Files
rtabmap/app/android/jni/CameraTango.cpp
T
matlabbe ee49beaf4f 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

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* cleanup

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* 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

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* Enabled testing on mac, updated windows testing like on linux

* added test_link

* fixed unresolved on windows

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* 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

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* fixing flaky macos test

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* fixing seed flaky test

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* 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

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* 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

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* testing more stuff

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* 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

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/*
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.
*/
#include "CameraTango.h"
#include "util.h"
#include "rtabmap/utilite/ULogger.h"
#include "rtabmap/core/util3d_transforms.h"
#include "rtabmap/core/OdometryEvent.h"
#include "rtabmap/core/util2d.h"
#include <tango_client_api.h>
#include <tango_support_api.h>
#include "tango-gl/camera.h"
namespace rtabmap {
#define nullptr 0
const int kVersionStringLength = 128;
const int holeSize = 5;
const float maxDepthError = 0.10;
const int scanDownsampling = 1;
//android phone
//11 10 01 00 // portrait
//01 11 00 10 // left
//10 00 11 01 // right
//00 01 10 11 // down
const float kTextureCoords0[] = {1.0, 1.0, 1.0, 0.0, 0.0, 1.0, 0.0, 0.0};
const float kTextureCoords90[] = {0.0, 1.0, 1.0, 1.0, 0.0, 0.0, 1.0, 0.0};
const float kTextureCoords180[] = {0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 1.0, 1.0};
const float kTextureCoords270[] = {1.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.0, 1.0};
// Callbacks
void onPointCloudAvailableRouter(void* context, const TangoPointCloud* point_cloud)
{
CameraTango* app = static_cast<CameraTango*>(context);
if(point_cloud->num_points>0)
{
app->cloudReceived(cv::Mat(1, point_cloud->num_points, CV_32FC4, point_cloud->points[0]), point_cloud->timestamp);
}
}
void onFrameAvailableRouter(void* context, TangoCameraId id, const TangoImageBuffer* color)
{
CameraTango* app = static_cast<CameraTango*>(context);
cv::Mat tangoImage;
if(color->format == TANGO_HAL_PIXEL_FORMAT_RGBA_8888)
{
tangoImage = cv::Mat(color->height, color->width, CV_8UC4, color->data);
}
else if(color->format == TANGO_HAL_PIXEL_FORMAT_YV12)
{
tangoImage = cv::Mat(color->height+color->height/2, color->width, CV_8UC1, color->data);
}
else if(color->format == TANGO_HAL_PIXEL_FORMAT_YCrCb_420_SP)
{
tangoImage = cv::Mat(color->height+color->height/2, color->width, CV_8UC1, color->data);
}
else if(color->format == 35)
{
tangoImage = cv::Mat(color->height+color->height/2, color->width, CV_8UC1, color->data);
}
else
{
LOGE("Not supported color format : %d.", color->format);
}
if(!tangoImage.empty())
{
app->rgbReceived(tangoImage, (unsigned int)color->format, color->timestamp);
}
}
void onPoseAvailableRouter(void* context, const TangoPoseData* pose)
{
if(pose->status_code == TANGO_POSE_VALID)
{
CameraTango* app = static_cast<CameraTango*>(context);
app->poseReceived(rtabmap_world_T_tango_world * app->tangoPoseToTransform(pose) * tango_device_T_rtabmap_world, pose->timestamp);
}
}
void onTangoEventAvailableRouter(void* context, const TangoEvent* event)
{
CameraTango* app = static_cast<CameraTango*>(context);
app->tangoEventReceived(event->type, event->event_key, event->event_value);
}
//////////////////////////////
// CameraTango
//////////////////////////////
CameraTango::CameraTango(bool colorCamera, int decimation, bool publishRawScan) :
tango_config_(0),
colorCamera_(colorCamera),
decimation_(decimation),
rawScanPublished_(publishRawScan),
tangoColorType_(0),
tangoColorStamp_(0)
{
UASSERT(decimation >= 1);
}
CameraTango::~CameraTango() {
// Disconnect Tango service
close();
}
// Compute fisheye distorted coordinates from undistorted coordinates.
// The distortion model used by the Tango fisheye camera is called FOV and is
// described in 'Straight lines have to be straight' by Frederic Devernay and
// Olivier Faugeras. See https://hal.inria.fr/inria-00267247/document.
// Tango ROS Streamer: https://github.com/Intermodalics/tango_ros/blob/master/tango_ros_common/tango_ros_native/src/tango_ros_node.cpp
void applyFovModel(
double xu, double yu, double w, double w_inverse, double two_tan_w_div_two,
double* xd, double* yd) {
double ru = sqrt(xu * xu + yu * yu);
constexpr double epsilon = 1e-7;
if (w < epsilon || ru < epsilon) {
*xd = xu;
*yd = yu ;
} else {
double rd_div_ru = std::atan(ru * two_tan_w_div_two) * w_inverse / ru;
*xd = xu * rd_div_ru;
*yd = yu * rd_div_ru;
}
}
// Compute the warp maps to undistort the Tango fisheye image using the FOV
// model. See OpenCV documentation for more information on warp maps:
// http://docs.opencv.org/2.4/modules/imgproc/doc/geometric_transformations.html
// Tango ROS Streamer: https://github.com/Intermodalics/tango_ros/blob/master/tango_ros_common/tango_ros_native/src/tango_ros_node.cpp
// @param fisheyeModel the fisheye camera intrinsics.
// @param mapX the output map for the x direction.
// @param mapY the output map for the y direction.
void initFisheyeRectificationMap(
const CameraModel& fisheyeModel,
cv::Mat & mapX, cv::Mat & mapY) {
const double & fx = fisheyeModel.K().at<double>(0,0);
const double & fy = fisheyeModel.K().at<double>(1,1);
const double & cx = fisheyeModel.K().at<double>(0,2);
const double & cy = fisheyeModel.K().at<double>(1,2);
const double & w = fisheyeModel.D().at<double>(0,0);
mapX.create(fisheyeModel.imageSize(), CV_32FC1);
mapY.create(fisheyeModel.imageSize(), CV_32FC1);
LOGD("initFisheyeRectificationMap: fx=%f fy=%f, cx=%f, cy=%f, w=%f", fx, fy, cx, cy, w);
// Pre-computed variables for more efficiency.
const double fy_inverse = 1.0 / fy;
const double fx_inverse = 1.0 / fx;
const double w_inverse = 1 / w;
const double two_tan_w_div_two = 2.0 * std::tan(w * 0.5);
// Compute warp maps in x and y directions.
// OpenCV expects maps from dest to src, i.e. from undistorted to distorted
// pixel coordinates.
for(int iu = 0; iu < fisheyeModel.imageHeight(); ++iu) {
for (int ju = 0; ju < fisheyeModel.imageWidth(); ++ju) {
double xu = (ju - cx) * fx_inverse;
double yu = (iu - cy) * fy_inverse;
double xd, yd;
applyFovModel(xu, yu, w, w_inverse, two_tan_w_div_two, &xd, &yd);
double jd = cx + xd * fx;
double id = cy + yd * fy;
mapX.at<float>(iu, ju) = jd;
mapY.at<float>(iu, ju) = id;
}
}
}
bool CameraTango::init(const std::string & calibrationFolder, const std::string & cameraName)
{
close();
CameraMobile::init(calibrationFolder, cameraName);
TangoSupport_initialize(TangoService_getPoseAtTime, TangoService_getCameraIntrinsics);
// Connect to Tango
LOGI("NativeRTABMap: Setup tango config");
tango_config_ = TangoService_getConfig(TANGO_CONFIG_DEFAULT);
if (tango_config_ == nullptr)
{
LOGE("NativeRTABMap: Failed to get default config form");
return false;
}
// Set auto-recovery for motion tracking as requested by the user.
bool is_atuo_recovery = true;
int ret = TangoConfig_setBool(tango_config_, "config_enable_auto_recovery", is_atuo_recovery);
if (ret != TANGO_SUCCESS)
{
LOGE("NativeRTABMap: config_enable_auto_recovery() failed with error code: %d", ret);
return false;
}
if(colorCamera_)
{
// Enable color.
ret = TangoConfig_setBool(tango_config_, "config_enable_color_camera", true);
if (ret != TANGO_SUCCESS)
{
LOGE("NativeRTABMap: config_enable_color_camera() failed with error code: %d", ret);
return false;
}
}
// Enable depth.
ret = TangoConfig_setBool(tango_config_, "config_enable_depth", true);
if (ret != TANGO_SUCCESS)
{
LOGE("NativeRTABMap: config_enable_depth() failed with error code: %d", ret);
return false;
}
// Need to specify the depth_mode as XYZC.
ret = TangoConfig_setInt32(tango_config_, "config_depth_mode", TANGO_POINTCLOUD_XYZC);
if (ret != TANGO_SUCCESS)
{
LOGE("Failed to set 'depth_mode' configuration flag with error code: %d", ret);
return false;
}
// Note that it's super important for AR applications that we enable low
// latency imu integration so that we have pose information available as
// quickly as possible. Without setting this flag, you'll often receive
// invalid poses when calling GetPoseAtTime for an image.
ret = TangoConfig_setBool(tango_config_, "config_enable_low_latency_imu_integration", true);
if (ret != TANGO_SUCCESS)
{
LOGE("NativeRTABMap: Failed to enable low latency imu integration.");
return false;
}
// Drift correction allows motion tracking to recover after it loses tracking.
//
// The drift corrected pose is is available through the frame pair with
// base frame AREA_DESCRIPTION and target frame DEVICE.
/*ret = TangoConfig_setBool(tango_config_, "config_enable_drift_correction", true);
if (ret != TANGO_SUCCESS) {
LOGE(
"NativeRTABMap: enabling config_enable_drift_correction "
"failed with error code: %d",
ret);
return false;
}*/
// Get TangoCore version string from service.
char tango_core_version[kVersionStringLength];
ret = TangoConfig_getString(tango_config_, "tango_service_library_version", tango_core_version, kVersionStringLength);
if (ret != TANGO_SUCCESS)
{
LOGE("NativeRTABMap: get tango core version failed with error code: %d", ret);
return false;
}
LOGI("NativeRTABMap: Tango version : %s", tango_core_version);
// Callbacks
LOGI("NativeRTABMap: Setup callbacks");
// Attach the OnXYZijAvailable callback.
// The callback will be called after the service is connected.
ret = TangoService_connectOnPointCloudAvailable(onPointCloudAvailableRouter);
if (ret != TANGO_SUCCESS)
{
LOGE("NativeRTABMap: Failed to connect to point cloud callback with error code: %d", ret);
return false;
}
ret = TangoService_connectOnFrameAvailable(colorCamera_?TANGO_CAMERA_COLOR:TANGO_CAMERA_FISHEYE, this, onFrameAvailableRouter);
if (ret != TANGO_SUCCESS)
{
LOGE("NativeRTABMap: Failed to connect to color callback with error code: %d", ret);
return false;
}
// Attach the onPoseAvailable callback.
// The callback will be called after the service is connected.
TangoCoordinateFramePair pair;
//pair.base = TANGO_COORDINATE_FRAME_AREA_DESCRIPTION; // drift correction is enabled
pair.base = TANGO_COORDINATE_FRAME_START_OF_SERVICE;
pair.target = TANGO_COORDINATE_FRAME_DEVICE;
ret = TangoService_connectOnPoseAvailable(1, &pair, onPoseAvailableRouter);
if (ret != TANGO_SUCCESS)
{
LOGE("NativeRTABMap: Failed to connect to pose callback with error code: %d", ret);
return false;
}
// Attach the onEventAvailable callback.
// The callback will be called after the service is connected.
ret = TangoService_connectOnTangoEvent(onTangoEventAvailableRouter);
if (ret != TANGO_SUCCESS)
{
LOGE("PointCloudApp: Failed to connect to event callback with error code: %d", ret);
return false;
}
// Now connect service so the callbacks above will be called
LOGI("NativeRTABMap: Connect to tango service");
ret = TangoService_connect(this, tango_config_);
if (ret != TANGO_SUCCESS)
{
LOGE("NativeRTABMap: Failed to connect to the Tango service with error code: %d", ret);
return false;
}
// update extrinsics
LOGI("NativeRTABMap: Update extrinsics");
TangoPoseData pose_data;
TangoCoordinateFramePair frame_pair;
// TangoService_getPoseAtTime function is used for query device extrinsics
// as well. We use timestamp 0.0 and the target frame pair to get the
// extrinsics from the sensors.
//
// Get color camera with respect to device transformation matrix.
frame_pair.base = TANGO_COORDINATE_FRAME_DEVICE;
frame_pair.target = colorCamera_?TANGO_COORDINATE_FRAME_CAMERA_COLOR:TANGO_COORDINATE_FRAME_CAMERA_FISHEYE;
ret = TangoService_getPoseAtTime(0.0, frame_pair, &pose_data);
if (ret != TANGO_SUCCESS)
{
LOGE("NativeRTABMap: Failed to get transform between the color camera frame and device frames");
return false;
}
deviceTColorCamera_ = rtabmap::Transform(
pose_data.translation[0],
pose_data.translation[1],
pose_data.translation[2],
pose_data.orientation[0],
pose_data.orientation[1],
pose_data.orientation[2],
pose_data.orientation[3]);
deviceTColorCamera_ = rtabmap_world_T_opengl_world * deviceTColorCamera_;
// camera intrinsic
TangoCameraIntrinsics color_camera_intrinsics;
ret = TangoService_getCameraIntrinsics(colorCamera_?TANGO_CAMERA_COLOR:TANGO_CAMERA_FISHEYE, &color_camera_intrinsics);
if (ret != TANGO_SUCCESS)
{
LOGE("NativeRTABMap: Failed to get the intrinsics for the color camera with error code: %d.", ret);
return false;
}
LOGD("Calibration: fx=%f fy=%f cx=%f cy=%f width=%d height=%d",
color_camera_intrinsics.fx,
color_camera_intrinsics.fy,
color_camera_intrinsics.cx,
color_camera_intrinsics.cy,
color_camera_intrinsics.width,
color_camera_intrinsics.height);
cv::Mat K = cv::Mat::eye(3, 3, CV_64FC1);
K.at<double>(0,0) = color_camera_intrinsics.fx;
K.at<double>(1,1) = color_camera_intrinsics.fy;
K.at<double>(0,2) = color_camera_intrinsics.cx;
K.at<double>(1,2) = color_camera_intrinsics.cy;
cv::Mat D = cv::Mat::zeros(1, 5, CV_64FC1);
LOGD("Calibration type = %d", color_camera_intrinsics.calibration_type);
if(color_camera_intrinsics.calibration_type == TANGO_CALIBRATION_POLYNOMIAL_5_PARAMETERS ||
color_camera_intrinsics.calibration_type == TANGO_CALIBRATION_EQUIDISTANT)
{
D.at<double>(0,0) = color_camera_intrinsics.distortion[0];
D.at<double>(0,1) = color_camera_intrinsics.distortion[1];
D.at<double>(0,2) = color_camera_intrinsics.distortion[2];
D.at<double>(0,3) = color_camera_intrinsics.distortion[3];
D.at<double>(0,4) = color_camera_intrinsics.distortion[4];
}
else if(color_camera_intrinsics.calibration_type == TANGO_CALIBRATION_POLYNOMIAL_3_PARAMETERS)
{
D.at<double>(0,0) = color_camera_intrinsics.distortion[0];
D.at<double>(0,1) = color_camera_intrinsics.distortion[1];
D.at<double>(0,2) = 0.;
D.at<double>(0,3) = 0.;
D.at<double>(0,4) = color_camera_intrinsics.distortion[2];
}
else if(color_camera_intrinsics.calibration_type == TANGO_CALIBRATION_POLYNOMIAL_2_PARAMETERS)
{
D.at<double>(0,0) = color_camera_intrinsics.distortion[0];
D.at<double>(0,1) = color_camera_intrinsics.distortion[1];
D.at<double>(0,2) = 0.;
D.at<double>(0,3) = 0.;
D.at<double>(0,4) = 0.;
}
cv::Mat R = cv::Mat::eye(3, 3, CV_64FC1);
cv::Mat P;
LOGD("Distortion params: %f, %f, %f, %f, %f", D.at<double>(0,0), D.at<double>(0,1), D.at<double>(0,2), D.at<double>(0,3), D.at<double>(0,4));
model_ = CameraModel(colorCamera_?"color":"fisheye",
cv::Size(color_camera_intrinsics.width, color_camera_intrinsics.height),
K, D, R, P,
deviceTColorCamera_);
if(!colorCamera_)
{
initFisheyeRectificationMap(model_, fisheyeRectifyMapX_, fisheyeRectifyMapY_);
}
LOGI("deviceTColorCameraRtabmap =%s", deviceTColorCamera_.prettyPrint().c_str());
return true;
}
void CameraTango::close()
{
if(tango_config_)
{
TangoConfig_free(tango_config_);
tango_config_ = nullptr;
LOGI("TangoService_disconnect()");
TangoService_disconnect();
LOGI("TangoService_disconnect() done.");
}
fisheyeRectifyMapX_ = cv::Mat();
fisheyeRectifyMapY_ = cv::Mat();
CameraMobile::close();
}
void CameraTango::cloudReceived(const cv::Mat & cloud, double timestamp)
{
if(!cloud.empty())
{
//LOGD("Depth received! %fs (%d points)", timestamp, cloud.cols);
UASSERT(cloud.type() == CV_32FC4);
boost::mutex::scoped_lock lock(tangoDataMutex_);
// From post: http://stackoverflow.com/questions/29236110/timing-issues-with-tango-image-frames
// "In the current version of Project Tango Tablet RGB IR camera
// is used for both depth and color images and it can only do one
// or the other for each frame. So in the stream we get 4 RGB frames
// followed by 1 Depth frame resulting in the pattern you observed. This
// is more of a hardware limitation."
//
// So, synchronize with the last RGB frame before the Depth is acquired
if(!tangoColor_.empty())
{
UTimer timer;
double dt = fabs(timestamp - tangoColorStamp_);
//LOGD("Depth: %f vs %f = %f", tangoColorStamp_, timestamp, dt);
if(dt >= 0.0 && dt < 0.5)
{
bool notify = !tangoData_.isValid();
cv::Mat tangoImage = tangoColor_;
cv::Mat rgb;
double cloudStamp = timestamp;
double rgbStamp = tangoColorStamp_;
int tangoColorType = tangoColorType_;
tangoColor_ = cv::Mat();
tangoColorStamp_ = 0.0;
tangoColorType_ = 0;
LOGD("tangoColorType=%d", tangoColorType);
if(tangoColorType == TANGO_HAL_PIXEL_FORMAT_RGBA_8888)
{
cv::cvtColor(tangoImage, rgb, cv::COLOR_RGBA2BGR);
}
else if(tangoColorType == TANGO_HAL_PIXEL_FORMAT_YV12)
{
cv::cvtColor(tangoImage, rgb, cv::COLOR_YUV2BGR_YV12);
}
else if(tangoColorType == TANGO_HAL_PIXEL_FORMAT_YCrCb_420_SP)
{
cv::cvtColor(tangoImage, rgb, cv::COLOR_YUV2BGR_NV21);
}
else if(tangoColorType == 35)
{
cv::cvtColor(tangoImage, rgb, cv::COLOR_YUV420sp2GRAY);
}
else
{
LOGE("Not supported color format : %d.", tangoColorType);
tangoData_ = SensorData();
return;
}
//for(int i=0; i<rgb.cols; ++i)
//{
// UERROR("%d,%d,%d", (int)rgb.at<cv::Vec3b>(i)[0], (int)rgb.at<cv::Vec3b>(i)[1], (int)rgb.at<cv::Vec3b>(i)[2]);
//}
CameraModel model = model_;
if(colorCamera_)
{
if(decimation_ > 1)
{
rgb = util2d::decimate(rgb, decimation_);
model = model.scaled(1.0/double(decimation_));
}
}
else
{
//UTimer t;
cv::Mat rgbRect;
cv::remap(rgb, rgbRect, fisheyeRectifyMapX_, fisheyeRectifyMapY_, cv::INTER_LINEAR, cv::BORDER_CONSTANT, 0);
rgb = rgbRect;
//LOGD("Rectification time=%fs", t.ticks());
}
// Querying the depth image's frame transformation based on the depth image's
// timestamp.
cv::Mat depth;
// Calculate the relative pose from color camera frame at timestamp
// color_timestamp t1 and depth
// camera frame at depth_timestamp t0.
Transform colorToDepth;
TangoPoseData pose_color_image_t1_T_depth_image_t0;
if (TangoSupport_calculateRelativePose(
rgbStamp, colorCamera_?TANGO_COORDINATE_FRAME_CAMERA_COLOR:TANGO_COORDINATE_FRAME_CAMERA_FISHEYE, cloudStamp,
TANGO_COORDINATE_FRAME_CAMERA_DEPTH,
&pose_color_image_t1_T_depth_image_t0) == TANGO_SUCCESS)
{
colorToDepth = tangoPoseToTransform(&pose_color_image_t1_T_depth_image_t0);
}
else
{
LOGE(
"SynchronizationApplication: Could not find a valid relative pose at "
"time for color and "
" depth cameras.");
}
if(colorToDepth.getNormSquared() > 100000)
{
LOGE("Very large color to depth error detected (%s)! Ignoring this frame!", colorToDepth.prettyPrint().c_str());
colorToDepth.setNull();
}
cv::Mat scan;
if(!colorToDepth.isNull())
{
// The Color Camera frame at timestamp t0 with respect to Depth
// Camera frame at timestamp t1.
//LOGD("colorToDepth=%s", colorToDepth.prettyPrint().c_str());
LOGD("rgb=%dx%d cloud size=%d", rgb.cols, rgb.rows, (int)cloud.total());
int pixelsSet = 0;
int depthSizeDec = colorCamera_?8:1;
depth = cv::Mat::zeros(model_.imageHeight()/depthSizeDec, model_.imageWidth()/depthSizeDec, CV_16UC1); // mm
CameraModel depthModel = model_.scaled(1.0f/float(depthSizeDec));
std::vector<cv::Point3f> scanData(rawScanPublished_?cloud.total():0);
int oi=0;
int closePoints = 0;
float closeROI[4];
closeROI[0] = depth.cols/4;
closeROI[1] = 3*(depth.cols/4);
closeROI[2] = depth.rows/4;
closeROI[3] = 3*(depth.rows/4);
unsigned short minDepthValue=10000;
for(unsigned int i=0; i<cloud.total(); ++i)
{
const float * p = cloud.ptr<float>(0,i);
cv::Point3f pt = util3d::transformPoint(cv::Point3f(p[0], p[1], p[2]), colorToDepth);
if(pt.z > 0.0f && i%scanDownsampling == 0 && rawScanPublished_)
{
scanData.at(oi++) = pt;
}
int pixel_x_l, pixel_y_l, pixel_x_h, pixel_y_h;
// get the coordinate on image plane.
pixel_x_l = static_cast<int>((depthModel.fx()) * (pt.x / pt.z) + depthModel.cx());
pixel_y_l = static_cast<int>((depthModel.fy()) * (pt.y / pt.z) + depthModel.cy());
pixel_x_h = static_cast<int>((depthModel.fx()) * (pt.x / pt.z) + depthModel.cx() + 0.5f);
pixel_y_h = static_cast<int>((depthModel.fy()) * (pt.y / pt.z) + depthModel.cy() + 0.5f);
unsigned short depth_value(pt.z * 1000.0f);
if(pixel_x_l>=closeROI[0] && pixel_x_l<closeROI[1] &&
pixel_y_l>closeROI[2] && pixel_y_l<closeROI[3] &&
depth_value < 600)
{
++closePoints;
if(depth_value < minDepthValue)
{
minDepthValue = depth_value;
}
}
bool pixelSet = false;
if(pixel_x_l>=0 && pixel_x_l<depth.cols &&
pixel_y_l>0 && pixel_y_l<depth.rows && // ignore first line
depth_value)
{
unsigned short & depthPixel = depth.at<unsigned short>(pixel_y_l, pixel_x_l);
if(depthPixel == 0 || depthPixel > depth_value)
{
depthPixel = depth_value;
pixelSet = true;
}
}
if(pixel_x_h>=0 && pixel_x_h<depth.cols &&
pixel_y_h>0 && pixel_y_h<depth.rows && // ignore first line
depth_value)
{
unsigned short & depthPixel = depth.at<unsigned short>(pixel_y_h, pixel_x_h);
if(depthPixel == 0 || depthPixel > depth_value)
{
depthPixel = depth_value;
pixelSet = true;
}
}
if(pixelSet)
{
pixelsSet += 1;
}
}
if(closePoints > 100)
{
this->post(new CameraInfoEvent(0, "TooClose", ""));
}
if(oi)
{
scan = cv::Mat(1, oi, CV_32FC3, scanData.data()).clone();
}
//LOGD("pixels depth set= %d", pixelsSet);
}
else
{
LOGE("color to depth pose is null?!? (rgb stamp=%f) (depth stamp=%f)", rgbStamp, cloudStamp);
}
if(!rgb.empty() && !depth.empty())
{
depth = rtabmap::util2d::fillDepthHoles(depth, holeSize, maxDepthError);
Transform odom = getPoseAtTimestamp(rgbStamp);
//LOGD("Local = %s", model.localTransform().prettyPrint().c_str());
//LOGD("tango = %s", poseDevice.prettyPrint().c_str());
//LOGD("opengl(t)= %s", (opengl_world_T_tango_world * poseDevice).prettyPrint().c_str());
// occlusion depth
if(!depth.empty())
{
rtabmap::CameraModel depthModel = model.scaled(float(depth.cols) / float(model.imageWidth()));
depthModel.setLocalTransform(odom*model.localTransform());
this->setOcclusionImage(depth, depthModel);
}
//LOGD("rtabmap = %s", odom.prettyPrint().c_str());
//LOGD("opengl(r)= %s", (opengl_world_T_rtabmap_world * odom * rtabmap_device_T_opengl_device).prettyPrint().c_str());
Transform scanLocalTransform = model.localTransform();
if(rawScanPublished_)
{
tangoData_ = SensorData(LaserScan::backwardCompatibility(scan, cloud.total()/scanDownsampling, 0, scanLocalTransform), rgb, depth, model, this->getNextSeqID(), rgbStamp);
}
else
{
tangoData_ = SensorData(rgb, depth, model, this->getNextSeqID(), rgbStamp);
}
tangoData_.setGroundTruth(odom);
}
else
{
LOGE("Could not get depth and rgb images!?!");
tangoData_ = SensorData();
return;
}
if(notify)
{
tangoDataReady_.release();
}
LOGD("process cloud received %fs", timer.ticks());
}
}
}
}
void CameraTango::rgbReceived(const cv::Mat & tangoImage, int type, double timestamp)
{
if(!tangoImage.empty())
{
//LOGD("RGB received! %fs", timestamp);
boost::mutex::scoped_lock lock(tangoDataMutex_);
tangoColor_ = tangoImage.clone();
tangoColorStamp_ = timestamp;
tangoColorType_ = type;
}
}
void CameraTango::tangoEventReceived(int type, const char * key, const char * value)
{
this->post(new CameraInfoEvent(type, key, value));
}
std::string CameraTango::getSerial() const
{
return "Tango";
}
rtabmap::Transform CameraTango::tangoPoseToTransform(const TangoPoseData * tangoPose) const
{
UASSERT(tangoPose);
rtabmap::Transform pose;
pose = rtabmap::Transform(
tangoPose->translation[0],
tangoPose->translation[1],
tangoPose->translation[2],
tangoPose->orientation[0],
tangoPose->orientation[1],
tangoPose->orientation[2],
tangoPose->orientation[3]);
return pose;
}
rtabmap::Transform CameraTango::getPoseAtTimestamp(double timestamp)
{
rtabmap::Transform pose;
TangoPoseData pose_start_service_T_device;
TangoCoordinateFramePair frame_pair;
frame_pair.base = TANGO_COORDINATE_FRAME_START_OF_SERVICE;
frame_pair.target = TANGO_COORDINATE_FRAME_DEVICE;
TangoErrorType status = TangoService_getPoseAtTime(timestamp, frame_pair, &pose_start_service_T_device);
if (status != TANGO_SUCCESS)
{
LOGE(
"PoseData: Failed to get transform between the Start of service and "
"device frames at timestamp %lf",
timestamp);
}
if (pose_start_service_T_device.status_code != TANGO_POSE_VALID)
{
LOGW(
"PoseData: Failed to get transform between the Start of service and "
"device frames at timestamp %lf",
timestamp);
}
else
{
pose = rtabmap_world_T_tango_world * tangoPoseToTransform(&pose_start_service_T_device) * tango_device_T_rtabmap_world;
}
return pose;
}
SensorData CameraTango::updateDataOnRender(Transform & pose)
{
//LOGI("Capturing image...");
pose.setNull();
if(textureId_ == 0)
{
glGenTextures(1, &textureId_);
glBindTexture(GL_TEXTURE_EXTERNAL_OES, textureId_);
glTexParameteri(GL_TEXTURE_EXTERNAL_OES, GL_TEXTURE_WRAP_S, GL_CLAMP_TO_EDGE);
glTexParameteri(GL_TEXTURE_EXTERNAL_OES, GL_TEXTURE_WRAP_T, GL_CLAMP_TO_EDGE);
glTexParameteri(GL_TEXTURE_EXTERNAL_OES, GL_TEXTURE_MIN_FILTER, GL_NEAREST);
glTexParameteri(GL_TEXTURE_EXTERNAL_OES, GL_TEXTURE_MAG_FILTER, GL_NEAREST);
}
// Update Texture (optional, just for first-view rendering)
if(colorCamera_ && textureId_)
{
double video_overlay_timestamp;
TangoErrorType status = TangoService_updateTextureExternalOes(TANGO_CAMERA_COLOR, textureId_, &video_overlay_timestamp);
if (status == TANGO_SUCCESS)
{
pose = getPoseAtTimestamp(video_overlay_timestamp);
int rotation = static_cast<int>(getScreenRotation()) + 1; // remove 90deg camera rotation
if (rotation > 3) {
rotation -= 4;
}
TangoDoubleMatrixTransformData matrix_transform;
status = TangoSupport_getDoubleMatrixTransformAtTime(
video_overlay_timestamp,
TANGO_COORDINATE_FRAME_CAMERA_COLOR,
TANGO_COORDINATE_FRAME_START_OF_SERVICE,
TANGO_SUPPORT_ENGINE_OPENGL,
TANGO_SUPPORT_ENGINE_OPENGL,
static_cast<TangoSupportRotation>(rotation),
&matrix_transform);
if (matrix_transform.status_code == TANGO_POSE_VALID)
{
// Get projection matrix
TangoCameraIntrinsics color_camera_intrinsics;
int ret = TangoSupport_getCameraIntrinsicsBasedOnDisplayRotation(
TANGO_CAMERA_COLOR,
static_cast<TangoSupportRotation>(rotation),
&color_camera_intrinsics);
if (ret == TANGO_SUCCESS) {
float image_width = static_cast<float>(color_camera_intrinsics.width);
float image_height = static_cast<float>(color_camera_intrinsics.height);
float fx = static_cast<float>(color_camera_intrinsics.fx);
float fy = static_cast<float>(color_camera_intrinsics.fy);
float cx = static_cast<float>(color_camera_intrinsics.cx);
float cy = static_cast<float>(color_camera_intrinsics.cy);
viewMatrix_ = glm::make_mat4(matrix_transform.matrix);
projectionMatrix_ = tango_gl::Camera::ProjectionMatrixForCameraIntrinsics(
image_width, image_height, fx, fy, cx, cy, 0.3, 50);
switch(rotation)
{
case ROTATION_90:
memcpy(transformed_uvs_, kTextureCoords90, 8*sizeof(float));
break;
case ROTATION_180:
memcpy(transformed_uvs_, kTextureCoords180, 8*sizeof(float));
break;
case ROTATION_270:
memcpy(transformed_uvs_, kTextureCoords270, 8*sizeof(float));
break;
case ROTATION_0:
default:
memcpy(transformed_uvs_, kTextureCoords0, 8*sizeof(float));
}
uvs_initialized_ = true;
}
else
{
UERROR("TangoSupport_getCameraIntrinsicsBasedOnDisplayRotation failed!");
}
}
else
{
UERROR("TangoSupport_getDoubleMatrixTransformAtTime failed!");
}
}
else
{
UERROR("TangoService_updateTextureExternalOes failed!");
}
}
SensorData data;
if(tangoDataReady_.acquireTry(1) == 0)
{
boost::mutex::scoped_lock lock(tangoDataMutex_);
data = tangoData_;
tangoData_ = SensorData();
pose = data.groundTruth();
data.setGroundTruth(Transform());
}
return data;
}
} /* namespace rtabmap */