Files
rtabmap/corelib/test/test_sensordata.cpp

918 lines
27 KiB
C++
Raw Normal View History

Adding doc and tests (#1492) * 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)
2026-08-06 13:32:20 -07:00
#include <gtest/gtest.h>
#include <rtabmap/core/SensorData.h>
#include <rtabmap/core/CameraModel.h>
#include <rtabmap/core/StereoCameraModel.h>
#include <rtabmap/core/LaserScan.h>
#include <rtabmap/core/IMU.h>
#include <rtabmap/core/GPS.h>
#include <rtabmap/core/EnvSensor.h>
#include <rtabmap/core/Landmark.h>
#include <rtabmap/core/GlobalDescriptor.h>
#include <rtabmap/utilite/UException.h>
#include <opencv2/core.hpp>
using namespace rtabmap;
// Constructor Tests
TEST(SensorDataTest, DefaultConstructor)
{
SensorData data;
EXPECT_FALSE(data.isValid());
EXPECT_EQ(data.id(), 0);
EXPECT_DOUBLE_EQ(data.stamp(), 0.0);
EXPECT_TRUE(data.imageRaw().empty());
EXPECT_TRUE(data.imageCompressed().empty());
EXPECT_TRUE(data.depthOrRightRaw().empty());
EXPECT_TRUE(data.depthOrRightCompressed().empty());
EXPECT_TRUE(data.cameraModels().empty());
EXPECT_TRUE(data.stereoCameraModels().empty());
}
TEST(SensorDataTest, ConstructorAppearanceOnly)
{
cv::Mat image = cv::Mat::ones(480, 640, CV_8UC3) * 128;
int id = 100;
double stamp = 12345.678;
SensorData data(image, id, stamp);
EXPECT_TRUE(data.isValid());
EXPECT_EQ(data.id(), id);
EXPECT_DOUBLE_EQ(data.stamp(), stamp);
EXPECT_FALSE(data.imageRaw().empty());
EXPECT_EQ(data.imageRaw().rows, 480);
EXPECT_EQ(data.imageRaw().cols, 640);
}
TEST(SensorDataTest, ConstructorMono)
{
cv::Mat image = cv::Mat::zeros(480, 640, CV_8UC1);
CameraModel model(525.0, 525.0, 320.0, 240.0);
int id = 200;
SensorData data(image, model, id);
EXPECT_TRUE(data.isValid());
EXPECT_EQ(data.id(), id);
EXPECT_FALSE(data.cameraModels().empty());
EXPECT_EQ(data.cameraModels().size(), 1u);
}
TEST(SensorDataTest, ConstructorRGBD)
{
cv::Mat rgb = cv::Mat::ones(480, 640, CV_8UC3) * 128;
cv::Mat depth = cv::Mat::ones(480, 640, CV_16UC1) * 1000;
CameraModel model(525.0, 525.0, 320.0, 240.0);
int id = 300;
SensorData data(rgb, depth, model, id);
EXPECT_TRUE(data.isValid());
EXPECT_EQ(data.id(), id);
EXPECT_FALSE(data.imageRaw().empty());
EXPECT_FALSE(data.depthOrRightRaw().empty());
EXPECT_FALSE(data.cameraModels().empty());
}
TEST(SensorDataTest, ConstructorRGBDWithConfidence)
{
cv::Mat rgb = cv::Mat::ones(480, 640, CV_8UC3) * 128;
cv::Mat depth = cv::Mat::ones(480, 640, CV_32FC1) * 1.5f;
cv::Mat confidence = cv::Mat::ones(480, 640, CV_8UC1) * 80;
CameraModel model(525.0, 525.0, 320.0, 240.0);
SensorData data(rgb, depth, confidence, model);
EXPECT_TRUE(data.isValid());
EXPECT_FALSE(data.depthConfidenceRaw().empty());
EXPECT_EQ(data.depthConfidenceRaw().type(), CV_8UC1);
}
TEST(SensorDataTest, ConstructorRGBDWithLaserScan)
{
cv::Mat rgb = cv::Mat::ones(480, 640, CV_8UC3) * 128;
cv::Mat depth = cv::Mat::ones(480, 640, CV_16UC1) * 1000;
CameraModel model(525.0, 525.0, 320.0, 240.0);
LaserScan scan = LaserScan::backwardCompatibility(cv::Mat(1,100,CV_32FC2));
SensorData data(scan, rgb, depth, model);
EXPECT_TRUE(data.isValid());
EXPECT_FALSE(data.laserScanRaw().isEmpty());
}
TEST(SensorDataTest, ConstructorMultiCameraRGBD)
{
cv::Mat rgb = cv::Mat::ones(480, 1280, CV_8UC3) * 128;
cv::Mat depth = cv::Mat::ones(480, 1280, CV_16UC1) * 1000;
std::vector<CameraModel> models;
models.push_back(CameraModel(525.0, 525.0, 320.0, 240.0));
models.push_back(CameraModel(525.0, 525.0, 960.0, 240.0));
SensorData data(rgb, depth, models);
EXPECT_TRUE(data.isValid());
EXPECT_EQ(data.cameraModels().size(), models.size());
}
TEST(SensorDataTest, ConstructorStereo)
{
cv::Mat left = cv::Mat::zeros(480, 640, CV_8UC1);
cv::Mat right = cv::Mat::zeros(480, 640, CV_8UC1);
StereoCameraModel model(525.0, 525.0, 320.0, 240.0, 0.12);
SensorData data(left, right, model);
EXPECT_TRUE(data.isValid());
EXPECT_FALSE(data.imageRaw().empty());
EXPECT_FALSE(data.depthOrRightRaw().empty());
EXPECT_FALSE(data.stereoCameraModels().empty());
}
TEST(SensorDataTest, ConstructorMultiStereo)
{
cv::Mat left = cv::Mat::zeros(480, 1280, CV_8UC1);
cv::Mat right = cv::Mat::zeros(480, 1280, CV_8UC1);
std::vector<StereoCameraModel> models;
models.push_back(StereoCameraModel(525.0, 525.0, 320.0, 240.0, 0.12));
models.push_back(StereoCameraModel(525.0, 525.0, 320.0, 240.0, 0.12));
SensorData data(left, right, models);
EXPECT_TRUE(data.isValid());
EXPECT_FALSE(data.imageRaw().empty());
EXPECT_FALSE(data.depthOrRightRaw().empty());
EXPECT_EQ(data.stereoCameraModels().size(), models.size());
}
TEST(SensorDataTest, ConstructorStereoWithLaserScan)
{
cv::Mat left = cv::Mat::zeros(480, 640, CV_8UC1);
cv::Mat right = cv::Mat::zeros(480, 640, CV_8UC1);
StereoCameraModel model(525.0, 525.0, 320.0, 240.0, 0.12);
LaserScan scan = LaserScan::backwardCompatibility(cv::Mat(1,100,CV_32FC2));
SensorData data(scan, left, right, model);
EXPECT_TRUE(data.isValid());
EXPECT_FALSE(data.laserScanRaw().isEmpty());
}
TEST(SensorDataTest, ConstructorIMUOnly)
{
IMU imu(cv::Vec3d(), cv::Mat(), cv::Vec3d(), cv::Mat(), Transform::getIdentity());
int id = 500;
double stamp = 99999.0;
SensorData data(imu, id, stamp);
EXPECT_TRUE(data.isValid());
EXPECT_EQ(data.id(), id);
EXPECT_DOUBLE_EQ(data.stamp(), stamp);
EXPECT_FALSE(data.imu().empty());
}
// isValid() Tests
TEST(SensorDataTest, IsValidWithId)
{
SensorData data;
EXPECT_FALSE(data.isValid());
data.setId(100);
EXPECT_TRUE(data.isValid());
}
TEST(SensorDataTest, IsValidWithStamp)
{
SensorData data;
EXPECT_FALSE(data.isValid());
data.setStamp(12345.0);
EXPECT_TRUE(data.isValid());
}
TEST(SensorDataTest, IsValidWithImage)
{
SensorData data;
cv::Mat image = cv::Mat::ones(100, 100, CV_8UC3);
data.setRGBDImage(image, cv::Mat(), CameraModel());
EXPECT_TRUE(data.isValid());
}
TEST(SensorDataTest, IsValidWithLaserScan)
{
SensorData data;
LaserScan scan = LaserScan::backwardCompatibility(cv::Mat(1,100,CV_32FC2));
data.setLaserScan(scan);
EXPECT_TRUE(data.isValid());
}
TEST(SensorDataTest, IsValidWithIMU)
{
SensorData data;
IMU imu(cv::Vec3d(), cv::Mat(), cv::Vec3d(), cv::Mat(), Transform::getIdentity());
data.setIMU(imu);
EXPECT_TRUE(data.isValid());
}
// ID and Stamp Tests
TEST(SensorDataTest, IdGetterSetter)
{
SensorData data;
EXPECT_EQ(data.id(), 0);
data.setId(123);
EXPECT_EQ(data.id(), 123);
data.setId(0);
EXPECT_EQ(data.id(), 0);
}
TEST(SensorDataTest, StampGetterSetter)
{
SensorData data;
EXPECT_DOUBLE_EQ(data.stamp(), 0.0);
data.setStamp(12345.678);
EXPECT_DOUBLE_EQ(data.stamp(), 12345.678);
data.setStamp(0.0);
EXPECT_DOUBLE_EQ(data.stamp(), 0.0);
}
// setRGBDImage Tests
TEST(SensorDataTest, SetRGBDImage)
{
SensorData data;
cv::Mat rgb = cv::Mat::ones(480, 640, CV_8UC3) * 128;
cv::Mat depth = cv::Mat::ones(480, 640, CV_16UC1) * 1000;
CameraModel model(525.0, 525.0, 320.0, 240.0);
data.setRGBDImage(rgb, depth, model);
EXPECT_FALSE(data.imageRaw().empty());
EXPECT_FALSE(data.depthOrRightRaw().empty());
EXPECT_EQ(data.imageRaw().rows, 480);
EXPECT_EQ(data.imageRaw().cols, 640);
EXPECT_FALSE(data.cameraModels().empty());
}
TEST(SensorDataTest, SetRGBDImageWithConfidence)
{
SensorData data;
cv::Mat rgb = cv::Mat::ones(480, 640, CV_8UC3) * 128;
cv::Mat depth = cv::Mat::ones(480, 640, CV_32FC1) * 1.5f;
cv::Mat confidence = cv::Mat::ones(480, 640, CV_8UC1) * 90;
CameraModel model(525.0, 525.0, 320.0, 240.0);
data.setRGBDImage(rgb, depth, confidence, model);
EXPECT_FALSE(data.depthConfidenceRaw().empty());
EXPECT_EQ(data.depthConfidenceRaw().type(), CV_8UC1);
}
TEST(SensorDataTest, SetRGBDImageMultiCamera)
{
SensorData data;
cv::Mat rgb = cv::Mat::ones(480, 1280, CV_8UC3) * 128;
cv::Mat depth = cv::Mat::ones(480, 1280, CV_16UC1) * 1000;
std::vector<CameraModel> models;
models.push_back(CameraModel(525.0, 525.0, 320.0, 240.0));
models.push_back(CameraModel(525.0, 525.0, 960.0, 240.0));
data.setRGBDImage(rgb, depth, models);
EXPECT_EQ(data.cameraModels().size(), 2u);
}
TEST(SensorDataTest, SetRGBDImageClearPreviousData)
{
SensorData data;
cv::Mat rgb1 = cv::Mat::ones(480, 640, CV_8UC3) * 128;
cv::Mat depth1 = cv::Mat::ones(480, 640, CV_16UC1) * 1000;
CameraModel model1(525.0, 525.0, 320.0, 240.0);
data.setRGBDImage(rgb1, depth1, model1);
cv::Mat rgb2 = cv::Mat::ones(240, 320, CV_8UC3) * 255;
cv::Mat depth2 = cv::Mat::ones(240, 320, CV_16UC1) * 2000;
CameraModel model2(525.0, 525.0, 160.0, 120.0);
data.setRGBDImage(rgb2, depth2, model2, true);
EXPECT_EQ(data.imageRaw().rows, 240);
EXPECT_EQ(data.imageRaw().cols, 320);
EXPECT_EQ(data.cameraModels().size(), 1u);
}
// setStereoImage Tests
TEST(SensorDataTest, SetStereoImage)
{
SensorData data;
cv::Mat left = cv::Mat::zeros(480, 640, CV_8UC1);
cv::Mat right = cv::Mat::zeros(480, 640, CV_8UC1);
StereoCameraModel model(525.0, 525.0, 320.0, 240.0, 0.12);
data.setStereoImage(left, right, model);
EXPECT_FALSE(data.imageRaw().empty());
EXPECT_FALSE(data.depthOrRightRaw().empty());
EXPECT_FALSE(data.stereoCameraModels().empty());
EXPECT_TRUE(data.cameraModels().empty());
}
TEST(SensorDataTest, SetStereoImageMultiCamera)
{
SensorData data;
cv::Mat left = cv::Mat::zeros(480, 1280, CV_8UC1);
cv::Mat right = cv::Mat::zeros(480, 1280, CV_8UC1);
std::vector<StereoCameraModel> models;
models.push_back(StereoCameraModel(525.0, 525.0, 320.0, 240.0, 0.12));
models.push_back(StereoCameraModel(525.0, 525.0, 960.0, 240.0, 0.12));
data.setStereoImage(left, right, models);
EXPECT_EQ(data.stereoCameraModels().size(), 2u);
}
// setLaserScan Tests
TEST(SensorDataTest, SetLaserScan)
{
SensorData data;
LaserScan scan = LaserScan::backwardCompatibility(cv::Mat(1,100,CV_32FC2));
data.setLaserScan(scan);
EXPECT_FALSE(data.laserScanRaw().isEmpty());
EXPECT_EQ(data.laserScanRaw().size(), 100u);
}
// Camera Model Tests
TEST(SensorDataTest, SetCameraModel)
{
SensorData data;
CameraModel model(525.0, 525.0, 320.0, 240.0);
data.setCameraModel(model);
EXPECT_EQ(data.cameraModels().size(), 1u);
EXPECT_DOUBLE_EQ(data.cameraModels()[0].fx(), 525.0);
}
TEST(SensorDataTest, SetCameraModels)
{
SensorData data;
std::vector<CameraModel> models;
models.push_back(CameraModel(525.0, 525.0, 320.0, 240.0));
models.push_back(CameraModel(600.0, 600.0, 400.0, 300.0));
data.setCameraModels(models);
EXPECT_EQ(data.cameraModels().size(), 2u);
}
TEST(SensorDataTest, SetStereoCameraModel)
{
SensorData data;
StereoCameraModel model(525.0, 525.0, 320.0, 240.0, 0.12);
data.setStereoCameraModel(model);
EXPECT_EQ(data.stereoCameraModels().size(), 1u);
EXPECT_DOUBLE_EQ(data.stereoCameraModels()[0].baseline(), 0.12);
}
TEST(SensorDataTest, SetStereoCameraModels)
{
SensorData data;
std::vector<StereoCameraModel> models;
models.push_back(StereoCameraModel(525.0, 525.0, 320.0, 240.0, 0.12));
models.push_back(StereoCameraModel(600.0, 600.0, 400.0, 300.0, 0.15));
data.setStereoCameraModels(models);
EXPECT_EQ(data.stereoCameraModels().size(), 2u);
}
// Convenience Methods Tests
TEST(SensorDataTest, DepthRaw)
{
SensorData data;
cv::Mat depth = cv::Mat::ones(480, 640, CV_16UC1) * 1000;
CameraModel model(525.0, 525.0, 320.0, 240.0);
data.setRGBDImage(cv::Mat(), depth, model);
EXPECT_TRUE(data.rightRaw().empty());
cv::Mat extractedDepth = data.depthRaw();
EXPECT_FALSE(extractedDepth.empty());
EXPECT_EQ(extractedDepth.type(), CV_16UC1);
}
TEST(SensorDataTest, RightRaw)
{
SensorData data;
cv::Mat left = cv::Mat::zeros(480, 640, CV_8UC1);
cv::Mat right = cv::Mat::ones(480, 640, CV_8UC1) * 128;
StereoCameraModel model(525.0, 525.0, 320.0, 240.0, 0.12);
data.setStereoImage(left, right, model);
EXPECT_TRUE(data.depthRaw().empty());
cv::Mat extractedRight = data.rightRaw();
EXPECT_FALSE(extractedRight.empty());
EXPECT_EQ(extractedRight.type(), CV_8UC1);
}
// Features Tests
TEST(SensorDataTest, SetFeatures)
{
SensorData data;
std::vector<cv::KeyPoint> keypoints;
keypoints.push_back(cv::KeyPoint(100, 200, 5.0f));
keypoints.push_back(cv::KeyPoint(300, 400, 5.0f));
std::vector<cv::Point3f> keypoints3D;
keypoints3D.push_back(cv::Point3f(1.0f, 2.0f, 3.0f));
keypoints3D.push_back(cv::Point3f(4.0f, 5.0f, 6.0f));
cv::Mat descriptors = cv::Mat::ones(2, 128, CV_32F);
data.setFeatures(keypoints, keypoints3D, descriptors);
EXPECT_EQ(data.keypoints().size(), 2u);
EXPECT_EQ(data.keypoints3D().size(), 2u);
EXPECT_FALSE(data.descriptors().empty());
EXPECT_EQ(data.descriptors().rows, 2);
}
// Global Descriptors Tests
TEST(SensorDataTest, AddGlobalDescriptor)
{
SensorData data;
GlobalDescriptor desc(0, cv::Mat::ones(1, 100, CV_32F));
data.addGlobalDescriptor(desc);
EXPECT_EQ(data.globalDescriptors().size(), 1u);
}
TEST(SensorDataTest, SetGlobalDescriptors)
{
SensorData data;
std::vector<GlobalDescriptor> descriptors;
descriptors.push_back(GlobalDescriptor(0, cv::Mat::ones(1, 100, CV_32F)));
descriptors.push_back(GlobalDescriptor(0, cv::Mat::ones(1, 200, CV_32F)));
data.setGlobalDescriptors(descriptors);
EXPECT_EQ(data.globalDescriptors().size(), 2u);
}
TEST(SensorDataTest, ClearGlobalDescriptors)
{
SensorData data;
GlobalDescriptor desc(0, cv::Mat::ones(1, 100, CV_32F));
data.addGlobalDescriptor(desc);
EXPECT_EQ(data.globalDescriptors().size(), 1u);
data.clearGlobalDescriptors();
EXPECT_TRUE(data.globalDescriptors().empty());
}
// Pose Tests
TEST(SensorDataTest, SetGroundTruth)
{
SensorData data;
Transform pose(1.0f, 2.0f, 3.0f, 0.1f, 0.2f, 0.3f);
data.setGroundTruth(pose);
EXPECT_FALSE(data.groundTruth().isNull());
EXPECT_FLOAT_EQ(data.groundTruth().x(), 1.0f);
}
TEST(SensorDataTest, SetGlobalPose)
{
SensorData data;
Transform pose(10.0f, 20.0f, 30.0f, 0.1f, 0.2f, 0.3f);
cv::Mat covariance = cv::Mat::eye(6, 6, CV_64FC1) * 0.1;
data.setGlobalPose(pose, covariance);
EXPECT_FALSE(data.globalPose().isNull());
EXPECT_FALSE(data.globalPoseCovariance().empty());
EXPECT_EQ(data.globalPoseCovariance().rows, 6);
EXPECT_EQ(data.globalPoseCovariance().cols, 6);
}
// GPS Tests
TEST(SensorDataTest, SetGPS)
{
double stamp = 1111.11;
double latitude = -73.0;
GPS gps(stamp, 45.0, latitude, 100.0, 5.0, 0.0);
SensorData data;
data.setGPS(gps);
EXPECT_DOUBLE_EQ(data.gps().stamp(), stamp);
EXPECT_DOUBLE_EQ(data.gps().latitude(), latitude);
}
// IMU Tests
TEST(SensorDataTest, SetIMU)
{
SensorData data;
IMU imu;
data.setIMU(imu);
EXPECT_TRUE(data.imu().empty());
imu = IMU(cv::Vec3d(), cv::Mat(), cv::Vec3d(), cv::Mat(), Transform::getIdentity());
data.setIMU(imu);
EXPECT_FALSE(data.imu().empty());
}
// Environmental Sensors Tests
TEST(SensorDataTest, SetEnvSensors)
{
SensorData data;
EnvSensors sensors;
sensors.insert(std::make_pair(EnvSensor::kAmbientTemperature, EnvSensor(EnvSensor::kAmbientTemperature, 25.0f, 0.0)));
data.setEnvSensors(sensors);
EXPECT_FALSE(data.envSensors().empty());
}
TEST(SensorDataTest, AddEnvSensor)
{
SensorData data;
EnvSensor sensor(EnvSensor::kAmbientRelativeHumidity, 60.0f, 0.0);
data.addEnvSensor(sensor);
EXPECT_FALSE(data.envSensors().empty());
EXPECT_EQ(data.envSensors().count(EnvSensor::kAmbientRelativeHumidity), 1u);
}
// Landmarks Tests
TEST(SensorDataTest, SetLandmarks)
{
SensorData data;
Landmarks landmarks;
landmarks.insert(std::make_pair(1, Landmark(1, 0, Transform(1.0f, 2.0f, 3.0f, 0, 0, 0), cv::Mat::eye(6,6,CV_64FC1))));
data.setLandmarks(landmarks);
EXPECT_FALSE(data.landmarks().empty());
EXPECT_EQ(data.landmarks().count(1), 1u);
}
// User Data Tests
TEST(SensorDataTest, SetUserData)
{
SensorData data;
cv::Mat userData = cv::Mat::ones(100, 100, CV_8UC1) * 128;
data.setUserData(userData);
EXPECT_FALSE(data.userDataRaw().empty());
EXPECT_EQ(data.userDataRaw().rows, 100);
EXPECT_EQ(data.userDataRaw().cols, 100);
}
// Occupancy Grid Tests
TEST(SensorDataTest, SetOccupancyGrid)
{
SensorData data;
// Use supported format: CV_32FC2 (2 channels of float)
cv::Mat ground = cv::Mat::ones(1, 100, CV_32FC2);
cv::Mat obstacles = cv::Mat::zeros(1, 100, CV_32FC2);
cv::Mat empty = cv::Mat::zeros(1, 100, CV_32FC2);
float cellSize = 0.05f;
cv::Point3f viewPoint(0.0f, 0.0f, 0.0f);
data.setOccupancyGrid(ground, obstacles, empty, cellSize, viewPoint);
EXPECT_FALSE(data.gridGroundCellsRaw().empty());
EXPECT_FALSE(data.gridObstacleCellsRaw().empty());
EXPECT_FALSE(data.gridEmptyCellsRaw().empty());
EXPECT_FLOAT_EQ(data.gridCellSize(), cellSize);
EXPECT_FLOAT_EQ(data.gridViewPoint().x, viewPoint.x);
// It should auto compress
EXPECT_FALSE(data.gridGroundCellsCompressed().empty());
EXPECT_FALSE(data.gridObstacleCellsCompressed().empty());
EXPECT_FALSE(data.gridEmptyCellsCompressed().empty());
}
TEST(SensorDataTest, SetOccupancyGridCompressed)
{
SensorData data;
// Use supported compressed format: CV_8UC1 with 1 row
cv::Mat ground = cv::Mat::ones(1, 100, CV_8UC1);
cv::Mat obstacles = cv::Mat::ones(1, 100, CV_8UC1);
cv::Mat empty = cv::Mat::ones(1, 100, CV_8UC1);
float cellSize = 0.05f;
cv::Point3f viewPoint(0.0f, 0.0f, 0.0f);
data.setOccupancyGrid(ground, obstacles, empty, cellSize, viewPoint);
EXPECT_FALSE(data.gridGroundCellsCompressed().empty());
EXPECT_FALSE(data.gridObstacleCellsCompressed().empty());
EXPECT_FALSE(data.gridEmptyCellsCompressed().empty());
EXPECT_FLOAT_EQ(data.gridCellSize(), cellSize);
}
TEST(SensorDataTest, SetOccupancyGridUnsupportedGroundFormat)
{
SensorData data;
// Unsupported format: CV_8UC1 with multiple rows (not compressed format)
cv::Mat ground = cv::Mat::ones(100, 100, CV_8UC1);
cv::Mat obstacles = cv::Mat::zeros(1, 100, CV_32FC2);
cv::Mat empty = cv::Mat::zeros(1, 100, CV_32FC2);
float cellSize = 0.05f;
cv::Point3f viewPoint(0.0f, 0.0f, 0.0f);
EXPECT_THROW(data.setOccupancyGrid(ground, obstacles, empty, cellSize, viewPoint), UException);
}
TEST(SensorDataTest, SetOccupancyGridUnsupportedObstacleFormat)
{
SensorData data;
cv::Mat ground = cv::Mat::zeros(1, 100, CV_32FC2);
// Unsupported format: CV_16UC1
cv::Mat obstacles = cv::Mat::ones(1, 100, CV_16UC1);
cv::Mat empty = cv::Mat::zeros(1, 100, CV_32FC2);
float cellSize = 0.05f;
cv::Point3f viewPoint(0.0f, 0.0f, 0.0f);
EXPECT_THROW(data.setOccupancyGrid(ground, obstacles, empty, cellSize, viewPoint), UException);
}
TEST(SensorDataTest, SetOccupancyGridUnsupportedEmptyFormat)
{
SensorData data;
cv::Mat ground = cv::Mat::zeros(1, 100, CV_32FC2);
cv::Mat obstacles = cv::Mat::zeros(1, 100, CV_32FC2);
// Unsupported format: CV_32FC1 (only CV_32FC2 through CV_32FC7 are supported)
cv::Mat empty = cv::Mat::ones(1, 100, CV_32FC1);
float cellSize = 0.05f;
cv::Point3f viewPoint(0.0f, 0.0f, 0.0f);
EXPECT_THROW(data.setOccupancyGrid(ground, obstacles, empty, cellSize, viewPoint), UException);
}
TEST(SensorDataTest, SetOccupancyGridSupportedFormats)
{
float cellSize = 0.05f;
cv::Point3f viewPoint(0.0f, 0.0f, 0.0f);
// Test all supported formats: CV_32FC2 through CV_32FC7
for (int channels = 2; channels <= 7; ++channels)
{
SensorData data;
cv::Mat ground = cv::Mat(1, 100, CV_32FC(channels));
cv::Mat obstacles = cv::Mat(1, 100, CV_32FC(channels));
cv::Mat empty = cv::Mat(1, 100, CV_32FC(channels));
EXPECT_NO_THROW(data.setOccupancyGrid(ground, obstacles, empty, cellSize, viewPoint))
<< "Failed for CV_32FC(" << channels << ")";
}
}
TEST(SensorDataTest, ClearOccupancyGridRaw)
{
SensorData data;
cv::Mat ground = cv::Mat::ones(1, 100, CV_32FC2);
cv::Mat obstacles = cv::Mat::zeros(1, 100, CV_32FC2);
cv::Mat empty = cv::Mat::zeros(1, 100, CV_32FC2);
data.setOccupancyGrid(ground, obstacles, empty, 0.05f, cv::Point3f(0, 0, 0));
EXPECT_FALSE(data.gridGroundCellsRaw().empty());
data.clearRawData(false, false, false, true);
EXPECT_TRUE(data.gridGroundCellsRaw().empty());
EXPECT_TRUE(data.gridObstacleCellsRaw().empty());
// Should not remove compressed
EXPECT_FALSE(data.gridGroundCellsCompressed().empty());
EXPECT_FALSE(data.gridObstacleCellsCompressed().empty());
}
// Data Clearing Tests
TEST(SensorDataTest, ClearCompressedData)
{
cv::Mat rgb = cv::Mat::ones(480, 640, CV_8UC3) * 128;
cv::Mat depth = cv::Mat::ones(480, 640, CV_16UC1) * 1000;
CameraModel model(525.0, 525.0, 320.0, 240.0);
// Construct with compressed data (simulated compressed data)
SensorData data(cv::Mat::ones(1, 100, CV_8UC1), cv::Mat::ones(1, 100, CV_8UC1), model);
// Add raw data
data.setRGBDImage(rgb, depth, model, false);
data.clearCompressedData(true, false, false);
// Raw data should still be present
EXPECT_FALSE(data.imageRaw().empty());
EXPECT_FALSE(data.depthRaw().empty());
}
TEST(SensorDataTest, ClearRawData)
{
SensorData data;
cv::Mat rgb = cv::Mat::ones(480, 640, CV_8UC3) * 128;
cv::Mat depth = cv::Mat::ones(480, 640, CV_16UC1) * 1000;
CameraModel model(525.0, 525.0, 320.0, 240.0);
data.setRGBDImage(rgb, depth, model);
EXPECT_FALSE(data.imageRaw().empty());
data.clearRawData(true, false, false);
EXPECT_TRUE(data.imageRaw().empty());
}
// Visibility Tests
TEST(SensorDataTest, IsPointVisibleFromCameras)
{
SensorData data;
CameraModel model(525.0, 525.0, 320.0, 240.0, CameraModel::opticalRotation(), 0.0, cv::Size(640, 480));
data.setCameraModel(model);
cv::Mat rgb = cv::Mat::ones(480, 640, CV_8UC3);
data.setRGBDImage(rgb, cv::Mat(), model);
EXPECT_EQ(data.cameraModels().size(), 1);
EXPECT_TRUE(data.cameraModels()[0].isValidForProjection());
// Point in front of camera (should be visible, returns camera index 0)
cv::Point3f pt(1.0f, 0.0f, 0.0f);
int cameraIndex = data.isPointVisibleFromCameras(pt);
EXPECT_EQ(cameraIndex, 0);
// Point behind camera (should not be visible, returns -1)
cv::Point3f ptBehind(-1.0f, 0.0f, 0.0f);
cameraIndex = data.isPointVisibleFromCameras(ptBehind);
EXPECT_EQ(cameraIndex, -1);
}
TEST(SensorDataTest, IsPointVisibleFromCamerasMultiCamera)
{
SensorData data;
std::vector<CameraModel> models;
models.push_back(CameraModel(525.0, 525.0, 320.0, 240.0, CameraModel::opticalRotation(), 0.0, cv::Size(640, 480)));
models.push_back(CameraModel(525.0, 525.0, 320.0, 240.0, CameraModel::opticalRotation(), 0.0, cv::Size(640, 480)));
data.setCameraModels(models);
cv::Mat rgb = cv::Mat::ones(480, 1280, CV_8UC3);
data.setRGBDImage(rgb, cv::Mat(), models);
EXPECT_EQ(data.cameraModels().size(), 2);
// Point visible from first camera (should return index 0)
cv::Point3f pt(1.0f, 0.0f, 0.0f);
int cameraIndex = data.isPointVisibleFromCameras(pt);
EXPECT_GE(cameraIndex, 0);
EXPECT_LE(cameraIndex, 1);
// Point not visible from any camera (should return -1)
cv::Point3f ptBehind(-1.0f, 0.0f, 0.0f);
cameraIndex = data.isPointVisibleFromCameras(ptBehind);
EXPECT_EQ(cameraIndex, -1);
}
TEST(SensorDataTest, IsPointVisibleFromCamerasNoCameras)
{
SensorData data;
// No camera models set
cv::Point3f pt(1.0f, 0.0f, 0.0f);
int cameraIndex = data.isPointVisibleFromCameras(pt);
EXPECT_EQ(cameraIndex, -1);
}
// Memory Usage Tests
TEST(SensorDataTest, GetMemoryUsed)
{
SensorData data;
unsigned long memEmpty = data.getMemoryUsed();
cv::Mat rgb = cv::Mat::ones(480, 640, CV_8UC3) * 128;
cv::Mat depth = cv::Mat::ones(480, 640, CV_16UC1) * 1000;
CameraModel model(525.0, 525.0, 320.0, 240.0);
data.setRGBDImage(rgb, depth, model);
unsigned long memWithData = data.getMemoryUsed();
EXPECT_GT(memWithData, memEmpty);
}
// Comprehensive Tests
TEST(SensorDataTest, ComprehensiveUsage)
{
SensorData data;
// Set ID and stamp
data.setId(1000);
data.setStamp(123456.789);
// Set RGB-D images
cv::Mat rgb = cv::Mat::ones(480, 640, CV_8UC3) * 128;
cv::Mat depth = cv::Mat::ones(480, 640, CV_16UC1) * 1000;
CameraModel model(525.0, 525.0, 320.0, 240.0);
data.setRGBDImage(rgb, depth, model);
// Set laser scan
LaserScan scan = LaserScan::backwardCompatibility(cv::Mat::ones(1, 640, CV_32FC3));
data.setLaserScan(scan);
// Set features
std::vector<cv::KeyPoint> keypoints;
keypoints.push_back(cv::KeyPoint(100, 200, 5.0f));
std::vector<cv::Point3f> keypoints3D;
keypoints3D.push_back(cv::Point3f(1.0f, 2.0f, 3.0f));
cv::Mat descriptors = cv::Mat::ones(1, 128, CV_32F);
data.setFeatures(keypoints, keypoints3D, descriptors);
// Set global pose
Transform pose(10.0f, 20.0f, 30.0f, 0, 0, 0);
cv::Mat covariance = cv::Mat::eye(6, 6, CV_64FC1) * 0.1;
data.setGlobalPose(pose, covariance);
// Verify all data
EXPECT_TRUE(data.isValid());
EXPECT_EQ(data.id(), 1000);
EXPECT_DOUBLE_EQ(data.stamp(), 123456.789);
EXPECT_FALSE(data.imageRaw().empty());
EXPECT_FALSE(data.depthOrRightRaw().empty());
EXPECT_FALSE(data.laserScanRaw().isEmpty());
EXPECT_EQ(data.keypoints().size(), 1u);
EXPECT_FALSE(data.globalPose().isNull());
}
// Edge Cases
TEST(SensorDataTest, EmptyImages)
{
SensorData data;
cv::Mat emptyRgb;
cv::Mat emptyDepth;
CameraModel model(525.0, 525.0, 320.0, 240.0);
data.setRGBDImage(emptyRgb, emptyDepth, model);
EXPECT_TRUE(data.imageRaw().empty());
EXPECT_TRUE(data.depthOrRightRaw().empty());
EXPECT_FALSE(data.cameraModels().empty());
}
TEST(SensorDataTest, DifferentImageTypes)
{
SensorData data;
// Grayscale
cv::Mat gray = cv::Mat::zeros(100, 100, CV_8UC1);
data.setRGBDImage(gray, cv::Mat(), CameraModel());
EXPECT_EQ(data.imageRaw().type(), CV_8UC1);
// RGB
cv::Mat color = cv::Mat::zeros(100, 100, CV_8UC3);
data.setRGBDImage(color, cv::Mat(), CameraModel());
EXPECT_EQ(data.imageRaw().type(), CV_8UC3);
}
TEST(SensorDataTest, DifferentDepthTypes)
{
SensorData data;
cv::Mat rgb = cv::Mat::ones(100, 100, CV_8UC3);
CameraModel model(525.0, 525.0, 50.0, 50.0);
// 16-bit depth (millimeters)
cv::Mat depth16 = cv::Mat::ones(100, 100, CV_16UC1) * 1000;
data.setRGBDImage(rgb, depth16, model);
EXPECT_EQ(data.depthOrRightRaw().type(), CV_16UC1);
// 32-bit depth (meters)
cv::Mat depth32 = cv::Mat::ones(100, 100, CV_32FC1) * 1.0f;
data.setRGBDImage(rgb, depth32, model);
EXPECT_EQ(data.depthOrRightRaw().type(), CV_32FC1);
}