|
fromROI.copyTo(toROI);
|
|
}
|
|
}
|
|
|
|
if(!data.cameraModels().empty())
|
|
{
|
|
CameraModel model = data.cameraModels()[_cameraIndices[i]];
|
|
if(!_cameraLocalTransformOverrides.empty())
|
|
{
|
|
model.setLocalTransform(_cameraLocalTransformOverrides[i] * CameraModel::opticalRotation());
|
|
}
|
|
combinedModels.push_back(model);
|
|
combinedLocalTransforms.push_back(model.localTransform());
|
|
}
|
|
else
|
|
{
|
|
StereoCameraModel stereoModel = data.stereoCameraModels()[_cameraIndices[i]];
|
|
if(!_cameraLocalTransformOverrides.empty())
|
|
{
|
|
stereoModel.setLocalTransform(_cameraLocalTransformOverrides[i] * CameraModel::opticalRotation());
|
|
}
|
|
combinedStereoModels.push_back(stereoModel);
|
|
combinedLocalTransforms.push_back(stereoModel.localTransform());
|
|
}
|
|
cameraOldNewIndices.insert(std::make_pair(_cameraIndices[i], i));
|
|
}
|
|
if(!combinedModels.empty())
|
|
{
|
|
data.setRGBDImage(combinedImages, combinedDepthImages, combinedDepthConfidenceImages, combinedModels);
|
|
}
|
|
else
|
|
{
|
|
data.setStereoImage(combinedImages, combinedDepthImages, combinedStereoModels);
|
|
}
|
|
}
|
|
else if(!_cameraLocalTransformOverrides.empty() &&
|
|
_cameraLocalTransformOverrides.size() == dbModels.size())
|
|
{
|
|
// just update local transforms
|
|
std::vector<CameraModel> combinedModels;
|
|
std::vector<StereoCameraModel> combinedStereoModels;
|
|
for(size_t i=0; i<dbModels.size(); ++i)
|
|
{
|
|
if(!data.cameraModels().empty())
|
|
{
|
|
CameraModel model = data.cameraModels()[i];
|
|
model.setLocalTransform(_cameraLocalTransformOverrides[i] * CameraModel::opticalRotation());
|
|
combinedModels.push_back(model);
|
|
combinedLocalTransforms.push_back(model.localTransform());
|
|
}
|
|
else
|
|
{
|
|
StereoCameraModel stereoModel = data.stereoCameraModels()[i];
|
|
stereoModel.setLocalTransform(_cameraLocalTransformOverrides[i] * CameraModel::opticalRotation());
|
|
combinedStereoModels.push_back(stereoModel);
|
|
combinedLocalTransforms.push_back(stereoModel.localTransform());
|
|
}
|
|
}
|
|
if(!combinedModels.empty())
|
|
{
|
|
data.setCameraModels(combinedModels);
|
|
}
|
|
else
|
|
{
|
|
data.setStereoCameraModels(combinedStereoModels);
|
|
}
|
|
}
|
|
data.setId(!_intermediateNodesAreNormalNodes && s->getWeight()==-1 ? -1 : seq);
|
|
data.setStamp(s->getStamp());
|
|
data.setGroundTruth(s->getGroundTruthPose());
|
|
if(!globalPose.isNull())
|
|
{
|
|
data.setGlobalPose(globalPose, globalPoseCov);
|
|
}
|
|
if(!gravityTransform.isNull())
|
|
{
|
|
Eigen::Quaterniond q = gravityTransform.getQuaterniond();
|
|
data.setIMU(IMU(
|
|
cv::Vec4d(q.x(), q.y(), q.z(), q.w()), cv::Mat::eye(3,3,CV_64FC1),
|
|
cv::Vec3d(), cv::Mat(),
|
|
cv::Vec3d(), cv::Mat(),
|
|
Transform::getIdentity())); // we assume that gravity links are already transformed in base_link
|
|
}
|
|
data.setLandmarks(landmarks);
|
|
|
|
UDEBUG("Laser=%d RGB/Left=%d Depth/Right=%d, Conf=%d, Grid=%d, UserData=%d, GlobalPose=%d, GPS=%d, IMU=%d",
|
|
data.laserScanRaw().isEmpty()?0:1,
|
|
data.imageRaw().empty()?0:1,
|
|
data.depthOrRightRaw().empty()?0:1,
|
|
data.depthConfidenceRaw().empty()?0:1,
|
|
data.gridCellSize()==0.0f?0:1,
|
|
data.userDataRaw().empty()?0:1,
|
|
globalPose.isNull()?0:1,
|
|
data.gps().stamp()!=0.0?1:0,
|
|
gravityTransform.isNull()?0:1);
|
|
|
|
cv::Mat descriptors = s->getWordsDescriptors().clone();
|
|
const std::vector<cv::KeyPoint> & keypoints = s->getWordsKpts();
|
|
const std::vector<cv::Point3f> & keypoints3D = s->getWords3();
|
|
if(!_featuresIgnored &&
|
|
!keypoints.empty() &&
|
|
(keypoints3D.empty() || keypoints.size() == keypoints3D.size()) &&
|
|
(descriptors.empty() || (int)keypoints.size() == descriptors.rows))
|
|
{
|
|
if(!cameraOldNewIndices.empty())
|
|
{
|
|
cv::Mat newDescriptors;
|
|
std::vector<cv::KeyPoint> newKeypoints;
|
|
std::vector<cv::Point3f> newKeypoints3D;
|
|
UASSERT(!dbModels.empty() && dbModels[0].imageWidth()>0);
|
|
int subImageWidth = dbModels[0].imageWidth();
|
|
for(size_t i = 0; i<keypoints.size(); ++i)
|
|
{
|
|
int cameraIndex = int(keypoints.at(i).pt.x / subImageWidth);
|
|
UASSERT_MSG(cameraIndex >= 0 && cameraIndex < (int)dbModels.size(),
|
|
uFormat("cameraIndex=%d, db models=%d, kpt.x=%f, image width=%d",
|
|
cameraIndex, (int)dbModels.size(), keypoints[i].pt.x, subImageWidth).c_str());
|
|
if(cameraOldNewIndices.find(cameraIndex) != cameraOldNewIndices.end())
|
|
{
|
|
int newCameraIndex = cameraOldNewIndices.at(cameraIndex);
|
|
newKeypoints.push_back(keypoints[i]);
|
|
newKeypoints.back().pt.x += (newCameraIndex-cameraIndex)*subImageWidth;
|
|
if(!keypoints3D.empty())
|
|
{
|
|
cv::Point3f pt = util3d::transformPoint(keypoints3D.at(i), dbModels[cameraIndex].localTransform().inverse());
|
|
pt = util3d::transformPoint(pt, combinedLocalTransforms[cameraIndex]);
|
|
newKeypoints3D.push_back(pt);
|
|
}
|
|
if(!descriptors.empty())
|
|
{
|
|
newDescriptors.push_back(descriptors.row(i));
|
|
}
|
|
}
|
|
}
|
|
data.setFeatures(newKeypoints, newKeypoints3D, newDescriptors);
|
|
}
|
|
else if(!combinedLocalTransforms.empty())
|
|
{
|
|
// We are overriding the camera local transforms, let's move 3D words accordingly
|
|
UASSERT(dbModels.size() == combinedLocalTransforms.size());
|
|
std::vector<cv::Point3f> newKeypoints3D;
|
|
UASSERT(dbModels[0].imageWidth()>0);
|
|
int subImageWidth = dbModels[0].imageWidth();
|
|
for(size_t i = 0; i<keypoints3D.size(); ++i)
|
|
{
|
|
int cameraIndex = int(keypoints.at(i).pt.x / subImageWidth);
|
|
UASSERT_MSG(cameraIndex >= 0 && cameraIndex < (int)dbModels.size(),
|
|
uFormat("cameraIndex=%d, db models=%d, kpt.x=%f, image width=%d",
|
|
cameraIndex, (int)dbModels.size(), keypoints[i].pt.x, subImageWidth).c_str());
|
|
cv::Point3f pt = util3d::transformPoint(keypoints3D.at(i), dbModels[cameraIndex].localTransform().inverse());
|
|
pt = util3d::transformPoint(pt, combinedLocalTransforms[cameraIndex]);
|
|
newKeypoints3D.push_back(pt);
|
|
}
|
|
data.setFeatures(keypoints, newKeypoints3D, descriptors);
|
|
}
|
|
else
|
|
{
|
|
data.setFeatures(keypoints, keypoints3D, descriptors);
|
|
}
|
|
}
|
|
else if(!_featuresIgnored && !keypoints.empty() && (!keypoints3D.empty() || !descriptors.empty()))
|
|
{
|
|
UERROR("Missing feature data, features won't be published.");
|
|
}
|
|
|
|
if(data.imageRaw().empty() && data.imageCompressed().empty() && s->getWeight()>=0 && keypoints.empty())
|
|
{
|
|
UWARN("No image loaded from the database for id=%d!", seq);
|
|
}
|
|
|
|
if(!_odometryIgnored)
|
|
{
|
|
if(pose.isNull())
|
|
{
|
|
UWARN("Reading the database: odometry is null! "
|
|
"Please set \"Ignore odometry = true\" if there is "
|
|
"no odometry in the database.");
|
|
}
|
|
if(info)
|
|
{
|
|
info->odomPose = pose;
|
|
UASSERT(!infMatrix.empty());
|
|
info->odomCovariance = infMatrix.inv();
|
|
info->odomVelocity = s->getVelocity();
|
|
UDEBUG("odom variance = %f/%f", info->odomCovariance.at<double>(0,0), info->odomCovariance.at<double>(5,5));
|
|
}
|
|
}
|
|
delete s;
|
|
break;
|
|
}
|
|
}
|
|
else
|
|
{
|
|
UERROR("Not initialized...");
|
|
}
|
|
return data;
|
|
}
|
|
|
|
} /* namespace rtabmap */
|