From de0d70ec3ca705fdfb90fe9fa38d35f524c8768c Mon Sep 17 00:00:00 2001 From: Fujun Ruan <85526629+Flowerst-0416@users.noreply.github.com> Date: Mon, 21 Nov 2022 01:06:03 -0500 Subject: [PATCH] add blaser_ros & camera_model --- blaser_ros/BlaserCommandsReadMe.md | 50 + blaser_ros/CMakeLists.txt | 100 + blaser_ros/README.md | 378 ++ blaser_ros/calib_result.txt | 5606 +++++++++++++++++ blaser_ros/cfg/LaserDetector.cfg | 12 + blaser_ros/config/cam1/cam_config/mei.yaml | 18 + .../config/cam1/cam_config/pinhole.yaml | 14 + .../cam1/env_config/.checkerboard.yaml.swp | Bin 0 -> 12288 bytes .../config/cam1/env_config/car_toys.yaml | 6 + .../config/cam1/env_config/checkerboard.yaml | 8 + .../cam1/target_config/checkerboard.yaml | 5 + .../config/cam1/target_config/small_cb.yaml | 5 + .../config/cam2/cam_config/icra2021.yaml | 18 + blaser_ros/config/cam2/cam_config/mei.yaml | 18 + blaser_ros/config/cam2/cam_config/ost.yaml | 20 + .../config/cam2/cam_config/pinhole.yaml | 14 + .../cam2/env_config/.checkerboard.yaml.swp | Bin 0 -> 12288 bytes .../config/cam2/env_config/car_toys.yaml | 6 + .../config/cam2/env_config/checkerboard.yaml | 8 + .../config/cam2/target_config/5mm_9x6.yaml | 5 + .../cam2/target_config/checkerboard.yaml | 5 + .../config/cam2/target_config/small_cb.yaml | 5 + .../resolution_analyser/res_analyser.yaml | 35 + blaser_ros/config/trl6_calib.yaml | 44 + blaser_ros/config/trl6_slam.rviz | 853 +++ blaser_ros/config/trl6_slam.yaml | 170 + blaser_ros/config/trl6_slam_0821LL_Final.yaml | 170 + blaser_ros/config/trl6_slam_210821.yaml | 131 + blaser_ros/config/vlio_rviz_config.rviz | 844 +++ blaser_ros/include/blaser_ros/common.h | 32 + blaser_ros/include/blaser_ros/laser_calib.h | 327 + .../include/blaser_ros/laser_detector.h | 64 + .../include/blaser_ros/laser_geometry_utils.h | 37 + .../include/blaser_ros/laser_rgb_estimator.h | 150 + .../blaser_ros/laser_stripe_detector.h | 173 + .../include/blaser_ros/resolution_analyser.h | 88 + .../blaser_ros/third_party/matplotlibcpp.h | 2986 +++++++++ blaser_ros/include/blaser_ros/tic_toc.h | 29 + .../blaser_ros/util/cv_click_handler.h | 25 + .../include/blaser_ros/util/geometry_util.h | 42 + blaser_ros/launch/blaser_driver.launch | 11 + blaser_ros/launch/blaser_open_serial.sh | 7 + blaser_ros/launch/bring_up_blaser.launch | 13 + .../launch/laser_detector_minia1001.launch | 4 + blaser_ros/launch/laser_detector_vio.launch | 4 + blaser_ros/launch/laser_rgb_estimator.launch | 9 + blaser_ros/launch/trl6_sensor_proc.launch | 24 + blaser_ros/launch/trl6_slam.launch | 10 + blaser_ros/matlab/numerical_diff.m | 28 + blaser_ros/matlab/numerical_diff_p2p.m | 22 + blaser_ros/matlab/p2l_so3.m | 9 + blaser_ros/matlab/p2p_so3.m | 8 + blaser_ros/matlab/skew_sym.m | 8 + blaser_ros/package.xml | 81 + .../Untitled-checkpoint.ipynb | 6 + .../Untitled1-checkpoint.ipynb | 177 + .../laser_calib_test-checkpoint.ipynb | 6 + .../vis_laser_calib_result-checkpoint.ipynb | 911 +++ blaser_ros/scripts/Untitled.ipynb | 54 + blaser_ros/scripts/Untitled1.ipynb | 988 +++ blaser_ros/scripts/im_hsv_shower.py | 17 + blaser_ros/scripts/im_saver.py | 34 + blaser_ros/scripts/img001.png | Bin 0 -> 5925169 bytes blaser_ros/scripts/imu_driver.py | 68 + blaser_ros/scripts/laser_calib_test.ipynb | 90 + .../scripts/laser_resolution_analyze.py | 157 + blaser_ros/scripts/pub_cam_odom.py | 53 + blaser_ros/scripts/static_tf_blaser_vio.py | 16 + .../scripts/vis_laser_calib_result.ipynb | 902 +++ blaser_ros/scripts/vis_laser_calib_result.py | 101 + blaser_ros/src/laser_calib.cpp | 792 +++ blaser_ros/src/laser_calib_node.cpp | 82 + blaser_ros/src/laser_detector.cpp | 109 + blaser_ros/src/laser_detector_node.cpp | 19 + blaser_ros/src/laser_geometry_utils.cpp | 26 + blaser_ros/src/laser_rgb_estimator.cpp | 299 + blaser_ros/src/laser_rgb_estimator_node.cpp | 16 + blaser_ros/src/laser_stripe_detector.cpp | 340 + blaser_ros/src/resolution_analyser.cpp | 311 + .../src/test/laser_stripe_detector_test.cpp | 28 + blaser_ros/src/util/cv_click_handler.cpp | 39 + blaser_ros/src/util/geometry_util.cpp | 117 + blaser_ros/todo.txt | 43 + camera_model/CMakeLists.txt | 67 + camera_model/cmake/FindEigen.cmake | 172 + .../camodocal/calib/CameraCalibration.h | 81 + .../include/camodocal/camera_models/Camera.h | 164 + .../camodocal/camera_models/CameraFactory.h | 32 + .../camodocal/camera_models/CataCamera.h | 210 + .../camera_models/CostFunctionFactory.h | 82 + .../camera_models/EquidistantCamera.h | 215 + .../camodocal/camera_models/PinholeCamera.h | 196 + .../camera_models/ScaramuzzaCamera.h | 348 + .../include/camodocal/chessboard/Chessboard.h | 86 + .../camodocal/chessboard/ChessboardCorner.h | 45 + .../camodocal/chessboard/ChessboardQuad.h | 29 + .../include/camodocal/chessboard/Spline.h | 319 + .../gpl/EigenQuaternionParameterization.h | 40 + .../include/camodocal/gpl/EigenUtils.h | 418 ++ camera_model/include/camodocal/gpl/gpl.h | 111 + .../camodocal/sparse_graph/Transform.h | 38 + camera_model/instruction | 1 + camera_model/package.xml | 54 + camera_model/readme.md | 15 + camera_model/src/calib/CameraCalibration.cc | 571 ++ camera_model/src/camera_models/Camera.cc | 248 + .../src/camera_models/CameraFactory.cc | 174 + camera_model/src/camera_models/CataCamera.cc | 1006 +++ .../src/camera_models/CostFunctionFactory.cc | 1208 ++++ .../src/camera_models/EquidistantCamera.cc | 820 +++ .../src/camera_models/PinholeCamera.cc | 881 +++ .../src/camera_models/ScaramuzzaCamera.cc | 833 +++ camera_model/src/chessboard/Chessboard.cc | 1982 ++++++ .../gpl/EigenQuaternionParameterization.cc | 46 + camera_model/src/gpl/gpl.cc | 928 +++ camera_model/src/intrinsic_calib.cc | 247 + camera_model/src/sparse_graph/Transform.cc | 77 + 117 files changed, 30284 insertions(+) create mode 100644 blaser_ros/BlaserCommandsReadMe.md create mode 100644 blaser_ros/CMakeLists.txt create mode 100644 blaser_ros/README.md create mode 100644 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camera_model/src/camera_models/PinholeCamera.cc create mode 100644 camera_model/src/camera_models/ScaramuzzaCamera.cc create mode 100644 camera_model/src/chessboard/Chessboard.cc create mode 100644 camera_model/src/gpl/EigenQuaternionParameterization.cc create mode 100644 camera_model/src/gpl/gpl.cc create mode 100644 camera_model/src/intrinsic_calib.cc create mode 100644 camera_model/src/sparse_graph/Transform.cc diff --git a/blaser_ros/BlaserCommandsReadMe.md b/blaser_ros/BlaserCommandsReadMe.md new file mode 100644 index 0000000..2631115 --- /dev/null +++ b/blaser_ros/BlaserCommandsReadMe.md @@ -0,0 +1,50 @@ + +# Blaser Commands Readme + +## -------Quick start Method-------- + + ### Step 0: Plug in Blaser's USB3 and USB2 cable to NUC + You will see the LED and Blue laser pulse once, then Blue laser turns on, then the sensor is ready! + + ### Short-Step 1: Bring up Blaser sensor + `roslaunch blaser_ros bring_up_blaser.launch` + + ### Short-Step 2: Start up Blaser SLAM backend and Mapping GUI + `roslaunch blaser_ros trl6_slam.launch` + +## -------Step-by-Step Method-------- + + ### Step 0: Plug in Blaser's USB3 and USB2 cable to NUC + You will see the LED and Blue laser pulse once, then Blue laser turns on, then the sensor is ready! + + ### Step 1: open roscore at terminal #1 + `roscore` + + ### Step 2: Allow port access for Blaser low-level control + `sudo chmod 666 /dev/ttyACM0` + + ### Step 3: Turn on Blaser Camera device driver + `rosrun blaser_pcl_core handheld_blaser_v30_node --lexp_val 50` + + ### Step 4: Start up Blaser Machine Vision frontend + `roslaunch blaser_ros trl6_sensor_proc.launch` + + ### Step 5: Start up Blaser SLAM backend and Mapping GUI + `roslaunch blaser_ros trl6_slam.launch` + +## -------How to stitch point cloud-------- + + ### To use mapping GUI: + ### You need to change the "Mapping status" Slider/Parameter: + ### - 0: Stop Map Generation + ### - 1: Start Stitching Point Cloud Map + ### - 2: Clear Map + + ### Always start from 0(stop) stage, when Blaser initialized, then trun on 1(start) to stitch point cloud, and end with move back to 0 to stop. + ### you can also slide it to 2(Clear map). + +## -------How to Save point cloud-------- + + ### Save pointcloud (colorized, accumulated) + `rosrun pcl_ros pointcloud_to_pcd input:=/slam_estimator/laser_pcd` + `rosrun pcl_ros pointcloud_to_pcd input:=/laser_detector/laser_points` diff --git a/blaser_ros/CMakeLists.txt b/blaser_ros/CMakeLists.txt new file mode 100644 index 0000000..3d82f87 --- /dev/null +++ b/blaser_ros/CMakeLists.txt @@ -0,0 +1,100 @@ +cmake_minimum_required(VERSION 2.8.3) +project(blaser_ros) + +set(CMAKE_BUILD_TYPE Release) + +execute_process(COMMAND lsb_release -cs + OUTPUT_VARIABLE LSB_RELEASE_ID_SHORT +) + +if(${LSB_RELEASE_ID_SHORT} MATCHES "bionic") + set(CMAKE_CXX_STANDARD_REQUIRED 11) + message("-- Systemm version: ${LSB_RELEASE_ID_SHORT}, set to C++11") +elseif(${LSB_RELEASE_ID_SHORT} MATCHES "focal") + set(CMAKE_CXX_STANDARD_REQUIRED 11) + message("-- Systemm version: ${LSB_RELEASE_ID_SHORT}, set to C++14") +endif() + +set(CMAKE_CXX_FLAGS_RELEASE "-O3 -Wall -g") + +find_package(catkin REQUIRED COMPONENTS + geometry_msgs + pcl_conversions + pcl_ros + roscpp + sensor_msgs + std_msgs + cv_bridge + camera_model + dynamic_reconfigure +) + +find_package(OpenCV REQUIRED) +find_package(Eigen3 REQUIRED) +find_package(PythonLibs 2.7) + +generate_dynamic_reconfigure_options( + cfg/LaserDetector.cfg +) + +catkin_package( + INCLUDE_DIRS include + LIBRARIES laser_stripe + CATKIN_DEPENDS geometry_msgs pcl_conversions pcl_ros roscpp sensor_msgs std_msgs + dynamic_reconfigure +# DEPENDS system_lib +) + +########### +## Build ## +########### + +## Specify additional locations of header files +## Your package locations should be listed before other locations +include_directories( + include + ${catkin_INCLUDE_DIRS} + ${EIGEN3_INCLUDE_DIR} + /usr/include/python3.8 +) + +## Declare a C++ library +add_library(laser_stripe + src/laser_stripe_detector.cpp + src/laser_geometry_utils.cpp +) +target_link_libraries(laser_stripe ${catkin_LIBRARIES} ${OpenCV_LIBS}) + +add_executable(laser_stripe_detector_test + src/test/laser_stripe_detector_test.cpp + src/laser_stripe_detector.cpp) +target_link_libraries(laser_stripe_detector_test ${catkin_LIBRARIES} ${OpenCV_LIBS}) + +add_executable(laser_calib + src/laser_calib.cpp + src/laser_calib_node.cpp + src/laser_stripe_detector.cpp + src/util/cv_click_handler.cpp) +target_link_libraries(laser_calib ${catkin_LIBRARIES} ${OpenCV_LIBS} + ${PYTHON_LIBRARIES}) + + +add_executable(laser_detector + src/laser_detector.cpp + src/laser_detector_node.cpp + src/laser_geometry_utils.cpp + src/laser_stripe_detector.cpp + ) +add_dependencies(laser_detector ${PROJECT_NAME}_gencfg) +target_link_libraries(laser_detector ${catkin_LIBRARIES} ${OpenCV_LIBS}) + +add_executable(laser_rgb_estimator + src/laser_rgb_estimator.cpp + src/util/geometry_util.cpp + src/laser_rgb_estimator_node.cpp) +target_link_libraries(laser_rgb_estimator ${catkin_LIBRARIES} ${OpenCV_LIBS}) + +add_executable(resolution_analyser + src/resolution_analyser.cpp) +target_link_libraries(resolution_analyser ${catkin_LIBRARIES} ${OpenCV_LIBS} + ${PYTHON_LIBRARIES}) diff --git a/blaser_ros/README.md b/blaser_ros/README.md new file mode 100644 index 0000000..836c0cc --- /dev/null +++ b/blaser_ros/README.md @@ -0,0 +1,378 @@ +# BLASER_ROS + +This ROS package contains software for hand-held Blaser, including + +* Laser plane calibration +* Laser points detection and triangulation +* Blaser resolution (sensitivity) analyzation +* Laser point cloud coloring (RGB value estimation), which is also implemented + in the SLAM package (`blaser_slam`) + +The library `camera_model` (forked from **camodocal**) is used extensively in this +package. + +This tutorial contains three sections + +0. Installing dependencies and Blaser software +1. Running SLAM (involves calibration & running triangulation) +2. Performing sensitivity evaluation + +## 0. Installation +This section is about how to set up Blaser software on a new computer. + +### 0.0 Environment +Blaser uses Ubuntu 18.04 and ROS Melodic ([Installation](http://wiki.ros.org/melodic/Installation/Ubuntu)). + +### 0.1 Install Dependencies + +1. First make a directory for all Blaser dependencies +```shell +mkdir ~/blaser_dependencies +``` + +2. Install [Matio](https://github.com/tbeu/matio) +```shell +cd ~/blaser_dependencies +git clone git://git.code.sf.net/p/matio/matio +cd matio +./autogen.sh +./configure +make +sudo make install +``` +3. Install [Ceres Solver](http://ceres-solver.org/installation.html) +```shell +cd ~/blaser_dependencies +wget http://ceres-solver.org/ceres-solver-1.14.0.tar.gz +sudo apt-get install libgoogle-glog-dev libgflags-dev libatlas-base-dev libsuitesparse-dev +tar zxf ceres-solver-1.14.0.tar.gz +mkdir ceres-bin +cd ceres-bin +cmake ../ceres-solver-1.14.0 +make -j8 +sudo make install +``` +4. Install [XIMEA Linux Software packge](https://www.ximea.com/support/wiki/apis/XIMEA_Linux_Software_Package) +```shell +cd ~/blaser_dependencies +wget https://www.ximea.com/downloads/recent/XIMEA_Linux_SP.tgz +tar xzf XIMEA_Linux_SP.tgz +mv package ximea_linux_sp +cd ximea_linux_sp +sudo ./install +``` +5. Python libraries +```sh +sudo apt-get install python-matplotlib python-numpy +``` +6. Enable high speed USB and USB permission +```shell +sudo adduser $USER dialout +# if file /etc/rc.local already exists +echo 'echo 0 > /sys/module/usbcore/parameters/usbfs_memory_mb' | sudo tee -a /etc/rc.local +# if file /etc/rc.local does not exist +printf '%s\n' '#!/bin/bash' 'echo 0 > /sys/module/usbcore/parameters/usbfs_memory_mb' | sudo tee /etc/rc.local; sudo chmod +x /etc/rc.local +# reboot for the changes to take effect +``` + +### 0.2 Install Blaser software +1. Create a catkin workspace for blaser: +```sh +mkdir -p ~/blaser_ws/src && cd ~/blaser_ws/src +``` +2. Then clone the repo `blaser_mapping`: +```sh +git clone https://github.com/biorobotics/blaser_mapping.git +``` +3. Clone the Blaser driver called `blaser-pcl-core` located in another Git repo. +```sh +git clone https://github.com/biorobotics/blaser-pcl-core.git +``` +4. build +```shell +cd ~/blaser_ws/ +catkin_make -j1 +``` +The compilation will take some time. Please wait. + +Once the compilation is done, you would be required to add a line to `~/.bashrc` file. +Open the the bashrc file by running the following command in a terminal. + +`gedit ~/.bashrc` + +This will open the text editor and add the following line at the end of the file. + + ``` + source ~/blaser_ws/devel/setup.bash + ``` + + Save and close the text editor and run `source ~/.bashrc` for the changes to take effect. + + You can test your installation by running + + ``` + roscd blaser_ros + ``` + Upon running the above commnand, your current directory should change to - `~/blaser_ws` . + +## Run Blaser +Now you can run Blaser following [this tutorial](https://github.com/biorobotics/blaser_mapping/blob/master/blaser_ros/README.md).\ +If the Blaser is already calibrated, you can skip Step 1.2 Sensor Calibration in the linked tutorial. + +## 1. Running SLAM + +Check out our [video tutorial](https://drive.google.com/file/d/15whcikrRbo9H2MsuE5pYbJ87K-Ah5hBY/view). + +To run SLAM, there are three steps involved. Firstly, you should run the sensor +driver for your specific Blaser prototype and acquire raw sensor topics. Next, +calibrate the camera intrinsics, camera-IMU extrinsics, and camera-laser extrinsics and load the +calibration results into a yaml file. Finally, +execute SLAM by running both the SLAM front-end and the back-end. + +### 1.1 Running sensor driver + +Run the driver for your specific Blaser prototype. + +For the Blaser 3.0 (sent to Boeing version), see [`blaser-pcl-core`](https://github.com/biorobotics/blaser-pcl-core). + +Make sure you have three ROS topics: + +1. Visual frames (sensor_msgs/Image, image stream observing the environment with + the laser turned off, at least 20 hz) +2. Profiling frames (sensor_msgs/Image, image stream observing the laser stripe, + at least 20 hz) +3. IMU data (sensor_msgs/Imu, at least 100 hz) + +Visualize these topics (use rqt_image_view and rqt_plot) to check if they are +valid. Adjust camera exposure, LED brightness, and laser brightness to make sure +that + +- Visual frames are neutrally exposed. +- Profiling frames are under-exposed (dark) while the laser stripe is clearly +visible but not over-exposed (RGB channel values should not reach 255). If laser +is over-exposed, shorten camera exposure time. +- The clock of the camera and the IMU are synced. + +Generally, short camera exposure time is preferred to reduce motion blur. +Therefore, it is good practice to use maximum LED and laser brightness for +SLAM. + +### 1.2 Sensor calibration + +There are three calibration tasks: camera intrinsics, camera-IMU extrinsics, and +camera-laser extrinsics. + +prepare a folder for this calibration trial and run some basic commands: + +Say you want to name your trial folder TRIAL_FOLDER (e.g. boeing-demo) +``` +$ roscd blaser_ros; mkdir -p calib_data/TRIAL_FOLDER; cd calib_data/TRIAL_FOLDER + +$ mkdir intrinsics; mkdir laser_plane; scp ~/catkin_ws/blaser_ws/src/blaser_ros/config/laser_calib.yaml . (don't forget the "." at the end!!) + +$ scp -r ~/catkin_ws/blaser_ws/src/blaser_ros/config/kalibr_data . (don't forget the "." at the end!!) + +$ scp ~/catkin_ws/blaser_ws/src/blaser_ros/config/trl6_slam.yaml .; mv trl6_slam.yaml slam.yaml +``` + +These commands create a calibration folder and copy sample yaml files, which will +be loaded with your own calibration data later. + +#### Camera intrinsics + +**First collect images observing a checkerboard from various angles.** +It is a good idea to use ROS tool **camera_calibration** to collect images. + +1. Run the Blaser driver +2. `cd ~/catkin_ws/blaser_ws/src/blaser_ros/calib_data/TRIAL_FOLDER/intrinsics` +3. Run the ros calibration tool +`rosrun camera_calibration cameracalibrator.py --size 10x7 --square 0.005 image:=/image_topic` +4. Follow its instructions to collect images to satisfy all its score bars +5. Click calibrate, and wait until it finishes +6. Click save to save the images and the calibration results as a tarball. The + terminal will say the tarball's location, usually in `/tmp/`. +7. Move the tarball to our data folder and extract the tarball +`mv /tmp/calibrationdata.tar.gz .; tar xvf calibrationdata.tar.gz; rm calibrationdata.tar.gz; rm ost.*` + +**Secondly, use package `camera_model` to perform calibration.** +`rosrun camera_model Calibration -w 7 -h 10 -s 5 -i ./ -v --camera-model mei` + +The camera model parameters will be saved to `camera_camera_calib.yaml`. + +Use help (`rosrun camera_model Calibration --help`) to see all the parameters. + +Be careful about what camera model you use. For a narrow FoV camera without huge +distortion, use `pinhole` model should suffice. If you use a large FoV camera +with a lot of distortion, use `mei` or `kannala-brandt`. Typically you can try +all the camera models and choose the one with the smallest reprojection error. + +**Finally, examine the intrinsics parameters and result** + +1. Is the reprojection error reasonable? (should be at least < 1.0 px) +2. Is fx and fy similar? +3. Is cx and cy reasonable? cx ~ width / 2, cy ~ height / 2 +4. Is image height and width correct? + +You can also generate undistorted images. All the straight lines in real world +should appear as perfectly straight on the image. + +#### Camera-IMU extrinsics + +Now we have to calibrate the Euclidean transformation between the IMU frame and +the camera frame. + +We use **Kalibr** to perform this calibration. It is a powerful calibration tool +that can calibrate camera intrinsics, camera-IMU extrinsics, multi-camera +extrinsics, etc. Follow its instructions for installation and usage. + +A few tips: + +* Use a different catkin workspace for **Kalibr**, since it uses `catkin build`. +* Since extrinsics calibration requires camera instrinsics, you may need to redo + camera intrinsics calibration using Kalibr, if the camera model used in + `camera_model` is not compatibale with Kalibr. +* You need IMU parameters (random walk and noise for accelerometer and + gyroscope) + for both extrinsics calibration and SLAM. `Kalibr`'s wiki has a tutorial on + how to determine these four parameters. You can also use `imu_utils` package + on Github to calibrate them. +* **Kalibr**'s wiki has some great tutorials on IMU modeling. + +Trouble shooting for installing Kalibr: +1. Issue 1: Cannot find package when enter `$sudo pip install python-igraph --upgrade` +Solution: Install older version of python-igraph. Still may need to `apt install bison byacc flex`. +2. Issue 2: [Cannot reach TAMU server when building Kalibr](https://github.com/h2r/kuka_brown/issues/1) +Solution: Modify CMakeList file in SuiteSparse package and add --no-check-certificate between wget and TAMU URL + +Use the following steps to calibrate +``` +$ cd ~/catkin_ws/blaser_ws/src/blaser_ros/calib_data/TRIAL_FOLDER/intrinsics + +(We recalibrate the camera intrinsics using the pinhole model. However, we only use it for imu-camera extrinsics calibration, NOT in SLAM!) +$ rosrun camera_model Calibration -w 10 -h 7 -s 5 -i ./ -v --camera-model pinhole + +$ cd ~/catkin_ws/blaser_ws/src/blaser_ros/calib_data/TRIAL_FOLDER/kalibr_data; mkdir kalibr_results + +Then update the camchain.yaml file with the new intrinsics from ~/catkin_ws/blaser_ws/src/blaser_ros/calib_data/TRIAL_FOLDER/intrinsics/camera_camera_calib.yaml + +Then collect a bag file using aprilgrid of either 8.8mm or 5.5mm grids: + +$ rosbag record --duration=100 -O data.bag /blaser_camera/image_hexp /imu + +$ cd kalibr_results; activate_kalibr + +$ rosrun kalibr kalibr_calibrate_imu_camera --bag ../data.bag --cam ../camchain.yaml --imu ../imu.yaml --target ../april_8mm.yaml +``` + +The calibration may take a long time. After it finishes, examine the rotation +and translation result. You should have a pretty good guess from the mechanical +design CAD file or by just looking at the sensor. + +#### Camera-laser extrinsics + +The extrinsics parameters between camera and laser is the 3D position of the +laser plane in the camera reference frame, defined as $ax + by + cz + d = 0$. In +order to determine the plane's position, we take sample points from this plane +and then try to fit a 3D plane to these 3D points. We obtain sample points from +images of a checkerboard where the laser stripe is projected onto the +checkerboard. Since the checkerboard defines a 3D plane, we can get a 3D point +position for each 2D laser point on the image, which is the intersection between +the checkerboard plane and the line-of-sight ray. + +We first need to make sure that the laser stripe detection is working. The laser +stripe detector basically performs an HSV filter with five parameters hue_min, +hue_max, sat_min, val_min, and val_ratio, defining a 3D range filter H in \[hue_low, +hue_high\], S in \[sat_low, 255\], and V in +\[max(val_low, image_max_val * val_ratio), 255\]. Note that V range is dynamic +and is set with every image. + +When using red laser and you want a hue range containing the hue=180 value, +set hue_min > hue_max and the program will generate two separate hue ranges: +one is \[hue_min, 180\] and the other is \[0, hue_max\]. + +To set these parameters, first use `python scripts/im_saver.py [image_topic]` to +save a couple of sample images, then use `python scripts/im_hsv_viewer.py +[image_file]` to determine the HSV value of the laser stripe and set appropriate +values for the threshold parameters. Load these values in a config file (todo +give example config and dir), which will be used in the calibration later. + +To test these parameters, run `laser_stripe_detector` node with sample images +and the config file. (todo turn on lsd visualization). + +Perform laser calibration using the following steps: + +$ cd ~/catkin_ws/blaser_ws/src/blaser_ros/calib_data/TRIAL_FOLDER; cd laser_plane (Stay in this folder throughout Step 2!) + +$ rosrun blaser_ros im_saver.py /blaser_camera/image_lexp + +Then press 's' to save the current image. Use a [foot switch](https://www.amazon.com/s?k=foot+switch+usb) if it helps. +Collect 10~15 images with varying checkerboard depth. +Avoid collision between laser line and checkerboard corners. + +Then update the laser_calib.yaml (copy from blaser_ros/config/) file with the new camera intrinsics you got in Step 1. +The intrinsics yaml file was generated in ~/catkin_ws/blaser_ws/src/blaser_ros/calib_data/TRIAL_FOLDER/intrinsics/camera_camera_calib.yaml + +$ rosrun blaser_ros laser_calib -i ./ -c laser_calib.yaml (Press 'y' to accept, 'n' to reject current image) + +$ python ../../../scripts/vis_laser_calib_result.py calib_results.txt + +#### Finally, load your calibrated parameters to the SLAM yaml file. + +1. The big yaml file is: ~/catkin_ws/blaser_ws/src/blaser_ros/calib_data/TRIAL_FOLDER/trl6_slam.yaml +2. Camera intrinsics result is in: ~/catkin_ws/blaser_ws/src/blaser_ros/calib_data/TRIAL_FOLDER/laser_plane/laser_calib.yaml +3. Laser-camera extrinsics is in : ~/catkin_ws/blaser_ws/src/blaser_ros/calib_data/TRIAL_FOLDER/laser_plane/calib_results.txt +4. Camera-imu extrinsics is in : cd ~/catkin_ws/blaser_ws/src/blaser_ros/calib_data/TRIAL_FOLDER/kalibr_data/kalibr_results/results-imucam-..data.txt (Please copy the T_ic!) + +After updating the yaml file, here's the final command before actually running slam! +$ cd ~/catkin_ws/blaser_ws/src/blaser_ros/config; rm trl6_slam.yaml; scp ~/catkin_ws/blaser_ws/src/blaser_ros/calib_data/TRIAL_FOLDER/trl6_slam.yaml . (Don't forget the dot!!) + +If your SLAM yaml file has a different name, simply update the name in `trl6_sensor_proc.launch` and `trl6_slam.launch`. + +### 1.3 Run SLAM +1. Device driver +`rosrun blaser_pcl_core handheld_blaser_v30_node --lexp_val 50` +2. SLAM frontend +`roslaunch blaser_ros trl6_sensor_proc.launch` +3. SLAM backend +`roslaunch blaser_ros trl6_slam.launch` +4. Use `rqt_reconfigure` to control the mapping process (start / stop / clear) mapping. Mapping status: + - 0: Stop + - 1: Start + - 2: Clear +`rosrun rqt_reconfigure rqt_reconfigure` +5. Save pointcloud (colorized, accumulated) +For 3D map: `rosrun pcl_ros pointcloud_to_pcd input:=/slam_estimator/laser_pcd` +For raw laser scans `rosrun pcl_ros pointcloud_to_pcd input:=/laser_detector/laser_points` + +## 2. Perform sensitivity analysis +The sensitivity of the Blaser sensor is defined as the shift of the laser stripe +on the image in response to a 1 mm depth change. It as a unit of pixel/mm. The +higher the sensitivity, the higher the 3D measurement precision. Assuming that +the laser detection on the image has an absolute error upper bound of 0.5 pixels, +then the sensor's 3D measurement precision is 0.5 pixel / sensitivity. E.g., if +the sensitivity is 5 pixel/mm, then the precision is 0.1 mm. + +The sensitivity analysis tool can be used to theoretically analyze the sensor's +precision, but also to determine the best sensor design in terms of laser leaning +angle (angle between the laser plane and the camera optical axis, 0 being parallel). + +To perform the sensitivity analysis, run +`rosrun blaser_ros resolution_analyser `. + +A sample sensitivty_analysis_yaml_file can be found at +`blaser_ros/config/resolution_analyser/resolution_analyser.yaml`. + +## Using ROS Bag with Blaser + +If you want to record sensor data and run SLAM with recorded data offline, use +compressed image topics instead of raw image topics. This can save you GBs of +storage space. Here's what I typically do: + +1. Record: record raw sensor data only, including raw imu data and compressed +image topics. The compressed image topics are already published by the driver. +`rosbag record /imu /blaser_camera/image_hexp/compressed /blaser_camera/image_lexp/compressed` +2. Replay: since the image topics are compressed, you need to *republish* the +image topics. This is implemented in the `sensor_proc.launch` file using the +`republish_compressed_image` argument, whose default value is 0. Use the +following command when using rosbags. +`roslaunch blaser_ros xx_sensor_proc.launch republish_compressed_image:=1` diff --git a/blaser_ros/calib_result.txt b/blaser_ros/calib_result.txt new file mode 100644 index 0000000..5841e56 --- /dev/null +++ b/blaser_ros/calib_result.txt @@ -0,0 +1,5606 @@ +laser plane parameters (ax + by + cx + d = 0): +-6494.7,31.7601,-100,151.818 +laser point positions in camera frame: +lp: 0.0223723,-0.0195598,0.0563187 +lp: 0.0223641,-0.0194623,0.0563286 +lp: 0.0223598,-0.019365,0.0563371 +lp: 0.0223556,-0.0192678,0.0563456 +lp: 0.022354,-0.0191707,0.0563532 +lp: 0.0223495,-0.0190738,0.0563618 +lp: 0.0223646,-0.0189772,0.056364 +lp: 0.0223585,-0.0188805,0.056373 +lp: 0.0223782,-0.0187842,0.0563736 +lp: 0.022372,-0.0186877,0.0563827 +lp: 0.0223696,-0.0185913,0.0563906 +lp: 0.0223683,-0.018495,0.0563981 +lp: 0.0223959,-0.0183993,0.0563961 +lp: 0.0223895,-0.0183032,0.0564052 +lp: 0.0223596,-0.0182068,0.0564221 +lp: 0.0223761,-0.0181112,0.0564237 +lp: 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0.0215854,0.0959957,0.135896 +lp: 0.0218472,0.0962662,0.135734 +lp: 0.0218499,0.0965931,0.135694 +lp: 0.0219847,0.0968926,0.135591 +lp: 0.0220042,0.0972178,0.135543 diff --git a/blaser_ros/cfg/LaserDetector.cfg b/blaser_ros/cfg/LaserDetector.cfg new file mode 100644 index 0000000..c5c916c --- /dev/null +++ b/blaser_ros/cfg/LaserDetector.cfg @@ -0,0 +1,12 @@ +#!/usr/bin/env python +PACKAGE = "blaser_ros" + +from dynamic_reconfigure.parameter_generator_catkin import * + +gen = ParameterGenerator() + +gen.add("brightness_min", int_t, 0, "Lower threshold of laser brightness", 70, 0, 255) +gen.add("hue_min", int_t, 0, "Lower threshold of hue. For red, use min>max", 118, 0, 180) +gen.add("hue_max", int_t, 0, "Upper threshold of hue. For red, use min>max", 124, 0, 180) + +exit(gen.generate(PACKAGE, "blaser_ros", "LaserDetector")) \ No newline at end of file diff --git a/blaser_ros/config/cam1/cam_config/mei.yaml b/blaser_ros/config/cam1/cam_config/mei.yaml new file mode 100644 index 0000000..ef9e27d --- /dev/null +++ b/blaser_ros/config/cam1/cam_config/mei.yaml @@ -0,0 +1,18 @@ +%YAML:1.0 +--- +model_type: MEI +camera_name: camera +image_width: 640 +image_height: 480 +mirror_parameters: + xi: 1.3502445948332753e+00 +distortion_parameters: + k1: -4.1188542616300872e-01 + k2: 1.6538648308362075e-01 + p1: -2.1812231602790573e-03 + p2: -7.3095517337040368e-04 +projection_parameters: + gamma1: 7.9637024491283989e+02 + gamma2: 7.9638156665611143e+02 + u0: 3.2586063178697401e+02 + v0: 2.2243680096400752e+02 diff --git a/blaser_ros/config/cam1/cam_config/pinhole.yaml b/blaser_ros/config/cam1/cam_config/pinhole.yaml new file mode 100644 index 0000000..9897166 --- /dev/null +++ b/blaser_ros/config/cam1/cam_config/pinhole.yaml @@ -0,0 +1,14 @@ +%YAML:1.0 +camera_matrix: !!opencv-matrix + rows: 3 + cols: 3 + dt: d + data: [ 340.81091, 0. , 328.9219 , + 0. , 341.29199, 224.53255, + 0. , 0. , 1. ] + +distortion_coefficients: !!opencv-matrix + rows: 1 + cols: 5 + dt: d + data: [-0.263077, 0.046754, -0.001104, -0.000508, 0.000000] diff --git a/blaser_ros/config/cam1/env_config/.checkerboard.yaml.swp b/blaser_ros/config/cam1/env_config/.checkerboard.yaml.swp new file mode 100644 index 0000000000000000000000000000000000000000..2c658953b9c5bcc883c39fc038d64c26df448ed5 GIT binary patch literal 12288 zcmeI&%SyvQ6b9g_D;M6-7l?`r(KeShwq#e_ShNU=f`|^2OOwzvl_a*f(N_?B6}LWs zYo9?}x^wMG6D1bw-trHeOeW_rnS78%$e7A$t1UGu3Zu5f*z?2N<R#$Exm+QNVHo5jTE0isfbp4PIW7!Nu>_q8V99ii!@_mqj00hPau9Hr=G0&=+I(pUD*H)#K<&&`@3?Tpk2tWV=5P$## zAOL}B7D%p2?2aCACV$A;yf2OQ`4AlhAOHafKmY;|fB*y_009U<00RF|K-i4EFEF;X zNQ-uuq0l+<*6bSRXlg(=kfZ6 vUsWhII#kn|bRB+AxDNLm-}Mqhsx_4S%FwqH&yaR%3fnkqwhs)IcKv?>xe9f< literal 0 HcmV?d00001 diff --git a/blaser_ros/config/cam1/env_config/car_toys.yaml b/blaser_ros/config/cam1/env_config/car_toys.yaml new file mode 100644 index 0000000..97765c8 --- /dev/null +++ b/blaser_ros/config/cam1/env_config/car_toys.yaml @@ -0,0 +1,6 @@ +%YAML:1.0 +laser_ROI: [0, 0, 640, 320] +red_mask_1_h: [180, 255, 255] +red_mask_1_l: [173, 120, 60] +red_mask_2_h: [7, 255, 255] +red_mask_2_l: [0, 120, 40] diff --git a/blaser_ros/config/cam1/env_config/checkerboard.yaml b/blaser_ros/config/cam1/env_config/checkerboard.yaml new file mode 100644 index 0000000..6d7d63d --- /dev/null +++ b/blaser_ros/config/cam1/env_config/checkerboard.yaml @@ -0,0 +1,8 @@ +%YAML:1.0 +image_width: 640 +image_height: 480 +laser_ROI: [100, 100, 30, 240] +red_mask_1_h_calib: [180, 255, 255] +red_mask_1_l_calib: [170, 50, 40] +red_mask_2_h_calib: [10, 255, 255] +red_mask_2_l_calib: [0, 50, 40] diff --git a/blaser_ros/config/cam1/target_config/checkerboard.yaml b/blaser_ros/config/cam1/target_config/checkerboard.yaml new file mode 100644 index 0000000..2fa43b3 --- /dev/null +++ b/blaser_ros/config/cam1/target_config/checkerboard.yaml @@ -0,0 +1,5 @@ +%YAML:1.0 +target_rows: 6 +target_cols: 9 +square_size: 0.03 # meters + diff --git a/blaser_ros/config/cam1/target_config/small_cb.yaml b/blaser_ros/config/cam1/target_config/small_cb.yaml new file mode 100644 index 0000000..057ad3e --- /dev/null +++ b/blaser_ros/config/cam1/target_config/small_cb.yaml @@ -0,0 +1,5 @@ +%YAML:1.0 +target_rows: 4 +target_cols: 6 +square_size: 0.03 # meters + diff --git a/blaser_ros/config/cam2/cam_config/icra2021.yaml b/blaser_ros/config/cam2/cam_config/icra2021.yaml new file mode 100644 index 0000000..93254ae --- /dev/null +++ b/blaser_ros/config/cam2/cam_config/icra2021.yaml @@ -0,0 +1,18 @@ +%YAML:1.0 +--- +model_type: MEI +camera_name: camera +image_width: 720 +image_height: 405 +mirror_parameters: + xi: 5.7602570603247061e-01 +distortion_parameters: + k1: -2.9874126664667061e-01 + k2: 9.5203350651380483e-02 + p1: 1.2930551699230442e-03 + p2: 2.7809768896184871e-03 +projection_parameters: + gamma1: 5.3270089970665867e+02 + gamma2: 5.3065647080334850e+02 + u0: 3.7609043648964234e+02 + v0: 1.9528125567529517e+02 diff --git a/blaser_ros/config/cam2/cam_config/mei.yaml b/blaser_ros/config/cam2/cam_config/mei.yaml new file mode 100644 index 0000000..fd79d0c --- /dev/null +++ b/blaser_ros/config/cam2/cam_config/mei.yaml @@ -0,0 +1,18 @@ +%YAML:1.0 +--- +model_type: MEI +camera_name: camera +image_width: 720 +image_height: 405 +mirror_parameters: + xi: 2.4416168888295084e+00 +distortion_parameters: + k1: 6.8975571389416923e-01 + k2: 2.1430508545870555e+00 + p1: -2.8123712670124939e-03 + p2: 7.6976435411558780e-05 +projection_parameters: + gamma1: 1.1219520741661877e+03 + gamma2: 1.1238613806730066e+03 + u0: 3.8054382166138168e+02 + v0: 1.9654743230743148e+02 diff --git a/blaser_ros/config/cam2/cam_config/ost.yaml b/blaser_ros/config/cam2/cam_config/ost.yaml new file mode 100644 index 0000000..544cab4 --- /dev/null +++ b/blaser_ros/config/cam2/cam_config/ost.yaml @@ -0,0 +1,20 @@ +image_width: 720 +image_height: 405 +camera_name: narrow_stereo +camera_matrix: + rows: 3 + cols: 3 + data: [327.569953, 0.000000, 366.279963, 0.000000, 328.646347, 200.676051, 0.000000, 0.000000, 1.000000] +distortion_model: plumb_bob +distortion_coefficients: + rows: 1 + cols: 5 + data: [-0.212206, 0.032621, -0.000697, 0.000473, 0.000000] +rectification_matrix: + rows: 3 + cols: 3 + data: [1.000000, 0.000000, 0.000000, 0.000000, 1.000000, 0.000000, 0.000000, 0.000000, 1.000000] +projection_matrix: + rows: 3 + cols: 4 + data: [218.516113, 0.000000, 369.899502, 0.000000, 0.000000, 298.828003, 199.878592, 0.000000, 0.000000, 0.000000, 1.000000, 0.000000] diff --git a/blaser_ros/config/cam2/cam_config/pinhole.yaml b/blaser_ros/config/cam2/cam_config/pinhole.yaml new file mode 100644 index 0000000..40eeb3e --- /dev/null +++ b/blaser_ros/config/cam2/cam_config/pinhole.yaml @@ -0,0 +1,14 @@ +%YAML:1.0 +camera_matrix: !!opencv-matrix + rows: 3 + cols: 3 + dt: d + data: [ 327.569953, 0.000000, 366.279963, + 0.000000, 328.646347, 200.676051, + 0.000000, 0.000000, 1.000000] + +distortion_coefficients: !!opencv-matrix + rows: 1 + cols: 5 + dt: d + data: [-0.212206, 0.032621, -0.000697, 0.000473, 0.000000] diff --git a/blaser_ros/config/cam2/env_config/.checkerboard.yaml.swp b/blaser_ros/config/cam2/env_config/.checkerboard.yaml.swp new file mode 100644 index 0000000000000000000000000000000000000000..2c658953b9c5bcc883c39fc038d64c26df448ed5 GIT binary patch literal 12288 zcmeI&%SyvQ6b9g_D;M6-7l?`r(KeShwq#e_ShNU=f`|^2OOwzvl_a*f(N_?B6}LWs zYo9?}x^wMG6D1bw-trHeOeW_rnS78%$e7A$t1UGu3Zu5f*z?2N<R#$Exm+QNVHo5jTE0isfbp4PIW7!Nu>_q8V99ii!@_mqj00hPau9Hr=G0&=+I(pUD*H)#K<&&`@3?Tpk2tWV=5P$## zAOL}B7D%p2?2aCACV$A;yf2OQ`4AlhAOHafKmY;|fB*y_009U<00RF|K-i4EFEF;X zNQ-uuq0l+<*6bSRXlg(=kfZ6 vUsWhII#kn|bRB+AxDNLm-}Mqhsx_4S%FwqH&yaR%3fnkqwhs)IcKv?>xe9f< literal 0 HcmV?d00001 diff --git a/blaser_ros/config/cam2/env_config/car_toys.yaml b/blaser_ros/config/cam2/env_config/car_toys.yaml new file mode 100644 index 0000000..97765c8 --- /dev/null +++ b/blaser_ros/config/cam2/env_config/car_toys.yaml @@ -0,0 +1,6 @@ +%YAML:1.0 +laser_ROI: [0, 0, 640, 320] +red_mask_1_h: [180, 255, 255] +red_mask_1_l: [173, 120, 60] +red_mask_2_h: [7, 255, 255] +red_mask_2_l: [0, 120, 40] diff --git a/blaser_ros/config/cam2/env_config/checkerboard.yaml b/blaser_ros/config/cam2/env_config/checkerboard.yaml new file mode 100644 index 0000000..9675880 --- /dev/null +++ b/blaser_ros/config/cam2/env_config/checkerboard.yaml @@ -0,0 +1,8 @@ +%YAML:1.0 +image_width: 720 +image_height: 405 +laser_ROI: [100, 100, 30, 100] +red_mask_1_h_calib: [180, 255, 255] +red_mask_1_l_calib: [170, 50, 40] +red_mask_2_h_calib: [10, 255, 255] +red_mask_2_l_calib: [0, 50, 40] diff --git a/blaser_ros/config/cam2/target_config/5mm_9x6.yaml b/blaser_ros/config/cam2/target_config/5mm_9x6.yaml new file mode 100644 index 0000000..79dc497 --- /dev/null +++ b/blaser_ros/config/cam2/target_config/5mm_9x6.yaml @@ -0,0 +1,5 @@ +%YAML:1.0 +target_rows: 6 +target_cols: 9 +square_size: 0.005 # meters + diff --git a/blaser_ros/config/cam2/target_config/checkerboard.yaml b/blaser_ros/config/cam2/target_config/checkerboard.yaml new file mode 100644 index 0000000..2fa43b3 --- /dev/null +++ b/blaser_ros/config/cam2/target_config/checkerboard.yaml @@ -0,0 +1,5 @@ +%YAML:1.0 +target_rows: 6 +target_cols: 9 +square_size: 0.03 # meters + diff --git a/blaser_ros/config/cam2/target_config/small_cb.yaml b/blaser_ros/config/cam2/target_config/small_cb.yaml new file mode 100644 index 0000000..057ad3e --- /dev/null +++ b/blaser_ros/config/cam2/target_config/small_cb.yaml @@ -0,0 +1,5 @@ +%YAML:1.0 +target_rows: 4 +target_cols: 6 +square_size: 0.03 # meters + diff --git a/blaser_ros/config/resolution_analyser/res_analyser.yaml b/blaser_ros/config/resolution_analyser/res_analyser.yaml new file mode 100644 index 0000000..bb604ac --- /dev/null +++ b/blaser_ros/config/resolution_analyser/res_analyser.yaml @@ -0,0 +1,35 @@ +%YAML:1.0 +--- +# camera intrinsics +model_type: MEI +camera_name: camera +image_width: 720 +image_height: 405 +mirror_parameters: + xi: 5.7602570603247061e-01 +distortion_parameters: + k1: -2.9874126664667061e-01 + k2: 9.5203350651380483e-02 + p1: 1.2930551699230442e-03 + p2: 2.7809768896184871e-03 +projection_parameters: + gamma1: 5.3270089970665867e+02 + gamma2: 5.3065647080334850e+02 + u0: 3.7609043648964234e+02 + v0: 1.9528125567529517e+02 + +# laser projector +baseline: 0.01 # 1cm +elevation_min: -0.78 # 45 degrees +elevation_max: 0.78 + +# depth distribution +depth_type: Gaussian +depth_min: 0.025 +depth_max: 0.1 +depth_mean: 0.03 +depth_std: 0.02 + +# laser angle params +theta_min: 0.0 # verticle +theta_max: 1.2 # around 70 degrees \ No newline at end of file diff --git a/blaser_ros/config/trl6_calib.yaml b/blaser_ros/config/trl6_calib.yaml new file mode 100644 index 0000000..fcbc3b4 --- /dev/null +++ b/blaser_ros/config/trl6_calib.yaml @@ -0,0 +1,44 @@ +%YAML:1.0 + +# camera +model_type: MEI +camera_name: camera +image_width: 1000 +image_height: 700 +mirror_parameters: + xi: 1.1933299845008256e+00 +distortion_parameters: + k1: -1.0307532762135361e+00 + k2: 7.2867705739311539e-01 + p1: -1.7115108692878054e-03 + p2: -2.3862940682902107e-04 +projection_parameters: + gamma1: 1.5368900494749112e+03 + gamma2: 1.5396215746367591e+03 + u0: 5.0511964199941451e+02 + v0: 2.1642723738028127e+02 +width: 1000 +height: 700 + + +# checkerboard parameters +target_rows: 7 +target_cols: 10 +square_size: 0.005 # meters + +# laser detection parameters for HSV thresholding +# For red laser that +hue_min: 118 +hue_max: 124 +sat_min: 150 +val_min: 70 # brightness +val_ratio: 0.05 # val_thresh = max(val_min, image_max_val * val_ratio) + +segment_length_min: 1 + +laser_ROI: [500, 100, 0, 0] # boundary width on left, right, top, bottom + +vis_laser_detection: 0 +laser_horizontal: 0 + + diff --git a/blaser_ros/config/trl6_slam.rviz b/blaser_ros/config/trl6_slam.rviz new file mode 100644 index 0000000..27f11c1 --- /dev/null +++ b/blaser_ros/config/trl6_slam.rviz @@ -0,0 +1,853 @@ +Panels: + - Class: rviz/Displays + Help Height: 0 + Name: Displays + Property Tree Widget: + Expanded: + - /Global Options1 + - /VIO1 + - /VIO1/TF1/Frames1 + - /VIO1/TF1/Tree1 + - /VIO1/LaserVisibleWindow1/Autocompute Value Bounds1 + - /Map1/LaserRGB1/Autocompute Value Bounds1 + - /Map1/LaserCnt1/Autocompute Value Bounds1 + Splitter Ratio: 0.4651159942150116 + Tree Height: 402 + - Class: rviz/Selection + Name: Selection + - Class: rviz/Tool Properties + Expanded: + - /2D Pose Estimate1 + - /2D Nav Goal1 + - /Publish Point1 + Name: Tool Properties + Splitter Ratio: 0.5886790156364441 + - Class: rviz/Views + Expanded: + - /Current View1 + Name: Views + Splitter Ratio: 0.5 + - Class: rviz/Time + Experimental: false + Name: Time + SyncMode: 0 + SyncSource: "" + - Class: rviz/Displays + Help Height: 78 + Name: Displays + Property Tree Widget: + Expanded: + - /VIO1/LaserVisibleWindow1/Autocompute Value Bounds1 + - /Map1/LaserRGB1/Autocompute Value Bounds1 + - /Map1/LaserCnt1/Autocompute Value Bounds1 + Splitter Ratio: 0.5 + Tree Height: 363 +Preferences: + PromptSaveOnExit: true +Toolbars: + toolButtonStyle: 2 +Visualization Manager: + Class: "" + Displays: + - Alpha: 0.5 + Cell Size: 0.009999999776482582 + Class: rviz/Grid + Color: 130; 130; 130 + Enabled: false + Line Style: + Line Width: 0.029999999329447746 + Value: Lines + Name: Grid + Normal Cell Count: 0 + Offset: + X: 0 + Y: 0 + Z: -0.05000000074505806 + Plane: XY + Plane Cell Count: 100 + Reference Frame: + Value: false + - Class: rviz/Axes + Enabled: false + Length: 1 + Name: Axes + Radius: 0.10000000149011612 + Reference Frame: + Value: false + - Class: rviz/Image + Enabled: true + Image Topic: /feature_tracker/feature_img + Max Value: 1 + Median window: 5 + Min Value: 0 + Name: tracked image + Normalize Range: true + Queue Size: 2 + Transport Hint: raw + Unreliable: false + Value: true + - Class: rviz/Image + Enabled: false + Image Topic: /laser_detector/laser_vis_image + Max Value: 1 + Median window: 5 + Min Value: 0 + Name: LaserVisImage + Normalize Range: true + Queue Size: 2 + Transport Hint: raw + Unreliable: false + Value: false + - Class: rviz/Group + Displays: + - Alpha: 1 + Buffer Length: 1 + Class: rviz/Path + Color: 0; 255; 0 + Enabled: false + Head Diameter: 0.30000001192092896 + Head Length: 0.20000000298023224 + Length: 0.30000001192092896 + Line Style: Lines + Line Width: 0.029999999329447746 + Name: Path + Offset: + X: 0 + Y: 0 + Z: 0 + Pose Color: 255; 85; 255 + Pose Style: None + Radius: 0.029999999329447746 + Shaft Diameter: 0.10000000149011612 + Shaft Length: 0.10000000149011612 + Topic: /vins_estimator/path + Unreliable: false + Value: false + - Class: rviz/MarkerArray + Enabled: true + Marker Topic: /vins_estimator/camera_pose_visual + Name: camera_visual + Namespaces: + {} + Queue Size: 100 + Value: true + - Alpha: 1 + Autocompute Intensity Bounds: false + Autocompute Value Bounds: + Max Value: 10 + Min Value: -10 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud + Color: 255; 255; 255 + Color Transformer: FlatColor + Decay Time: 3000 + Enabled: false + Invert Rainbow: true + Max Color: 0; 0; 0 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: history_point + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 1 + Size (m): 0.5 + Style: Points + Topic: /vins_estimator/history_cloud + Unreliable: false + Use Fixed Frame: true + Use rainbow: false + Value: false + - Class: rviz/TF + Enabled: true + Frame Timeout: 1000 + Frames: + All Enabled: false + Marker Scale: 0.05000000074505806 + Name: TF + Show Arrows: false + Show Axes: true + Show Names: true + Tree: + {} + Update Interval: 0 + Value: true + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 0.20000000298023224 + Min Value: -0.22112953662872314 + Value: false + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud + Color: 52; 101; 164 + Color Transformer: FlatColor + Decay Time: 0 + Enabled: true + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: LaserVisibleWindow + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 3 + Size (m): 0.00019999999494757503 + Style: Points + Topic: /slam_estimator/laser_visible + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: true + - Alpha: 1 + Autocompute Intensity Bounds: false + Autocompute Value Bounds: + Max Value: -0.0995621532201767 + Min Value: -0.1641932725906372 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud2 + Color: 255; 255; 255 + Color Transformer: Intensity + Decay Time: 0 + Enabled: true + Invert Rainbow: false + Max Color: 233; 185; 110 + Max Intensity: 140 + Min Color: 255; 0; 0 + Min Intensity: 50 + Name: current_point + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 13 + Size (m): 0.009999999776482582 + Style: Points + Topic: /slam_estimator/point_cloud2 + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: true + Enabled: true + Name: VIO + - Class: rviz/Group + Displays: + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 10 + Min Value: -10 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud + Color: 255; 255; 255 + Color Transformer: "" + Decay Time: 0 + Enabled: true + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: laser_cand + Position Transformer: "" + Queue Size: 10 + Selectable: true + Size (Pixels): 3 + Size (m): 0.009999999776482582 + Style: Flat Squares + Topic: /vins_estimator/vlio_dbg/lpc_cand_3d + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: true + - Alpha: 1 + Class: rviz/PointStamped + Color: 204; 41; 204 + Enabled: true + History Length: 1 + Name: feature_2d + Radius: 0.009999999776482582 + Topic: /vins_estimator/vlio_dbg/feature_pt + Unreliable: false + Value: true + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 10 + Min Value: -10 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud + Color: 252; 233; 79 + Color Transformer: FlatColor + Decay Time: 0 + Enabled: true + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: feature_3d + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 20 + Size (m): 0.009999999776482582 + Style: Points + Topic: /vins_estimator/vlio_dbg/feature_pt_3d + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: true + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 0.2196808159351349 + Min Value: 0.17004889249801636 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud + Color: 239; 41; 41 + Color Transformer: AxisColor + Decay Time: 0 + Enabled: true + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: laser_pc_3d + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 3 + Size (m): 0.009999999776482582 + Style: Points + Topic: /vins_estimator/vlio_dbg/lpc_c + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: true + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 10 + Min Value: -10 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud2 + Color: 255; 255; 255 + Color Transformer: Intensity + Decay Time: 0 + Enabled: true + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 0.2196808159351349 + Min Color: 0; 0; 0 + Min Intensity: 0.17004889249801636 + Name: laser_pc_2d + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 3 + Size (m): 0.009999999776482582 + Style: Points + Topic: /vins_estimator/vlio_dbg/lpc_cn + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: true + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 10 + Min Value: -10 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud + Color: 255; 255; 255 + Color Transformer: Intensity + Decay Time: 0 + Enabled: true + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: laser_close_3d + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 6 + Size (m): 0.009999999776482582 + Style: Points + Topic: /vins_estimator/vlio_dbg/lpc_close_3d + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: true + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 10 + Min Value: -10 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud + Color: 255; 255; 255 + Color Transformer: Intensity + Decay Time: 0 + Enabled: true + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: laser_close_2d + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 6 + Size (m): 0.009999999776482582 + Style: Points + Topic: /vins_estimator/vlio_dbg/lpc_close_2d + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: true + Enabled: true + Name: VL3d_debug + - Class: rviz/Group + Displays: + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 10 + Min Value: -10 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud2 + Color: 255; 0; 0 + Color Transformer: FlatColor + Decay Time: 0 + Enabled: true + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: NewLaserFrame + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 7 + Size (m): 9.999999747378752e-5 + Style: Points + Topic: /laser_rgb_est/new_pc_rgb + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: true + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 10 + Min Value: -10 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud2 + Color: 255; 255; 255 + Color Transformer: RGB8 + Decay Time: 1000 + Enabled: true + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: RGBLaserCloud + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 5 + Size (m): 9.999999747378752e-5 + Style: Points + Topic: /laser_rgb_est/new_pc_rgb + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: true + Enabled: true + Name: DemoVis + - Class: rviz/Group + Displays: + - Class: rviz/Marker + Enabled: false + Marker Topic: /vins_estimator/laser_normal + Name: LaserNormal + Namespaces: + {} + Queue Size: 100 + Value: false + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: -0.08294937014579773 + Min Value: -0.11999999731779099 + Value: false + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud2 + Color: 255; 255; 255 + Color Transformer: RGB8 + Decay Time: 0 + Enabled: true + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: LaserRGB + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 4 + Size (m): 0.0010000000474974513 + Style: Points + Topic: /slam_estimator/laser_pcd + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: true + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: -0.04353427141904831 + Min Value: -0.1026337519288063 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud2 + Color: 255; 255; 255 + Color Transformer: AxisColor + Decay Time: 0 + Enabled: false + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 1 + Min Color: 0; 0; 0 + Min Intensity: 1 + Name: LaserCnt + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 2 + Size (m): 0.0005000000237487257 + Style: Spheres + Topic: /vins_estimator/laser_pcd_cnt + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: false + - Class: rviz/Marker + Enabled: false + Marker Topic: /vins_estimator/laser_icp_match + Name: LaserAssociation + Namespaces: + {} + Queue Size: 100 + Value: false + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 10 + Min Value: -10 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud2 + Color: 255; 255; 255 + Color Transformer: FlatColor + Decay Time: 0 + Enabled: false + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 1 + Min Color: 0; 0; 0 + Min Intensity: 1 + Name: FeatureCnt + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 10 + Size (m): 0.004999999888241291 + Style: Points + Topic: /vins_estimator/feature_pcd + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: false + - Class: rviz/Marker + Enabled: false + Marker Topic: /vins_estimator/feature_match + Name: FeatureAssociation + Namespaces: + {} + Queue Size: 100 + Value: false + - Class: rviz/Marker + Enabled: false + Marker Topic: /vins_estimator/feature_bbox + Name: FeatureBBox + Namespaces: + {} + Queue Size: 100 + Value: false + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 10 + Min Value: -10 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud2 + Color: 204; 0; 0 + Color Transformer: FlatColor + Decay Time: 0 + Enabled: false + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: NewLaserFrame + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 5 + Size (m): 0.009999999776482582 + Style: Points + Topic: /vins_estimator/new_laser_frame + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: false + Enabled: true + Name: Map + - Class: rviz/Image + Enabled: true + Image Topic: /slam_estimator/f_on_im + Max Value: 1 + Median window: 5 + Min Value: 0 + Name: FeatureOnImage + Normalize Range: true + Queue Size: 2 + Transport Hint: raw + Unreliable: false + Value: true + - Class: rviz/Group + Displays: + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 10 + Min Value: -10 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud2 + Color: 237; 212; 0 + Color Transformer: RGB8 + Decay Time: 0 + Enabled: true + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: WorldPtCloud + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 20 + Size (m): 0.009999999776482582 + Style: Points + Topic: /vins_estimator/icp_assoc_vis/world_pt + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: true + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 10 + Min Value: -10 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud2 + Color: 239; 41; 41 + Color Transformer: RGB8 + Decay Time: 0 + Enabled: false + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: OptPtCloud + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 2 + Size (m): 0.0003000000142492354 + Style: Spheres + Topic: /vins_estimator/icp_assoc_vis/opt_pt + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: false + - Class: rviz/Marker + Enabled: false + Marker Topic: /vins_estimator/icp_assoc_vis/world_opt_link + Name: world_opt_link + Namespaces: + {} + Queue Size: 100 + Value: false + - Class: rviz/Marker + Enabled: true + Marker Topic: /vins_estimator/icp_assoc_vis/world_residual + Name: world_residual + Namespaces: + {} + Queue Size: 100 + Value: true + - Class: rviz/Marker + Enabled: false + Marker Topic: /vins_estimator/icp_assoc_vis/opt_residual + Name: opt_residual + Namespaces: + {} + Queue Size: 100 + Value: false + - Class: rviz/Marker + Enabled: true + Marker Topic: /vins_estimator/icp_assoc_vis/world_match + Name: world_match + Namespaces: + {} + Queue Size: 100 + Value: true + Enabled: false + Name: ICPAssocVis + - Class: rviz/Image + Enabled: true + Image Topic: /laser_detector/laser_vis_image + Max Value: 1 + Median window: 5 + Min Value: 0 + Name: Image + Normalize Range: true + Queue Size: 2 + Transport Hint: raw + Unreliable: false + Value: true + - Class: rviz/Marker + Enabled: false + Marker Topic: /slam_estimator/key_poses + Name: Marker + Namespaces: + {} + Queue Size: 100 + Value: false + Enabled: true + Global Options: + Background Color: 0; 0; 0 + Default Light: true + Fixed Frame: world + Frame Rate: 30 + Name: root + Tools: + - Class: rviz/MoveCamera + - Class: rviz/Select + - Class: rviz/FocusCamera + - Class: rviz/Measure + - Class: rviz/SetInitialPose + Theta std deviation: 0.2617993950843811 + Topic: /initialpose + X std deviation: 0.5 + Y std deviation: 0.5 + - Class: rviz/SetGoal + Topic: /move_base_simple/goal + - Class: rviz/PublishPoint + Single click: true + Topic: /clicked_point + Value: true + Views: + Current: + Class: rviz/Orbit + Distance: 0.2010522037744522 + Enable Stereo Rendering: + Stereo Eye Separation: 0.05999999865889549 + Stereo Focal Distance: 1 + Swap Stereo Eyes: false + Value: false + Focal Point: + X: 0.0039941612631082535 + Y: -0.012956541031599045 + Z: -0.06377584487199783 + Focal Shape Fixed Size: true + Focal Shape Size: 0.05000000074505806 + Invert Z Axis: false + Name: Current View + Near Clip Distance: 0.009999999776482582 + Pitch: 1.5647963285446167 + Target Frame: + Value: Orbit (rviz) + Yaw: 1.4595123529434204 + Saved: ~ +Window Geometry: + Displays: + collapsed: false + FeatureOnImage: + collapsed: false + Height: 1385 + Hide Left Dock: false + Hide Right Dock: true + Image: + collapsed: false + LaserVisImage: + collapsed: false + QMainWindow State: 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+ Selection: + collapsed: false + Time: + collapsed: false + Tool Properties: + collapsed: false + Views: + collapsed: true + Width: 1759 + X: 67 + Y: 27 + tracked image: + collapsed: false diff --git a/blaser_ros/config/trl6_slam.yaml b/blaser_ros/config/trl6_slam.yaml new file mode 100644 index 0000000..e38b199 --- /dev/null +++ b/blaser_ros/config/trl6_slam.yaml @@ -0,0 +1,170 @@ +%YAML:1.0 + +sensor_type: 0 # 0 for blaser, 1 for pipeblaser + +#common parameters +imu_topic: "/imu" +laser_topic: "/laser_detector/laser_points" +image_visual_topic: "/blaser_camera/image_hexp" +image_profile_topic: "/blaser_camera/image_lexp" +output_path: "/home/blaser/Desktop/vins_output" + +# camera + +# 0821 LL using KB model +model_type: KANNALA_BRANDT +camera_name: camera +image_width: 1000 +image_height: 700 +projection_parameters: + k2: -1.6442621295975660e-01 + k3: 3.0797322841285522e-02 + k4: -3.4880451836893055e-02 + k5: 1.8922706417464980e-02 + mu: 7.0181883970036540e+02 + mv: 7.0317268581495978e+02 + u0: 5.0629495538746147e+02 + v0: 2.1660916321486852e+02 + +# # 0820 DC version +# model_type: MEI +# camera_name: camera +# image_width: 1000 +# image_height: 700 +# mirror_parameters: +# xi: 3.1993163015418709e+01 +# distortion_parameters: +# k1: -1.1057655507699939e+01 +# k2: 4.1476619251102575e+03 +# p1: -3.5190907287160678e-02 +# p2: 2.2439209402131115e-02 +# projection_parameters: +# gamma1: 2.3106557046229165e+04 +# gamma2: 2.3149102246138438e+04 +# u0: 5.0471425675203875e+02 +# v0: 2.1937935969106067e+02 + +# # 0820 LL working version +# model_type: MEI +# camera_name: camera +# image_width: 1000 +# image_height: 700 +# mirror_parameters: +# xi: 3.2012119754785829e+01 +# distortion_parameters: +# k1: -1.1061216580375628e+01 +# k2: 4.1608246878212613e+03 +# p1: -3.5211358574601163e-02 +# p2: 2.2452561933505050e-02 +# projection_parameters: +# gamma1: 2.3119833376479648e+04 +# gamma2: 2.3162403001089599e+04 +# u0: 5.0471423124456055e+02 +# v0: 2.1937936021168335e+02 + + +# Extrinsic parameter between IMU and Camera. +estimate_extrinsic: 0 # 0 Have an accurate extrinsic parameters. We will trust the following imu^R_cam, imu^T_cam, don't change it. + # 1 Have an initial guess about extrinsic parameters. We will optimize around your initial guess. + # 2 Don't know anything about extrinsic parameters. You don't need to give R,T. We will try to calibrate it. Do some rotation movement at beginning. +#If you choose 0 or 1, you should write down the following matrix. +extrinsicRotation: !!opencv-matrix + rows: 3 + cols: 3 + dt: d + data: [-0.99961933, -0.00808748, -0.02637793, + 0.02638251, -0.0004602, -0.99965182, + 0.00807252, -0.99996719, 0.00067339] + +#Translation from camera frame to imu frame, imu^T_cam +extrinsicTranslation: !!opencv-matrix + rows: 3 + cols: 1 + dt: d + # data: [0.00416818, 0.02023904, -0.00090114] #from Kalibr + data: [0.0135, 0.013, -0.0094] # from CAD + +#feature traker paprameters +max_cnt: 100 # max feature number in feature tracking +min_dist: 20 # min distance between two features +corner_quality: 0.01 +freq: 0 # frequence (Hz) of publish tracking result. At least 10Hz for good estimation. If set 0, the frequence will be same as raw image +F_threshold: 1.0 # ransac threshold (pixel) +show_track: 1 # publish tracking image as topic +equalize: 0 # if image is too dark or light, trun on equalize to find enough features +fisheye: 0 # if using fisheye, trun on it. A circle mask will be loaded to remove edge noisy points + +#optimization parameters +max_solver_time: 0.022 # max solver itration time (ms), to guarantee real time +max_num_iterations: 8 # max solver itrations, to guarantee real time +keyframe_parallax: 30.0 # 30 # keyframe selection threshold (pixel) + +#imu parameters The more accurate parameters you provide, the better performance +acc_n: 0.1 # accelerometer measurement noise standard deviation. #0.2 +gyr_n: 0.02 # gyroscope measurement noise standard deviation. #0.05 +acc_w: 0.01 # accelerometer bias random work noise standard deviation. #0.02 +gyr_w: 2.0e-5 # gyroscope bias random work noise standard deviation. #4.0e-5 + +#acc_n: 0.2 #0.01 # accelerometer measurement noise standard deviation. #0.2 +#gyr_n: 0.05 #0.0025 # gyroscope measurement noise standard deviation. #0.05 +#acc_w: 0.02 #0.001 # accelerometer bias random work noise standard deviation. #0.02 +#gyr_w: 4.0e-5 #2.0e-6 # gyroscope bias random work noise standard deviation. #4.0e-5 + + +g_norm: 9.80665 # gravity magnitude + +#loop closure parameters +loop_closure: 0 # start loop closure +load_previous_pose_graph: 0 # load and reuse previous pose graph; load from 'pose_graph_save_path' +fast_relocalization: 0 # useful in real-time and large project +pose_graph_save_path: "/home/ubuntu/Desktop/vins_output/pose_graph/" # save and load path + +#unsynchronization parameters +estimate_td: 1 # online estimate time offset between camera and imu +td: 0.0 # initial value of time offset. unit: s. readed image clock + td = real image clock (IMU clock) + +#rolling shutter parameters +rolling_shutter: 1 # 0: global shutter camera, 1: rolling shutter camera +rolling_shutter_tr: 0 # unit: s. rolling shutter read out time per frame (from data sheet). + +static_initialization: 0 + +#visualization parameters +save_image: 0 # save image in pose graph for visualization prupose; you can close this function by setting 0 +visualize_imu_forward: 0 # output imu forward propogation to achieve low latency and high frequence results +visualize_camera_size: 0.01 # size of camera marker in RVIZ +visualize_camera_line_width: 0.002 + +use_encoder: 0 + +# image parameters +width: 1000 +height: 700 +center_u: 5.0471423124456055e+02 +center_v: 2.1937936021168335e+02 + +# laser triangulation parameters +# laser_plane: [-4613.02,3.924,-100,109.235] # old working ver +laser_plane: [-5992.34,34.5386,-100,140.78] #0821LL +# laser_plane: [-5719.46,31.6129,-100.0,134.645] # Daqian based on 0820LL +#laser plane: [-6801.8,45.8367,-100.0,159.858] # 0820LL data +#laser plane: [-10427.9,78.6371,-100.0,238.168] # 0819 data +laser_depth_range: [0.01, 1.0] # distance between 3d point & camera + +# laser detection parameters +hue_min: 118 +hue_max: 124 +sat_min: 150 +val_min: 70 # brightness +val_ratio: 0.05 # val_thresh = max(val_min, image_max_val * val_ratio) + +segment_length_min: 1 + +laser_ROI: [500, 100, 0, 0] # boundary width on left, right, top, bottom + +vis_laser_detection: 0 +laser_horizontal: 0 + +#mask_file: "/home/pipe/catkin_ws/pipe_blaser_ws/src/pipe_blaser_ros/config/v2_mask.png" +mask_file: "/home/blaser/catkin_ws/blaser_ws/src/pipe_blaser_ros/config/mask_v2_170d.png" + diff --git a/blaser_ros/config/trl6_slam_0821LL_Final.yaml b/blaser_ros/config/trl6_slam_0821LL_Final.yaml new file mode 100644 index 0000000..e38b199 --- /dev/null +++ b/blaser_ros/config/trl6_slam_0821LL_Final.yaml @@ -0,0 +1,170 @@ +%YAML:1.0 + +sensor_type: 0 # 0 for blaser, 1 for pipeblaser + +#common parameters +imu_topic: "/imu" +laser_topic: "/laser_detector/laser_points" +image_visual_topic: "/blaser_camera/image_hexp" +image_profile_topic: "/blaser_camera/image_lexp" +output_path: "/home/blaser/Desktop/vins_output" + +# camera + +# 0821 LL using KB model +model_type: KANNALA_BRANDT +camera_name: camera +image_width: 1000 +image_height: 700 +projection_parameters: + k2: -1.6442621295975660e-01 + k3: 3.0797322841285522e-02 + k4: -3.4880451836893055e-02 + k5: 1.8922706417464980e-02 + mu: 7.0181883970036540e+02 + mv: 7.0317268581495978e+02 + u0: 5.0629495538746147e+02 + v0: 2.1660916321486852e+02 + +# # 0820 DC version +# model_type: MEI +# camera_name: camera +# image_width: 1000 +# image_height: 700 +# mirror_parameters: +# xi: 3.1993163015418709e+01 +# distortion_parameters: +# k1: -1.1057655507699939e+01 +# k2: 4.1476619251102575e+03 +# p1: -3.5190907287160678e-02 +# p2: 2.2439209402131115e-02 +# projection_parameters: +# gamma1: 2.3106557046229165e+04 +# gamma2: 2.3149102246138438e+04 +# u0: 5.0471425675203875e+02 +# v0: 2.1937935969106067e+02 + +# # 0820 LL working version +# model_type: MEI +# camera_name: camera +# image_width: 1000 +# image_height: 700 +# mirror_parameters: +# xi: 3.2012119754785829e+01 +# distortion_parameters: +# k1: -1.1061216580375628e+01 +# k2: 4.1608246878212613e+03 +# p1: -3.5211358574601163e-02 +# p2: 2.2452561933505050e-02 +# projection_parameters: +# gamma1: 2.3119833376479648e+04 +# gamma2: 2.3162403001089599e+04 +# u0: 5.0471423124456055e+02 +# v0: 2.1937936021168335e+02 + + +# Extrinsic parameter between IMU and Camera. +estimate_extrinsic: 0 # 0 Have an accurate extrinsic parameters. We will trust the following imu^R_cam, imu^T_cam, don't change it. + # 1 Have an initial guess about extrinsic parameters. We will optimize around your initial guess. + # 2 Don't know anything about extrinsic parameters. You don't need to give R,T. We will try to calibrate it. Do some rotation movement at beginning. +#If you choose 0 or 1, you should write down the following matrix. +extrinsicRotation: !!opencv-matrix + rows: 3 + cols: 3 + dt: d + data: [-0.99961933, -0.00808748, -0.02637793, + 0.02638251, -0.0004602, -0.99965182, + 0.00807252, -0.99996719, 0.00067339] + +#Translation from camera frame to imu frame, imu^T_cam +extrinsicTranslation: !!opencv-matrix + rows: 3 + cols: 1 + dt: d + # data: [0.00416818, 0.02023904, -0.00090114] #from Kalibr + data: [0.0135, 0.013, -0.0094] # from CAD + +#feature traker paprameters +max_cnt: 100 # max feature number in feature tracking +min_dist: 20 # min distance between two features +corner_quality: 0.01 +freq: 0 # frequence (Hz) of publish tracking result. At least 10Hz for good estimation. If set 0, the frequence will be same as raw image +F_threshold: 1.0 # ransac threshold (pixel) +show_track: 1 # publish tracking image as topic +equalize: 0 # if image is too dark or light, trun on equalize to find enough features +fisheye: 0 # if using fisheye, trun on it. A circle mask will be loaded to remove edge noisy points + +#optimization parameters +max_solver_time: 0.022 # max solver itration time (ms), to guarantee real time +max_num_iterations: 8 # max solver itrations, to guarantee real time +keyframe_parallax: 30.0 # 30 # keyframe selection threshold (pixel) + +#imu parameters The more accurate parameters you provide, the better performance +acc_n: 0.1 # accelerometer measurement noise standard deviation. #0.2 +gyr_n: 0.02 # gyroscope measurement noise standard deviation. #0.05 +acc_w: 0.01 # accelerometer bias random work noise standard deviation. #0.02 +gyr_w: 2.0e-5 # gyroscope bias random work noise standard deviation. #4.0e-5 + +#acc_n: 0.2 #0.01 # accelerometer measurement noise standard deviation. #0.2 +#gyr_n: 0.05 #0.0025 # gyroscope measurement noise standard deviation. #0.05 +#acc_w: 0.02 #0.001 # accelerometer bias random work noise standard deviation. #0.02 +#gyr_w: 4.0e-5 #2.0e-6 # gyroscope bias random work noise standard deviation. #4.0e-5 + + +g_norm: 9.80665 # gravity magnitude + +#loop closure parameters +loop_closure: 0 # start loop closure +load_previous_pose_graph: 0 # load and reuse previous pose graph; load from 'pose_graph_save_path' +fast_relocalization: 0 # useful in real-time and large project +pose_graph_save_path: "/home/ubuntu/Desktop/vins_output/pose_graph/" # save and load path + +#unsynchronization parameters +estimate_td: 1 # online estimate time offset between camera and imu +td: 0.0 # initial value of time offset. unit: s. readed image clock + td = real image clock (IMU clock) + +#rolling shutter parameters +rolling_shutter: 1 # 0: global shutter camera, 1: rolling shutter camera +rolling_shutter_tr: 0 # unit: s. rolling shutter read out time per frame (from data sheet). + +static_initialization: 0 + +#visualization parameters +save_image: 0 # save image in pose graph for visualization prupose; you can close this function by setting 0 +visualize_imu_forward: 0 # output imu forward propogation to achieve low latency and high frequence results +visualize_camera_size: 0.01 # size of camera marker in RVIZ +visualize_camera_line_width: 0.002 + +use_encoder: 0 + +# image parameters +width: 1000 +height: 700 +center_u: 5.0471423124456055e+02 +center_v: 2.1937936021168335e+02 + +# laser triangulation parameters +# laser_plane: [-4613.02,3.924,-100,109.235] # old working ver +laser_plane: [-5992.34,34.5386,-100,140.78] #0821LL +# laser_plane: [-5719.46,31.6129,-100.0,134.645] # Daqian based on 0820LL +#laser plane: [-6801.8,45.8367,-100.0,159.858] # 0820LL data +#laser plane: [-10427.9,78.6371,-100.0,238.168] # 0819 data +laser_depth_range: [0.01, 1.0] # distance between 3d point & camera + +# laser detection parameters +hue_min: 118 +hue_max: 124 +sat_min: 150 +val_min: 70 # brightness +val_ratio: 0.05 # val_thresh = max(val_min, image_max_val * val_ratio) + +segment_length_min: 1 + +laser_ROI: [500, 100, 0, 0] # boundary width on left, right, top, bottom + +vis_laser_detection: 0 +laser_horizontal: 0 + +#mask_file: "/home/pipe/catkin_ws/pipe_blaser_ws/src/pipe_blaser_ros/config/v2_mask.png" +mask_file: "/home/blaser/catkin_ws/blaser_ws/src/pipe_blaser_ros/config/mask_v2_170d.png" + diff --git a/blaser_ros/config/trl6_slam_210821.yaml b/blaser_ros/config/trl6_slam_210821.yaml new file mode 100644 index 0000000..9db6365 --- /dev/null +++ b/blaser_ros/config/trl6_slam_210821.yaml @@ -0,0 +1,131 @@ +%YAML:1.0 + +sensor_type: 0 # 0 for blaser, 1 for pipeblaser + +#common parameters +imu_topic: "/imu" +laser_topic: "/laser_detector/laser_points" +image_visual_topic: "/blaser_camera/image_hexp" +image_profile_topic: "/blaser_camera/image_lexp" +output_path: "/home/dcheng/Desktop/vins_output" + +# camera +model_type: MEI +camera_name: camera +image_width: 1000 +image_height: 700 +mirror_parameters: + xi: 3.1993163015418709e+01 +distortion_parameters: + k1: -1.1057655507699939e+01 + k2: 4.1476619251102575e+03 + p1: -3.5190907287160678e-02 + p2: 2.2439209402131115e-02 +projection_parameters: + gamma1: 2.3106557046229165e+04 + gamma2: 2.3149102246138438e+04 + u0: 5.0471425675203875e+02 + v0: 2.1937935969106067e+02 + + +# Extrinsic parameter between IMU and Camera. +estimate_extrinsic: 0 # 0 Have an accurate extrinsic parameters. We will trust the following imu^R_cam, imu^T_cam, don't change it. + # 1 Have an initial guess about extrinsic parameters. We will optimize around your initial guess. + # 2 Don't know anything about extrinsic parameters. You don't need to give R,T. We will try to calibrate it. Do some rotation movement at beginning. +#If you choose 0 or 1, you should write down the following matrix. +extrinsicRotation: !!opencv-matrix + rows: 3 + cols: 3 + dt: d + data: [-0.99961933, -0.00808748, -0.02637793, + 0.02638251, -0.0004602, -0.99965182, + 0.00807252, -0.99996719, 0.00067339] + +#Translation from camera frame to imu frame, imu^T_cam +extrinsicTranslation: !!opencv-matrix + rows: 3 + cols: 1 + dt: d + data: [0.00416818, 0.02023904, -0.00090114] + + +#feature traker paprameters +max_cnt: 100 # max feature number in feature tracking +min_dist: 20 # min distance between two features +corner_quality: 0.01 +freq: 0 # frequence (Hz) of publish tracking result. At least 10Hz for good estimation. If set 0, the frequence will be same as raw image +F_threshold: 1.0 # ransac threshold (pixel) +show_track: 1 # publish tracking image as topic +equalize: 0 # if image is too dark or light, trun on equalize to find enough features +fisheye: 0 # if using fisheye, trun on it. A circle mask will be loaded to remove edge noisy points + +#optimization parameters +max_solver_time: 0.022 # max solver itration time (ms), to guarantee real time +max_num_iterations: 8 # max solver itrations, to guarantee real time +keyframe_parallax: 30.0 # 30 # keyframe selection threshold (pixel) + +#imu parameters The more accurate parameters you provide, the better performance +acc_n: 0.1 # accelerometer measurement noise standard deviation. #0.2 +gyr_n: 0.02 # gyroscope measurement noise standard deviation. #0.05 +acc_w: 0.01 # accelerometer bias random work noise standard deviation. #0.02 +gyr_w: 2.0e-5 # gyroscope bias random work noise standard deviation. #4.0e-5 + +#acc_n: 0.2 #0.01 # accelerometer measurement noise standard deviation. #0.2 +#gyr_n: 0.05 #0.0025 # gyroscope measurement noise standard deviation. #0.05 +#acc_w: 0.02 #0.001 # accelerometer bias random work noise standard deviation. #0.02 +#gyr_w: 4.0e-5 #2.0e-6 # gyroscope bias random work noise standard deviation. #4.0e-5 + + +g_norm: 9.80665 # gravity magnitude + +#loop closure parameters +loop_closure: 0 # start loop closure +load_previous_pose_graph: 0 # load and reuse previous pose graph; load from 'pose_graph_save_path' +fast_relocalization: 0 # useful in real-time and large project +pose_graph_save_path: "/home/ubuntu/Desktop/vins_output/pose_graph/" # save and load path + +#unsynchronization parameters +estimate_td: 1 # online estimate time offset between camera and imu +td: 0.0 # initial value of time offset. unit: s. readed image clock + td = real image clock (IMU clock) + +#rolling shutter parameters +rolling_shutter: 1 # 0: global shutter camera, 1: rolling shutter camera +rolling_shutter_tr: 0 # unit: s. rolling shutter read out time per frame (from data sheet). + +static_initialization: 0 + +#visualization parameters +save_image: 0 # save image in pose graph for visualization prupose; you can close this function by setting 0 +visualize_imu_forward: 0 # output imu forward propogation to achieve low latency and high frequence results +visualize_camera_size: 0.01 # size of camera marker in RVIZ +visualize_camera_line_width: 0.002 + +use_encoder: 0 + +# image parameters +width: 1000 +height: 700 +center_u: 5.0471425675203875e+02 +center_v: 2.1937935969106067e+02 + +# laser triangulation parameters +laser_plane: [-5719.46,31.6129,-100.0,134.645] +laser_depth_range: [0.01, 1.0] # distance between 3d point & camera + +# laser detection parameters +hue_min: 118 +hue_max: 124 +sat_min: 150 +val_min: 70 # brightness +val_ratio: 0.05 # val_thresh = max(val_min, image_max_val * val_ratio) + +segment_length_min: 1 + +laser_ROI: [500, 100, 0, 0] # boundary width on left, right, top, bottom + +vis_laser_detection: 0 +laser_horizontal: 0 + +#mask_file: "/home/pipe/catkin_ws/pipe_blaser_ws/src/pipe_blaser_ros/config/v2_mask.png" +mask_file: "/home/dcheng/catkin_ws/blaser_ws/src/pipe_blaser_ros/config/mask_v2_170d.png" + diff --git a/blaser_ros/config/vlio_rviz_config.rviz b/blaser_ros/config/vlio_rviz_config.rviz new file mode 100644 index 0000000..fe13f99 --- /dev/null +++ b/blaser_ros/config/vlio_rviz_config.rviz @@ -0,0 +1,844 @@ +Panels: + - Class: rviz/Displays + Help Height: 0 + Name: Displays + Property Tree Widget: + Expanded: + - /Global Options1 + - /VIO1 + - /VIO1/TF1/Frames1 + - /VIO1/TF1/Tree1 + - /VIO1/LaserVisibleWindow1/Autocompute Value Bounds1 + - /Map1/LaserRGB1/Autocompute Value Bounds1 + - /Map1/LaserCnt1/Autocompute Value Bounds1 + - /Image1 + Splitter Ratio: 0.4651159942150116 + Tree Height: 693 + - Class: rviz/Selection + Name: Selection + - Class: rviz/Tool Properties + Expanded: + - /2D Pose Estimate1 + - /2D Nav Goal1 + - /Publish Point1 + Name: Tool Properties + Splitter Ratio: 0.5886790156364441 + - Class: rviz/Views + Expanded: + - /Current View1 + Name: Views + Splitter Ratio: 0.5 + - Class: rviz/Time + Experimental: false + Name: Time + SyncMode: 0 + SyncSource: "" + - Class: rviz/Displays + Help Height: 78 + Name: Displays + Property Tree Widget: + Expanded: + - /VIO1/LaserVisibleWindow1/Autocompute Value Bounds1 + - /Map1/LaserRGB1/Autocompute Value Bounds1 + - /Map1/LaserCnt1/Autocompute Value Bounds1 + Splitter Ratio: 0.5 + Tree Height: 358 +Preferences: + PromptSaveOnExit: true +Toolbars: + toolButtonStyle: 2 +Visualization Manager: + Class: "" + Displays: + - Alpha: 0.5 + Cell Size: 0.009999999776482582 + Class: rviz/Grid + Color: 130; 130; 130 + Enabled: false + Line Style: + Line Width: 0.029999999329447746 + Value: Lines + Name: Grid + Normal Cell Count: 0 + Offset: + X: 0 + Y: 0 + Z: -0.05000000074505806 + Plane: XY + Plane Cell Count: 100 + Reference Frame: + Value: false + - Class: rviz/Axes + Enabled: false + Length: 1 + Name: Axes + Radius: 0.10000000149011612 + Reference Frame: + Value: false + - Class: rviz/Image + Enabled: true + Image Topic: /feature_tracker/feature_img + Max Value: 1 + Median window: 5 + Min Value: 0 + Name: tracked image + Normalize Range: true + Queue Size: 2 + Transport Hint: raw + Unreliable: false + Value: true + - Class: rviz/Image + Enabled: false + Image Topic: /laser_detector/laser_vis_image + Max Value: 1 + Median window: 5 + Min Value: 0 + Name: LaserVisImage + Normalize Range: true + Queue Size: 2 + Transport Hint: raw + Unreliable: false + Value: false + - Class: rviz/Group + Displays: + - Alpha: 1 + Buffer Length: 1 + Class: rviz/Path + Color: 0; 255; 0 + Enabled: false + Head Diameter: 0.30000001192092896 + Head Length: 0.20000000298023224 + Length: 0.30000001192092896 + Line Style: Lines + Line Width: 0.029999999329447746 + Name: Path + Offset: + X: 0 + Y: 0 + Z: 0 + Pose Color: 255; 85; 255 + Pose Style: None + Radius: 0.029999999329447746 + Shaft Diameter: 0.10000000149011612 + Shaft Length: 0.10000000149011612 + Topic: /vins_estimator/path + Unreliable: false + Value: false + - Class: rviz/MarkerArray + Enabled: true + Marker Topic: /vins_estimator/camera_pose_visual + Name: camera_visual + Namespaces: + {} + Queue Size: 100 + Value: true + - Alpha: 1 + Autocompute Intensity Bounds: false + Autocompute Value Bounds: + Max Value: 10 + Min Value: -10 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud + Color: 255; 255; 255 + Color Transformer: FlatColor + Decay Time: 3000 + Enabled: false + Invert Rainbow: true + Max Color: 0; 0; 0 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: history_point + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 1 + Size (m): 0.5 + Style: Points + Topic: /vins_estimator/history_cloud + Unreliable: false + Use Fixed Frame: true + Use rainbow: false + Value: false + - Class: rviz/TF + Enabled: true + Frame Timeout: 1000 + Frames: + All Enabled: false + Marker Scale: 0.05000000074505806 + Name: TF + Show Arrows: false + Show Axes: true + Show Names: true + Tree: + {} + Update Interval: 0 + Value: true + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 0.20000000298023224 + Min Value: -0.22112953662872314 + Value: false + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud + Color: 52; 101; 164 + Color Transformer: FlatColor + Decay Time: 0 + Enabled: true + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: LaserVisibleWindow + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 3 + Size (m): 0.00019999999494757503 + Style: Points + Topic: /vins_estimator/laser_window + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: true + - Alpha: 1 + Autocompute Intensity Bounds: false + Autocompute Value Bounds: + Max Value: -0.0995621532201767 + Min Value: -0.1641932725906372 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud2 + Color: 255; 255; 255 + Color Transformer: Intensity + Decay Time: 0 + Enabled: true + Invert Rainbow: false + Max Color: 233; 185; 110 + Max Intensity: 140 + Min Color: 255; 0; 0 + Min Intensity: 50 + Name: current_point + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 13 + Size (m): 0.009999999776482582 + Style: Points + Topic: /vins_estimator/point_cloud2 + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: true + Enabled: true + Name: VIO + - Class: rviz/Group + Displays: + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 10 + Min Value: -10 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud + Color: 255; 255; 255 + Color Transformer: "" + Decay Time: 0 + Enabled: true + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: laser_cand + Position Transformer: "" + Queue Size: 10 + Selectable: true + Size (Pixels): 3 + Size (m): 0.009999999776482582 + Style: Flat Squares + Topic: /vins_estimator/vlio_dbg/lpc_cand_3d + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: true + - Alpha: 1 + Class: rviz/PointStamped + Color: 204; 41; 204 + Enabled: true + History Length: 1 + Name: feature_2d + Radius: 0.009999999776482582 + Topic: /vins_estimator/vlio_dbg/feature_pt + Unreliable: false + Value: true + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 10 + Min Value: -10 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud + Color: 252; 233; 79 + Color Transformer: FlatColor + Decay Time: 0 + Enabled: true + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: feature_3d + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 20 + Size (m): 0.009999999776482582 + Style: Points + Topic: /vins_estimator/vlio_dbg/feature_pt_3d + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: true + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 0.2196808159351349 + Min Value: 0.17004889249801636 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud + Color: 239; 41; 41 + Color Transformer: AxisColor + Decay Time: 0 + Enabled: true + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: laser_pc_3d + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 3 + Size (m): 0.009999999776482582 + Style: Points + Topic: /vins_estimator/vlio_dbg/lpc_c + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: true + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 10 + Min Value: -10 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud2 + Color: 255; 255; 255 + Color Transformer: Intensity + Decay Time: 0 + Enabled: true + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 0.2196808159351349 + Min Color: 0; 0; 0 + Min Intensity: 0.17004889249801636 + Name: laser_pc_2d + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 3 + Size (m): 0.009999999776482582 + Style: Points + Topic: /vins_estimator/vlio_dbg/lpc_cn + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: true + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 10 + Min Value: -10 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud + Color: 255; 255; 255 + Color Transformer: Intensity + Decay Time: 0 + Enabled: true + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: laser_close_3d + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 6 + Size (m): 0.009999999776482582 + Style: Points + Topic: /vins_estimator/vlio_dbg/lpc_close_3d + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: true + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 10 + Min Value: -10 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud + Color: 255; 255; 255 + Color Transformer: Intensity + Decay Time: 0 + Enabled: true + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: laser_close_2d + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 6 + Size (m): 0.009999999776482582 + Style: Points + Topic: /vins_estimator/vlio_dbg/lpc_close_2d + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: true + Enabled: true + Name: VL3d_debug + - Class: rviz/Group + Displays: + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 10 + Min Value: -10 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud2 + Color: 255; 0; 0 + Color Transformer: FlatColor + Decay Time: 0 + Enabled: true + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: NewLaserFrame + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 7 + Size (m): 9.999999747378752e-5 + Style: Points + Topic: /laser_rgb_est/new_pc_rgb + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: true + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 10 + Min Value: -10 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud2 + Color: 255; 255; 255 + Color Transformer: RGB8 + Decay Time: 1000 + Enabled: true + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: RGBLaserCloud + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 5 + Size (m): 9.999999747378752e-5 + Style: Points + Topic: /laser_rgb_est/new_pc_rgb + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: true + Enabled: true + Name: DemoVis + - Class: rviz/Group + Displays: + - Class: rviz/Marker + Enabled: false + Marker Topic: /vins_estimator/laser_normal + Name: LaserNormal + Namespaces: + {} + Queue Size: 100 + Value: false + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: -0.08294937014579773 + Min Value: -0.11999999731779099 + Value: false + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud2 + Color: 255; 255; 255 + Color Transformer: RGB8 + Decay Time: 0 + Enabled: true + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: LaserRGB + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 4 + Size (m): 0.0010000000474974513 + Style: Points + Topic: /vins_estimator/laser_pcd + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: true + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: -0.04353427141904831 + Min Value: -0.1026337519288063 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud2 + Color: 255; 255; 255 + Color Transformer: AxisColor + Decay Time: 0 + Enabled: false + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 1 + Min Color: 0; 0; 0 + Min Intensity: 1 + Name: LaserCnt + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 2 + Size (m): 0.0005000000237487257 + Style: Spheres + Topic: /vins_estimator/laser_pcd_cnt + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: false + - Class: rviz/Marker + Enabled: false + Marker Topic: /vins_estimator/laser_icp_match + Name: LaserAssociation + Namespaces: + {} + Queue Size: 100 + Value: false + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 10 + Min Value: -10 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud2 + Color: 255; 255; 255 + Color Transformer: FlatColor + Decay Time: 0 + Enabled: false + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 1 + Min Color: 0; 0; 0 + Min Intensity: 1 + Name: FeatureCnt + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 10 + Size (m): 0.004999999888241291 + Style: Points + Topic: /vins_estimator/feature_pcd + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: false + - Class: rviz/Marker + Enabled: false + Marker Topic: /vins_estimator/feature_match + Name: FeatureAssociation + Namespaces: + {} + Queue Size: 100 + Value: false + - Class: rviz/Marker + Enabled: false + Marker Topic: /vins_estimator/feature_bbox + Name: FeatureBBox + Namespaces: + {} + Queue Size: 100 + Value: false + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 10 + Min Value: -10 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud2 + Color: 204; 0; 0 + Color Transformer: FlatColor + Decay Time: 0 + Enabled: false + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: NewLaserFrame + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 5 + Size (m): 0.009999999776482582 + Style: Points + Topic: /vins_estimator/new_laser_frame + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: false + Enabled: true + Name: Map + - Class: rviz/Image + Enabled: true + Image Topic: /vins_estimator/f_on_im + Max Value: 1 + Median window: 5 + Min Value: 0 + Name: Image + Normalize Range: true + Queue Size: 2 + Transport Hint: raw + Unreliable: false + Value: true + - Class: rviz/Group + Displays: + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 10 + Min Value: -10 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud2 + Color: 237; 212; 0 + Color Transformer: RGB8 + Decay Time: 0 + Enabled: true + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: WorldPtCloud + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 20 + Size (m): 0.009999999776482582 + Style: Points + Topic: /vins_estimator/icp_assoc_vis/world_pt + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: true + - Alpha: 1 + Autocompute Intensity Bounds: true + Autocompute Value Bounds: + Max Value: 10 + Min Value: -10 + Value: true + Axis: Z + Channel Name: intensity + Class: rviz/PointCloud2 + Color: 239; 41; 41 + Color Transformer: RGB8 + Decay Time: 0 + Enabled: false + Invert Rainbow: false + Max Color: 255; 255; 255 + Max Intensity: 4096 + Min Color: 0; 0; 0 + Min Intensity: 0 + Name: OptPtCloud + Position Transformer: XYZ + Queue Size: 10 + Selectable: true + Size (Pixels): 2 + Size (m): 0.0003000000142492354 + Style: Spheres + Topic: /vins_estimator/icp_assoc_vis/opt_pt + Unreliable: false + Use Fixed Frame: true + Use rainbow: true + Value: false + - Class: rviz/Marker + Enabled: false + Marker Topic: /vins_estimator/icp_assoc_vis/world_opt_link + Name: world_opt_link + Namespaces: + {} + Queue Size: 100 + Value: false + - Class: rviz/Marker + Enabled: true + Marker Topic: /vins_estimator/icp_assoc_vis/world_residual + Name: world_residual + Namespaces: + {} + Queue Size: 100 + Value: true + - Class: rviz/Marker + Enabled: false + Marker Topic: /vins_estimator/icp_assoc_vis/opt_residual + Name: opt_residual + Namespaces: + {} + Queue Size: 100 + Value: false + - Class: rviz/Marker + Enabled: true + Marker Topic: /vins_estimator/icp_assoc_vis/world_match + Name: world_match + Namespaces: + {} + Queue Size: 100 + Value: true + Enabled: false + Name: ICPAssocVis + - Class: rviz/Image + Enabled: true + Image Topic: /ring_laser_triangulator/laser_vis_image + Max Value: 1 + Median window: 5 + Min Value: 0 + Name: Image + Normalize Range: true + Queue Size: 2 + Transport Hint: raw + Unreliable: false + Value: true + Enabled: true + Global Options: + Background Color: 0; 0; 0 + Default Light: true + Fixed Frame: world + Frame Rate: 30 + Name: root + Tools: + - Class: rviz/MoveCamera + - Class: rviz/Select + - Class: rviz/FocusCamera + - Class: rviz/Measure + - Class: rviz/SetInitialPose + Theta std deviation: 0.2617993950843811 + Topic: /initialpose + X std deviation: 0.5 + Y std deviation: 0.5 + - Class: rviz/SetGoal + Topic: /move_base_simple/goal + - Class: rviz/PublishPoint + Single click: true + Topic: /clicked_point + Value: true + Views: + Current: + Class: rviz/Orbit + Distance: 2.8520445823669434 + Enable Stereo Rendering: + Stereo Eye Separation: 0.05999999865889549 + Stereo Focal Distance: 1 + Swap Stereo Eyes: false + Value: false + Focal Point: + X: 0.10116031765937805 + Y: 0.4000096321105957 + Z: 0.07418225705623627 + Focal Shape Fixed Size: true + Focal Shape Size: 0.05000000074505806 + Invert Z Axis: false + Name: Current View + Near Clip Distance: 0.009999999776482582 + Pitch: 0.004797247238457203 + Target Frame: + Value: Orbit (rviz) + Yaw: 2.7099976539611816 + Saved: ~ +Window Geometry: + Displays: + collapsed: false + Height: 2103 + Hide Left Dock: false + Hide Right Dock: true + Image: + collapsed: false + LaserVisImage: + collapsed: false + QMainWindow State: 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+ Selection: + collapsed: false + Time: + collapsed: false + Tool Properties: + collapsed: false + Views: + collapsed: true + Width: 1983 + X: 3901 + Y: 27 + tracked image: + collapsed: false diff --git a/blaser_ros/include/blaser_ros/common.h b/blaser_ros/include/blaser_ros/common.h new file mode 100644 index 0000000..cd3b384 --- /dev/null +++ b/blaser_ros/include/blaser_ros/common.h @@ -0,0 +1,32 @@ +// +// Created by dcheng on 5/28/20. +// + +#ifndef VIO_BLASER_COMMON_H +#define VIO_BLASER_COMMON_H + +#include +#include +#include +#include +#include +#include +#include + +using std::cout; +using std::endl; +using Eigen::Matrix3d; +using Eigen::Matrix4d; +using Eigen::Vector2d; +using Eigen::Vector3d; +using Eigen::Vector4d; +using Eigen::Quaterniond; +using Eigen::RowVector3d; + +template +T lerp(T a, T b, T t) +{ + return a + t * (b - a); +} + +#endif //VIO_BLASER_COMMON_H diff --git a/blaser_ros/include/blaser_ros/laser_calib.h b/blaser_ros/include/blaser_ros/laser_calib.h new file mode 100644 index 0000000..570ccea --- /dev/null +++ b/blaser_ros/include/blaser_ros/laser_calib.h @@ -0,0 +1,327 @@ +// +// Created by dcheng on 3/21/20. +// + +#ifndef VIO_BLASER_LASER_CALIB_H +#define VIO_BLASER_LASER_CALIB_H + +#include +#include +#include +#include +#include +#include +#include "camodocal/camera_models/CameraFactory.h" + +struct LaserPoint +{ + cv::Point3f pos_cam; // up to scale position in camera frame + cv::Point3f pos_cb; // up to scale position in checkerboard frame + cv::Point2f pos_cam_norm; // normalized position in camera frame [x y 1] + cv::Point2f uv_undistort; // undistorted pixel coordinates + cv::Point2f uv; + + explicit LaserPoint(const cv::Point2f& _uv, const cv::Point2f& _uv_un) + : uv_undistort(_uv_un) + , uv(_uv) + {} +}; + +struct ImCalib +{ + std::string fn; + std::string short_fn; + cv::Mat im_; + cv::Mat im_undistort_; + + // checkerboard points. the undistorted points + std::vector checkerboard_pts_, checkerboard_pts_undistort_; + std::vector laser_uv_u_, laser_uv_d_; + std::vector laser_uv_un_inlier_, laser_uv_un_outlier_; + std::vector laser_idx_inlier_, laser_idx_outlier_; + std::vector v_laser_pts; + std::vector laser_line_params; + + // transformation from checkerboard frame to camera frame + Eigen::Matrix3d R; + Eigen::Vector3d t; + + cv::Point2f laser_end_l_, laser_end_r_; + + explicit ImCalib(cv::Mat& im) + : im_(im) + , laser_line_params(4) + {} + +}; + +typedef std::shared_ptr ImCalibConstPtr; +typedef std::shared_ptr ImCalibPtr; + +typedef std::vector>::iterator v_imcalib_ptr_it; + + + +class LaserCalibCB +{ +public: + /** + * Constructor of LaserCalib class, loads config and initialize variables + * @param image_dir directory of calibration images + * @param target_config_fn checkerboard config file + * @param env_config_fn environment config file, laser detection params + * @param cam_config_fn camera intrinsics config file + */ + explicit LaserCalibCB(const std::string& image_dir, + const std::string& config_fn, + const std::string& output_fn, + bool f_calib_laser_ori); + + ~LaserCalibCB(); + + /** + * User inspects each image and decide either accept or discard + */ + void examineByImage(); + + /** + * Solve laser plane that fits the laser points. + * @param plane_param output ax + by + cz + d = 0 + * @return false if laser points number < threshold + */ + bool solveLaserPlane(Eigen::Vector4d &plane_param); + + bool solveLaserParams(const Eigen::Vector4d& plane_param, + Eigen::Vector3d& laser_ori, + Eigen::Matrix3d& Rcl, Eigen::Vector3d& tcl, + Eigen::Vector2d& fan_lb, Eigen::Vector2d& fan_rb); + +protected: + /** + * functions to load config files + */ + bool loadImages(std::string image_dir); + + virtual bool loadCamConfig(const std::string& config_fn) = 0; + bool loadTargetConfig(const std::string& config_fn); + + /** + * generate undistorted visualization image, including: + * 1. draw checkerboard + * 2. draw laser line + * 3. draw laser point inliers and outliers + * 4. write the image file name + * @param im_ptr the pointer of ImCalib object + * @param im_vis output visualization image + * @return + */ + bool genVisImage(ImCalibPtr im_ptr, cv::Mat& im_vis); + + /** + * Generate checkerboard points (3d coordinates in checkerboard frame) + */ + void genCheckerboardPoints(); + + /** + * Process a image, including undistort image, detect checkerboard points, + * compute R t to image frame using PnP, find laser points, find laser line, + * find laser points inlier and outliers, project + * @return false if anything went wrong + */ + bool procImages(); + + + virtual bool solveCheckerBoardRt(ImCalibPtr p_im) = 0; + + /** + * Delete a ImCalib object from the data set, with a given reason + * @param im_calib_it the iterator pointing to ImCalib object + * @param err_msg input the reason to delete this image + * @param iter_step_back if true, then im_calib_it--, to counter the ++ in + * outer for loop + * @return false if the iterator is invalid + */ + bool pruneImageCandidate(v_imcalib_ptr_it& im_calib_it, + const std::string& err_msg, bool iter_step_back = true); + + /** + * Fit line to 2d points using RANSAC + * @tparam pt_t point type (should be cv point) + * @tparam Vec4 + * @param pts input points + * @param line_params output line parameters (vx, vy, x0, y0) + * @param pts_inliers output inlier points + * @param pts_outliers output outlier points + * @return false if no line with enough inliers found + */ + template + bool ransacFitLine(std::vector& pts, Vec4& line_params, + std::vector& pts_inliers, + std::vector& pts_outliers, + std::vector& idx_inliers, + std::vector& idx_outliers); + + /** + * Given a line and a set of points, find inliers and outliers + * @tparam pt_t oint type (should be cv point) + * @tparam Vec4 + * @param pts input points + * @param line_params input line parameters (vx, vy, x0, y0) + * @param pts_inliers output inlier points + * @param pts_outliers output outlier points + * @param th_dist distance threshold + * @return + */ + template + bool findLineInliersOutliers(const std::vector& pts, Vec4 line_params, + std::vector& pts_inliers, std::vector& pts_outliers, + std::vector& idx_inliers, std::vector& idx_outliers, + double th_dist = 3); + + /** + * Solve a laser point's all kinds of positions from pixel coordinates + * @param lpt laser point object + * @param R rotation matrix from checkerboard frame to camera frame + * @param t translation vector from checkerboard frame to camera frame + * @return + */ + bool solveLaserPtPos(LaserPoint& lpt, Eigen::Matrix3d& R, + Eigen::Vector3d& t); + + bool ptNormToCheckerboard(const Eigen::Vector3d& pt_norm, + Eigen::Matrix3d& R, + Eigen::Vector3d& t, + Eigen::Vector3d& pt_3d, + Eigen::Vector3d& pt_cb); + + /** + * Compute the positions of all laser points in a image + * @param im input ImCalib object + * @return + */ + bool solveImageLaserPtPos(ImCalib& im); + + /** + * Evaluate plane fitting error (average distance from points to plane) + * @tparam Vec3 Eigen vector3 + * @tparam Vec4 Eigen vector4 + * @param laser_pts_pos laser point positions in camera frame + * @param plane_param plane parameters (a, b, c, d) + * @return error (average distance from points to plane in meters) + */ + template + double evalPlaneError(const std::vector& laser_pts_pos, + const Vec4& plane_param) const; + + /** + * Undistort pixels to new pixel coordinates. Opencv undistortPoints function + * outputs normalized coordinates p_n. This function gives K * p_n + * @tparam CvPoint_t cvpoint type + * @param src input distorted (original) pixel coordinates + * @param dst output undistorted pixel coordinates + */ + + virtual void undistortPixels(const std::vector& src, + std::vector& dst) = 0; + + void undistortPixel(const cv::Point2f& src, cv::Point2f& dst); + + /** + * Lift distorted pixel to normalized point + * @param pt distorted pixel coordinates uv + * @param pt_3d output normalized point position + */ + virtual void pixel2Normal(const Eigen::Vector2d& pt, Eigen::Vector3d& pt_3d) = 0; + + virtual void undistImage(const cv::Mat& src, cv::Mat& dst) = 0; + + void initClickStripeEnds(); + static void clickStripeEndsCb(int event, int x, int y, int flags, void* param); + bool clickStripeEnds(ImCalibPtr im_ptr); + + // vector of images: original, undistorted, valid images for calibration + std::vector v_im_calib_; + ImCalibPtr cur_im_ptr_; + LaserStripeDetector lsd_; + + // laser origin related + bool f_calib_laser_ori_; + std::deque laser_end_l_, laser_end_r_; + static std::string click_wn_; // click window name + cv::Mat cur_im_; + + // checkerboard + double cb_square_size_; + cv::Size cb_pattern_size_; + std::vector cb_pts_; + + std::string output_fn_; +}; + +class LaserCalibCBPinhole : public LaserCalibCB +{ +public: + explicit LaserCalibCBPinhole(const std::string& image_dir, + const std::string& config_fn, + const std::string& output_fn, + bool f_calib_laser_ori); + +private: + bool loadCamConfig(const std::string& config_fn) override ; + + bool solveCheckerBoardRt(ImCalibPtr p_im) override ; + + void undistortPixels(const std::vector& src, + std::vector& dst) override ; + + + void undistImage(const cv::Mat& src, cv::Mat& dst) override; + + void pixel2Normal(const Eigen::Vector2d& pt, Eigen::Vector3d& pt_3d); + +private: + cv::Mat K_, D_; // intrinsics +}; + +typedef std::shared_ptr LaserCalibCBPtr; +typedef std::shared_ptr LaserCalibCBPinholePtr; + +class LaserCalibCBCamodocal : public LaserCalibCB +{ +public: + explicit LaserCalibCBCamodocal(const std::string& image_dir, + const std::string& config_fn, + const std::string& output_fn, + bool f_calib_laser_ori); + +private: + bool loadCamConfig(const std::string& cam_config_fn) override ; + + bool initUndistortRectifyMap(); + + bool solveCheckerBoardRt(ImCalibPtr p_im) override ; + + void undistortPixels(const std::vector& src, + std::vector& dst) override ; + + + void undistImage(const cv::Mat& src, cv::Mat& dst) override; + + void pixel2Normal(const Eigen::Vector2d& pt, Eigen::Vector3d& pt_3d); + +private: + camodocal::CameraPtr m_camera_; + cv::Mat rect_map1_, rect_map2_, R_rect_cv_; + Eigen::Matrix3d K_rect_, R_rect_; +}; + +typedef std::shared_ptr LaserCalibCBCamodocalPtr; + + +LaserCalibCBPtr createLaserCalib(const std::string& model, + const std::string& image_dir, + const std::string& config_fn, + const std::string& output_fn, + bool f_calib_laser_ori); + +#endif //VIO_BLASER_LASER_CALIB_H diff --git a/blaser_ros/include/blaser_ros/laser_detector.h b/blaser_ros/include/blaser_ros/laser_detector.h new file mode 100644 index 0000000..c787c97 --- /dev/null +++ b/blaser_ros/include/blaser_ros/laser_detector.h @@ -0,0 +1,64 @@ +// +// Created by dcheng on 4/11/20. +// + +#ifndef LASER_DETECTOR_LASER_DETECTOR_H +#define LASER_DETECTOR_LASER_DETECTOR_H + +#include +#include +#include +#include +#include +#include +#include +#include + +#include "camodocal/camera_models/CameraFactory.h" +#include "camodocal/camera_models/CataCamera.h" +#include "camodocal/camera_models/PinholeCamera.h" + +#include +#include + +/** + * Laser Detector class. + * Only detects laser and publish 2D pixels and 3D points. + * Does not do any point cloud management work. Leave that to VLIO. + */ +class LaserDetector +{ +public: + explicit LaserDetector(std::string& config_fn, const std::string& nh_name); + +private: + void readParams(const std::string& config_fn); + + void laser_im_cb(const sensor_msgs::ImageConstPtr im_msg); + + void laser_extract_param_cb(blaser_ros::LaserDetectorConfig& config, + uint32_t level); + + /***** dynamic reconfigures *****/ + dynamic_reconfigure::Server reconfigure_server_; + dynamic_reconfigure::Server::CallbackType reconfigure_f_; + + /***** data containers *****/ + camodocal::CameraPtr m_camera_; + LaserStripeDetector lsd_; + Laser2Dto3DPtr laser_lift_; + + std::vector laser_plane_; + + std::vector laser_depth_range_; + + /***** ros subs & pubs *****/ + ros::NodeHandle nh_; + ros::Subscriber laser_im_sub_; + ros::Publisher laser_pc_pub_; + ros::Publisher laser_vis_im_pub_; + + std::string image_profile_topic_; +}; + +#endif //LASER_DETECTOR_LASER_DETECTOR_H diff --git a/blaser_ros/include/blaser_ros/laser_geometry_utils.h b/blaser_ros/include/blaser_ros/laser_geometry_utils.h new file mode 100644 index 0000000..bbda026 --- /dev/null +++ b/blaser_ros/include/blaser_ros/laser_geometry_utils.h @@ -0,0 +1,37 @@ +// +// Created by dcheng on 4/11/20. +// + +#ifndef VIO_BLASER_LASER_GEOMETRY_UTILS_H +#define VIO_BLASER_LASER_GEOMETRY_UTILS_H + +#include +#include +#include +#include + +class Laser2Dto3D +{ +public: + /** + * Constructor for class + * @tparam V4_t vector of 4, like Eigen::Vector4d, std::vector, etc. + * @param plane_params laser param vector of 4: ax + by + cz + d = 0 + */ + explicit Laser2Dto3D(const std::vector &plane_params); + + /** + * Lift 2d laser pixels to 3d space + * @param pts_norm normalized 2d pixels (undistorted) + * @param pts_3d output laser points in 3d + */ + void ptsNormTo3D(const std::vector& pts_norm, + std::vector& pts_3d); + +private: + Eigen::Vector4d plane_; +}; + +typedef std::shared_ptr Laser2Dto3DPtr; + +#endif //VIO_BLASER_LASER_GEOMETRY_UTILS_H diff --git a/blaser_ros/include/blaser_ros/laser_rgb_estimator.h b/blaser_ros/include/blaser_ros/laser_rgb_estimator.h new file mode 100644 index 0000000..d2d5708 --- /dev/null +++ b/blaser_ros/include/blaser_ros/laser_rgb_estimator.h @@ -0,0 +1,150 @@ +// +// Created by dcheng on 5/27/20. +// + +#ifndef VIO_BLASER_LASER_RGB_ESTIMATOR_H +#define VIO_BLASER_LASER_RGB_ESTIMATOR_H + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include "camodocal/camera_models/CameraFactory.h" +#include "camodocal/camera_models/CataCamera.h" +#include "camodocal/camera_models/PinholeCamera.h" + +typedef pcl::PointCloud pcl_xyz; +typedef pcl::PointCloud pcl_xyzrgb; + +class ImageFrame +{ +public: + explicit ImageFrame(cv_bridge::CvImageConstPtr p_cv_im); + + const Matrix4d &getTwc() const; + void setTwc(const Matrix4d &twc_); + + double getStamp() const; + + const cv::Mat &getImage() const; + + bool isFSetPose() const; + +private: + void changeBrightness(double alpha, double beta); + cv::Mat image_; + + double stamp_; + + Matrix4d Twc_; + + bool f_set_pose_; +}; + +typedef std::shared_ptr ImageFramePtr; + +class LaserFrame +{ +public: + explicit LaserFrame(sensor_msgs::PointCloudConstPtr msg); + + bool loadPCfromMsg(sensor_msgs::PointCloudConstPtr msg); + + bool genPcW(const Matrix4d& Twc); + + double getStamp() const; + + pcl::PointCloud::Ptr &getPPcRgbW(); + +private: + double stamp_; + + pcl_xyzrgb::Ptr p_pc_rgb_c_; + pcl_xyzrgb::Ptr p_pc_rgb_w_; +}; + +typedef std::shared_ptr LaserFramePtr; + + +/** + * 1. resource in: + * 1.1 laser: new laser frame, feed into container + * 1.2 image: new image frame, feed into container + * 1.3 odom: set corresponding image frame (should be the nf_bef + 1 th image in vector) + * Twc, trigger data proc and sliding window + * 2. resource proc: + * 2.1 Interpolate pose for laser frame nf_aft before the image frame + * 2.2 Find RGB value with k frames. X o X O X o X + * 2.3 Add this laser frame into whole point cloud + * 3. resource free (sliding window) + * 3.1 Delete first image frame + * 3.2 Delete the laser frame that got RGBed. + */ +class LaserRGBEstimator +{ +public: + LaserRGBEstimator(); + + void image_cb(sensor_msgs::ImageConstPtr msg); + + void laser_cb(sensor_msgs::PointCloudConstPtr msg); + + void odom_cb(nav_msgs::OdometryConstPtr msg); + + template + RowVector3d estPointColorWithImage(const PointT& p_w, ImageFramePtr pif); + + /** + * [start, end) + * @param plf + * @param start + * @param end + * @return + */ + bool estLaserFrameColor(LaserFramePtr plf, + std::deque::iterator start, + std::deque::iterator end); + + bool slide_window(); + + bool pubPcRGB(); + +private: + void init(); + + bool initSlideWindow(size_t idx_im_pose); + + size_t setImagePose(nav_msgs::OdometryConstPtr msg); + + // sliding windows + std::deque image_sw_; + std::deque laser_sw_; + bool f_sw_init_; + + // result (and fixed) point cloud + pcl_xyzrgb::Ptr whole_pc_rgb_; + pcl_xyzrgb::Ptr new_pc_rgb_; + + // parameters + static const uint8_t nf_bef_, nf_aft_; + camodocal::CameraPtr m_camera_; + Matrix4d Tic_; + int status; + + // ros related + ros::NodeHandle nh_; + ros::Subscriber image_sub_; + ros::Subscriber laser_sub_; + ros::Subscriber odom_sub_; + ros::Publisher pc_rgb_pub_; + ros::Publisher new_pc_rgb_pub_; +}; + + + +#endif //VIO_BLASER_LASER_RGB_ESTIMATOR_H diff --git a/blaser_ros/include/blaser_ros/laser_stripe_detector.h b/blaser_ros/include/blaser_ros/laser_stripe_detector.h new file mode 100644 index 0000000..358f026 --- /dev/null +++ b/blaser_ros/include/blaser_ros/laser_stripe_detector.h @@ -0,0 +1,173 @@ +// +// Created by dcheng on 3/21/20. +// + +#ifndef VIO_BLASER_LASER_STRIPE_DETECTOR_H +#define VIO_BLASER_LASER_STRIPE_DETECTOR_H + +#include +#include +#include +#include + +/* +class LaserExtractParam +{ +public: + LaserExtractParam(); + + LaserExtractParam(int brightness_thresh, + int hue_thresh_1, + int hue_thresh_2); + + void setParams(int brightness_thresh, + int hue_thresh_1, + int hue_thresh_2); + + void genHSVScalars(cv::Scalar& red_mask_1_l, + cv::Scalar& red_mask_1_h, + cv::Scalar& red_mask_2_l, + cv::Scalar& red_mask_2_h) const; + +private: + int brightness_thresh_; + int hue_thresh_1_; + int hue_thresh_2_; +}; + */ + +class LaserStripeDetector +{ +public: + /** + * Constructor function. + * @param env_config_fn yaml file describing laser detection parameters + */ + explicit LaserStripeDetector(const std::string& config_fn); + + /** + * Constructor function that also enables camera undistortion. Need to provide + * camera intrinsics. Only supports pinhole model, no support for camodocal + * @param env_config_fn yaml file describing laser detection parameters + * @param cam_config_fn yaml file describing camera parameters + */ + explicit LaserStripeDetector(const std::string& env_config_fn, + const std::string& cam_config_fn); + + /** + * Function to detect laser points in the given image + * @param im input image + * @param laser_pts output laser pixels + * @return false if no laser pixels are found + */ + bool detectLaserStripe(cv::Mat& im, std::vector &laser_pts); + + /** + * Return the undistorted laser pixels. Make sure that the intrinsics are + * provided before hand, and that the image is not undistorted. + * @param im undistorted image + * @param laser_pts output: undistorted laser pixels + * @return false if no laser pixels are detected + */ + bool detectLaserStripeUndistort(cv::Mat& im, + std::vector &laser_pts); + + /** + * Set the laser extraction param, resulting HSV thresholds: + * red_mask_1_h = [180, 255, 255] + * red_mask_1_l = [hue_thresh_1, 170, brightness_thresh] + * red_mask_2_h = [hue_thresh_2, 255, 255] + * red_mask_2_l = [0, 170, brightness_thresh] + * @param brightness_thresh + * @param hue_thresh_1 + * @param hue_thresh_2 + * @return true if all params are within range + */ + bool setLaserExtractParams(int brightness_thresh, + int hue_thresh_1, + int hue_thresh_2); + +private: + /** + * Find the Center of Mass of a high-valued window on each column of the + * given image. If there does not exist any pixel with a high value (>= 10) + * on a column, then this column is discarded. + * @param im + * @param CoM_pts + * @return false if no points are selected. + */ + bool findCoMColumn(Eigen::MatrixXd &im, std::vector &CoM_pts); + + /** + * Find the Center of Mass of a high-valued window on each row of the + * given image. If there does not exist any pixel with a high value (>= 10) + * on a column, then this column is discarded. + * @param im + * @param CoM_pts + * @return false if no points are selected. + */ + bool findCoMRow(Eigen::MatrixXd &im, std::vector &CoM_pts); + + // functions to load config yaml files + void loadEnvConfig(const std::string& env_config_fn); + void loadCamConfig(const std::string& cam_config_fn); + + void rejectOutliers(const std::vector &pts_in, + std::vector &pts_out); + + /** + * Initialize algorithm parameters that are not pass in through config files + */ + void initParams(); + + /** + * Generate HSV masks for image thresholding. + * @param max_val max value (intensity) of the image + * @param hsv_masks For range covering hue=180/0 (eg. red), indicated by + * hue_min > hue_max, vector size = 4 + * else, vector size = 2 (lower, upper bound) + */ + void generateHSVMasks(const cv::Mat& im_hsv, cv::Mat& hsv_mask) const; + + /** + * Visualize laser stripe detection result using opencv imshow for debug + * @param im_ori original image + * @param hsv_mask + * @param im_v V (value) channel of masked HSV image + * @param laser_pixels detected laser pixel coordinates + */ + void visualize(const cv::Mat &im_ori, const cv::Mat &hsv_mask, + const cv::Mat &im_v, + const std::vector &laser_pixels) const; + + // camera intrinsics + const bool f_intrisics_; + cv::Mat K_; + cv::Mat D_; + + int height_; + int width_; + + // two red threshold, lower and higher bounds + // HSV masks. for range covering hue=180/0 (eg. red), vector size = 2 + // else vector size = 1 + // each element pair has a lower HSV bound (first) and a upper one (second) + //std::vector> hsv_masks_; + //cv::Scalar red_mask_1_l_, red_mask_1_h_, red_mask_2_l_, red_mask_2_h_; + + double hue_min_, hue_max_, sat_min_, val_min_, val_ratio_; + + // region of interest where we try to find laser stripe + cv::Rect laser_ROI_; + + static const int MIN_LASER_PTS = 20; + + // algorithm parameters + cv::Mat mask_dilate_kernel_, mask_close_kernel_; + + // control parameters + bool f_vis_; + bool find_laser_per_column; +}; + +#endif //VIO_BLASER_LASER_STRIPE_DETECTOR_H diff --git a/blaser_ros/include/blaser_ros/resolution_analyser.h b/blaser_ros/include/blaser_ros/resolution_analyser.h new file mode 100644 index 0000000..2d02c25 --- /dev/null +++ b/blaser_ros/include/blaser_ros/resolution_analyser.h @@ -0,0 +1,88 @@ +// +// Created by dcheng on 11/23/20. +// + +#ifndef VIO_BLASER_RESOLUTION_ANALYSER_H +#define VIO_BLASER_RESOLUTION_ANALYSER_H + +#include +#include "camodocal/camera_models/CameraFactory.h" +#include "camodocal/camera_models/CataCamera.h" +#include "camodocal/camera_models/PinholeCamera.h" + +class LaserProjector +{ +public: + LaserProjector(const std::string& config_fn, double theta); + + bool project(double depth, size_t n_pts, std::vector& pts) const; + + double elevation_min_; + double elevation_max_; + +private: + double baseline_; + double theta_; // 0 is vertical + + Eigen::Matrix4d Tcl_; +}; + +class DepthDistribution +{ +public: + DepthDistribution(const std::string& config_fn); + + std::vector> weighted_depths_; // depth, weight + + static const int NUM_DEPTHS = 100; + +private: + void readParams(const std::string& config_fn); + + void genWeightedDepthsUniform(); + void genWeightedDepthsGaussian(); + + enum { + Gaussian, + Uniform + } type; + + double min; + double max; + + // gaussian params + double mean; + double std; +}; + +class ResolutionAnalyser +{ +public: + ResolutionAnalyser(const std::string& config_fn); + + void evalRes(); + + void evalRes(const std::vector& thetas); + + double evalResAtTheta(double theta, + std::vector& depths, std::vector& ress, + std::vector& weights, bool is_vis = false); + + double evalResAtDepth(double depth, const LaserProjector& laser_projector, + bool is_vis = false); + +private: + + + void readParam(const std::string& config_fn); + + camodocal::CameraPtr m_camera_; + DepthDistribution depth_distribution_; + const std::string config_fn_; + static const int NUM_THETAS = 100; + constexpr static const double DEPTH_DELTA = 0.001; + double theta_min_; + double theta_max_; +}; + +#endif //VIO_BLASER_RESOLUTION_ANALYSER_H diff --git a/blaser_ros/include/blaser_ros/third_party/matplotlibcpp.h b/blaser_ros/include/blaser_ros/third_party/matplotlibcpp.h new file mode 100644 index 0000000..214adfb --- /dev/null +++ b/blaser_ros/include/blaser_ros/third_party/matplotlibcpp.h @@ -0,0 +1,2986 @@ +#pragma once + +// Python headers must be included before any system headers, since +// they define _POSIX_C_SOURCE +#include + +#include +#include +#include +#include +#include +#include +#include +#include // requires c++11 support +#include +#include // std::stod + +#ifndef WITHOUT_NUMPY +# define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION +# include + +# ifdef WITH_OPENCV +# include +# endif // WITH_OPENCV + +/* + * A bunch of constants were removed in OpenCV 4 in favour of enum classes, so + * define the ones we need here. + */ +# if CV_MAJOR_VERSION > 3 +# define CV_BGR2RGB cv::COLOR_BGR2RGB +# define CV_BGRA2RGBA cv::COLOR_BGRA2RGBA +# endif +#endif // WITHOUT_NUMPY + +#if PY_MAJOR_VERSION >= 3 +# define PyString_FromString PyUnicode_FromString +# define PyInt_FromLong PyLong_FromLong +# define PyString_FromString PyUnicode_FromString +#endif + + +namespace matplotlibcpp { +namespace detail { + +static std::string s_backend; + +struct _interpreter { + PyObject* s_python_function_arrow; + PyObject *s_python_function_show; + PyObject *s_python_function_close; + PyObject *s_python_function_draw; + PyObject *s_python_function_pause; + PyObject *s_python_function_save; + PyObject *s_python_function_figure; + PyObject *s_python_function_fignum_exists; + PyObject *s_python_function_plot; + PyObject *s_python_function_quiver; + PyObject* s_python_function_contour; + PyObject *s_python_function_semilogx; + PyObject *s_python_function_semilogy; + PyObject *s_python_function_loglog; + PyObject *s_python_function_fill; + PyObject *s_python_function_fill_between; + PyObject *s_python_function_hist; + PyObject *s_python_function_imshow; + PyObject *s_python_function_scatter; + PyObject *s_python_function_boxplot; + PyObject *s_python_function_subplot; + PyObject *s_python_function_subplot2grid; + PyObject *s_python_function_legend; + PyObject *s_python_function_xlim; + PyObject *s_python_function_ion; + PyObject *s_python_function_ginput; + PyObject *s_python_function_ylim; + PyObject *s_python_function_title; + PyObject *s_python_function_axis; + PyObject *s_python_function_axhline; + PyObject *s_python_function_axvline; + PyObject *s_python_function_axvspan; + PyObject *s_python_function_xlabel; + PyObject *s_python_function_ylabel; + PyObject *s_python_function_gca; + PyObject *s_python_function_xticks; + PyObject *s_python_function_yticks; + PyObject* s_python_function_margins; + PyObject *s_python_function_tick_params; + PyObject *s_python_function_grid; + PyObject* s_python_function_cla; + PyObject *s_python_function_clf; + PyObject *s_python_function_errorbar; + PyObject *s_python_function_annotate; + PyObject *s_python_function_tight_layout; + PyObject *s_python_colormap; + PyObject *s_python_empty_tuple; + PyObject *s_python_function_stem; + PyObject *s_python_function_xkcd; + PyObject *s_python_function_text; + PyObject *s_python_function_suptitle; + PyObject *s_python_function_bar; + PyObject *s_python_function_barh; + PyObject *s_python_function_colorbar; + PyObject *s_python_function_subplots_adjust; + PyObject *s_python_function_rcparams; + PyObject *s_python_function_spy; + + /* For now, _interpreter is implemented as a singleton since its currently not possible to have + multiple independent embedded python interpreters without patching the python source code + or starting a separate process for each. [1] + Furthermore, many python objects expect that they are destructed in the same thread as they + were constructed. [2] So for advanced usage, a `kill()` function is provided so that library + users can manually ensure that the interpreter is constructed and destroyed within the + same thread. + + 1: http://bytes.com/topic/python/answers/793370-multiple-independent-python-interpreters-c-c-program + 2: https://github.com/lava/matplotlib-cpp/pull/202#issue-436220256 + */ + + static _interpreter& get() { + return interkeeper(false); + } + + static _interpreter& kill() { + return interkeeper(true); + } + + // Stores the actual singleton object referenced by `get()` and `kill()`. + static _interpreter& interkeeper(bool should_kill) { + static _interpreter ctx; + if (should_kill) + ctx.~_interpreter(); + return ctx; + } + + PyObject* safe_import(PyObject* module, std::string fname) { + PyObject* fn = PyObject_GetAttrString(module, fname.c_str()); + + if (!fn) + throw std::runtime_error(std::string("Couldn't find required function: ") + fname); + + if (!PyFunction_Check(fn)) + throw std::runtime_error(fname + std::string(" is unexpectedly not a PyFunction.")); + + return fn; + } + +private: + +#ifndef WITHOUT_NUMPY +# if PY_MAJOR_VERSION >= 3 + + void *import_numpy() { + import_array(); // initialize C-API + return NULL; + } + +# else + + void import_numpy() { + import_array(); // initialize C-API + } + +# endif +#endif + + _interpreter() { + + // optional but recommended +#if PY_MAJOR_VERSION >= 3 + wchar_t name[] = L"plotting"; +#else + char name[] = "plotting"; +#endif + Py_SetProgramName(name); + Py_Initialize(); + + wchar_t const *dummy_args[] = {L"Python", NULL}; // const is needed because literals must not be modified + wchar_t const **argv = dummy_args; + int argc = sizeof(dummy_args)/sizeof(dummy_args[0])-1; + +#if PY_MAJOR_VERSION >= 3 + PySys_SetArgv(argc, const_cast(argv)); +#else + PySys_SetArgv(argc, (char **)(argv)); +#endif + +#ifndef WITHOUT_NUMPY + import_numpy(); // initialize numpy C-API +#endif + + PyObject* matplotlibname = PyString_FromString("matplotlib"); + PyObject* pyplotname = PyString_FromString("matplotlib.pyplot"); + PyObject* cmname = PyString_FromString("matplotlib.cm"); + PyObject* pylabname = PyString_FromString("pylab"); + if (!pyplotname || !pylabname || !matplotlibname || !cmname) { + throw std::runtime_error("couldnt create string"); + } + + PyObject* matplotlib = PyImport_Import(matplotlibname); + + Py_DECREF(matplotlibname); + if (!matplotlib) { + PyErr_Print(); + throw std::runtime_error("Error loading module matplotlib!"); + } + + // matplotlib.use() must be called *before* pylab, matplotlib.pyplot, + // or matplotlib.backends is imported for the first time + if (!s_backend.empty()) { + PyObject_CallMethod(matplotlib, const_cast("use"), const_cast("s"), s_backend.c_str()); + } + + + + PyObject* pymod = PyImport_Import(pyplotname); + Py_DECREF(pyplotname); + if (!pymod) { throw std::runtime_error("Error loading module matplotlib.pyplot!"); } + + s_python_colormap = PyImport_Import(cmname); + Py_DECREF(cmname); + if (!s_python_colormap) { throw std::runtime_error("Error loading module matplotlib.cm!"); } + + PyObject* pylabmod = PyImport_Import(pylabname); + Py_DECREF(pylabname); + if (!pylabmod) { throw std::runtime_error("Error loading module pylab!"); } + + s_python_function_arrow = safe_import(pymod, "arrow"); + s_python_function_show = safe_import(pymod, "show"); + s_python_function_close = safe_import(pymod, "close"); + s_python_function_draw = safe_import(pymod, "draw"); + s_python_function_pause = safe_import(pymod, "pause"); + s_python_function_figure = safe_import(pymod, "figure"); + s_python_function_fignum_exists = safe_import(pymod, "fignum_exists"); + s_python_function_plot = safe_import(pymod, "plot"); + s_python_function_quiver = safe_import(pymod, "quiver"); + s_python_function_contour = safe_import(pymod, "contour"); + s_python_function_semilogx = safe_import(pymod, "semilogx"); + s_python_function_semilogy = safe_import(pymod, "semilogy"); + s_python_function_loglog = safe_import(pymod, "loglog"); + s_python_function_fill = safe_import(pymod, "fill"); + s_python_function_fill_between = safe_import(pymod, "fill_between"); + s_python_function_hist = safe_import(pymod,"hist"); + s_python_function_scatter = safe_import(pymod,"scatter"); + s_python_function_boxplot = safe_import(pymod,"boxplot"); + s_python_function_subplot = safe_import(pymod, "subplot"); + s_python_function_subplot2grid = safe_import(pymod, "subplot2grid"); + s_python_function_legend = safe_import(pymod, "legend"); + s_python_function_xlim = safe_import(pymod, "xlim"); + s_python_function_ylim = safe_import(pymod, "ylim"); + s_python_function_title = safe_import(pymod, "title"); + s_python_function_axis = safe_import(pymod, "axis"); + s_python_function_axhline = safe_import(pymod, "axhline"); + s_python_function_axvline = safe_import(pymod, "axvline"); + s_python_function_axvspan = safe_import(pymod, "axvspan"); + s_python_function_xlabel = safe_import(pymod, "xlabel"); + s_python_function_ylabel = safe_import(pymod, "ylabel"); + s_python_function_gca = safe_import(pymod, "gca"); + s_python_function_xticks = safe_import(pymod, "xticks"); + s_python_function_yticks = safe_import(pymod, "yticks"); + s_python_function_margins = safe_import(pymod, "margins"); + s_python_function_tick_params = safe_import(pymod, "tick_params"); + s_python_function_grid = safe_import(pymod, "grid"); + s_python_function_ion = safe_import(pymod, "ion"); + s_python_function_ginput = safe_import(pymod, "ginput"); + s_python_function_save = safe_import(pylabmod, "savefig"); + s_python_function_annotate = safe_import(pymod,"annotate"); + s_python_function_cla = safe_import(pymod, "cla"); + s_python_function_clf = safe_import(pymod, "clf"); + s_python_function_errorbar = safe_import(pymod, "errorbar"); + s_python_function_tight_layout = safe_import(pymod, "tight_layout"); + s_python_function_stem = safe_import(pymod, "stem"); + s_python_function_xkcd = safe_import(pymod, "xkcd"); + s_python_function_text = safe_import(pymod, "text"); + s_python_function_suptitle = safe_import(pymod, "suptitle"); + s_python_function_bar = safe_import(pymod,"bar"); + s_python_function_barh = safe_import(pymod, "barh"); + s_python_function_colorbar = PyObject_GetAttrString(pymod, "colorbar"); + s_python_function_subplots_adjust = safe_import(pymod,"subplots_adjust"); + s_python_function_rcparams = PyObject_GetAttrString(pymod, "rcParams"); + s_python_function_spy = PyObject_GetAttrString(pymod, "spy"); +#ifndef WITHOUT_NUMPY + s_python_function_imshow = safe_import(pymod, "imshow"); +#endif + s_python_empty_tuple = PyTuple_New(0); + } + + ~_interpreter() { + Py_Finalize(); + } +}; + +} // end namespace detail + +/// Select the backend +/// +/// **NOTE:** This must be called before the first plot command to have +/// any effect. +/// +/// Mainly useful to select the non-interactive 'Agg' backend when running +/// matplotlibcpp in headless mode, for example on a machine with no display. +/// +/// See also: https://matplotlib.org/2.0.2/api/matplotlib_configuration_api.html#matplotlib.use +inline void backend(const std::string& name) +{ + detail::s_backend = name; +} + +inline bool annotate(std::string annotation, double x, double y) +{ + detail::_interpreter::get(); + + PyObject * xy = PyTuple_New(2); + PyObject * str = PyString_FromString(annotation.c_str()); + + PyTuple_SetItem(xy,0,PyFloat_FromDouble(x)); + PyTuple_SetItem(xy,1,PyFloat_FromDouble(y)); + + PyObject* kwargs = PyDict_New(); + PyDict_SetItemString(kwargs, "xy", xy); + + PyObject* args = PyTuple_New(1); + PyTuple_SetItem(args, 0, str); + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_annotate, args, kwargs); + + Py_DECREF(args); + Py_DECREF(kwargs); + + if(res) Py_DECREF(res); + + return res; +} + +namespace detail { + +#ifndef WITHOUT_NUMPY +// Type selector for numpy array conversion +template struct select_npy_type { const static NPY_TYPES type = NPY_NOTYPE; }; //Default +template <> struct select_npy_type { const static NPY_TYPES type = NPY_DOUBLE; }; +template <> struct select_npy_type { const static NPY_TYPES type = NPY_FLOAT; }; +template <> struct select_npy_type { const static NPY_TYPES type = NPY_BOOL; }; +template <> struct select_npy_type { const static NPY_TYPES type = NPY_INT8; }; +template <> struct select_npy_type { const static NPY_TYPES type = NPY_SHORT; }; +template <> struct select_npy_type { const static NPY_TYPES type = NPY_INT; }; +template <> struct select_npy_type { const static NPY_TYPES type = NPY_INT64; }; +template <> struct select_npy_type { const static NPY_TYPES type = NPY_UINT8; }; +template <> struct select_npy_type { const static NPY_TYPES type = NPY_USHORT; }; +template <> struct select_npy_type { const static NPY_TYPES type = NPY_ULONG; }; +template <> struct select_npy_type { const static NPY_TYPES type = NPY_UINT64; }; + +// Sanity checks; comment them out or change the numpy type below if you're compiling on +// a platform where they don't apply +static_assert(sizeof(long long) == 8); +template <> struct select_npy_type { const static NPY_TYPES type = NPY_INT64; }; +static_assert(sizeof(unsigned long long) == 8); +template <> struct select_npy_type { const static NPY_TYPES type = NPY_UINT64; }; + +template +PyObject* get_array(const std::vector& v) +{ + npy_intp vsize = v.size(); + NPY_TYPES type = select_npy_type::type; + if (type == NPY_NOTYPE) { + size_t memsize = v.size()*sizeof(double); + double* dp = static_cast(::malloc(memsize)); + for (size_t i=0; i(varray), NPY_ARRAY_OWNDATA); + return varray; + } + + PyObject* varray = PyArray_SimpleNewFromData(1, &vsize, type, (void*)(v.data())); + return varray; +} + + +template +PyObject* get_2darray(const std::vector<::std::vector>& v) +{ + if (v.size() < 1) throw std::runtime_error("get_2d_array v too small"); + + npy_intp vsize[2] = {static_cast(v.size()), + static_cast(v[0].size())}; + + PyArrayObject *varray = + (PyArrayObject *)PyArray_SimpleNew(2, vsize, NPY_DOUBLE); + + double *vd_begin = static_cast(PyArray_DATA(varray)); + + for (const ::std::vector &v_row : v) { + if (v_row.size() != static_cast(vsize[1])) + throw std::runtime_error("Missmatched array size"); + std::copy(v_row.begin(), v_row.end(), vd_begin); + vd_begin += vsize[1]; + } + + return reinterpret_cast(varray); +} + +#else // fallback if we don't have numpy: copy every element of the given vector + +template +PyObject* get_array(const std::vector& v) +{ + PyObject* list = PyList_New(v.size()); + for(size_t i = 0; i < v.size(); ++i) { + PyList_SetItem(list, i, PyFloat_FromDouble(v.at(i))); + } + return list; +} + +#endif // WITHOUT_NUMPY + +// sometimes, for labels and such, we need string arrays +inline PyObject * get_array(const std::vector& strings) +{ + PyObject* list = PyList_New(strings.size()); + for (std::size_t i = 0; i < strings.size(); ++i) { + PyList_SetItem(list, i, PyString_FromString(strings[i].c_str())); + } + return list; +} + +// not all matplotlib need 2d arrays, some prefer lists of lists +template +PyObject* get_listlist(const std::vector>& ll) +{ + PyObject* listlist = PyList_New(ll.size()); + for (std::size_t i = 0; i < ll.size(); ++i) { + PyList_SetItem(listlist, i, get_array(ll[i])); + } + return listlist; +} + +} // namespace detail + +/// Plot a line through the given x and y data points.. +/// +/// See: https://matplotlib.org/3.2.1/api/_as_gen/matplotlib.pyplot.plot.html +template +bool plot(const std::vector &x, const std::vector &y, const std::map& keywords) +{ + assert(x.size() == y.size()); + + detail::_interpreter::get(); + + // using numpy arrays + PyObject* xarray = detail::get_array(x); + PyObject* yarray = detail::get_array(y); + + // construct positional args + PyObject* args = PyTuple_New(2); + PyTuple_SetItem(args, 0, xarray); + PyTuple_SetItem(args, 1, yarray); + + // construct keyword args + PyObject* kwargs = PyDict_New(); + for(std::map::const_iterator it = keywords.begin(); it != keywords.end(); ++it) + { + PyDict_SetItemString(kwargs, it->first.c_str(), PyString_FromString(it->second.c_str())); + } + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_plot, args, kwargs); + + Py_DECREF(args); + Py_DECREF(kwargs); + if(res) Py_DECREF(res); + + return res; +} + +// TODO - it should be possible to make this work by implementing +// a non-numpy alternative for `detail::get_2darray()`. +#ifndef WITHOUT_NUMPY +template +void plot_surface(const std::vector<::std::vector> &x, + const std::vector<::std::vector> &y, + const std::vector<::std::vector> &z, + const std::map &keywords = + std::map(), + const long fig_number=0) +{ + detail::_interpreter::get(); + + // We lazily load the modules here the first time this function is called + // because I'm not sure that we can assume "matplotlib installed" implies + // "mpl_toolkits installed" on all platforms, and we don't want to require + // it for people who don't need 3d plots. + static PyObject *mpl_toolkitsmod = nullptr, *axis3dmod = nullptr; + if (!mpl_toolkitsmod) { + detail::_interpreter::get(); + + PyObject* mpl_toolkits = PyString_FromString("mpl_toolkits"); + PyObject* axis3d = PyString_FromString("mpl_toolkits.mplot3d"); + if (!mpl_toolkits || !axis3d) { throw std::runtime_error("couldnt create string"); } + + mpl_toolkitsmod = PyImport_Import(mpl_toolkits); + Py_DECREF(mpl_toolkits); + if (!mpl_toolkitsmod) { throw std::runtime_error("Error loading module mpl_toolkits!"); } + + axis3dmod = PyImport_Import(axis3d); + Py_DECREF(axis3d); + if (!axis3dmod) { throw std::runtime_error("Error loading module mpl_toolkits.mplot3d!"); } + } + + assert(x.size() == y.size()); + assert(y.size() == z.size()); + + // using numpy arrays + PyObject *xarray = detail::get_2darray(x); + PyObject *yarray = detail::get_2darray(y); + PyObject *zarray = detail::get_2darray(z); + + // construct positional args + PyObject *args = PyTuple_New(3); + PyTuple_SetItem(args, 0, xarray); + PyTuple_SetItem(args, 1, yarray); + PyTuple_SetItem(args, 2, zarray); + + // Build up the kw args. + PyObject *kwargs = PyDict_New(); + PyDict_SetItemString(kwargs, "rstride", PyInt_FromLong(1)); + PyDict_SetItemString(kwargs, "cstride", PyInt_FromLong(1)); + + PyObject *python_colormap_coolwarm = PyObject_GetAttrString( + detail::_interpreter::get().s_python_colormap, "coolwarm"); + + PyDict_SetItemString(kwargs, "cmap", python_colormap_coolwarm); + + for (std::map::const_iterator it = keywords.begin(); + it != keywords.end(); ++it) { + if (it->first == "linewidth" || it->first == "alpha") { + PyDict_SetItemString(kwargs, it->first.c_str(), + PyFloat_FromDouble(std::stod(it->second))); + } else { + PyDict_SetItemString(kwargs, it->first.c_str(), + PyString_FromString(it->second.c_str())); + } + } + + PyObject *fig_args = PyTuple_New(1); + PyObject* fig = nullptr; + PyTuple_SetItem(fig_args, 0, PyLong_FromLong(fig_number)); + PyObject *fig_exists = + PyObject_CallObject( + detail::_interpreter::get().s_python_function_fignum_exists, fig_args); + if (!PyObject_IsTrue(fig_exists)) { + fig = PyObject_CallObject(detail::_interpreter::get().s_python_function_figure, + detail::_interpreter::get().s_python_empty_tuple); + } else { + fig = PyObject_CallObject(detail::_interpreter::get().s_python_function_figure, + fig_args); + } + Py_DECREF(fig_exists); + if (!fig) throw std::runtime_error("Call to figure() failed."); + + PyObject *gca_kwargs = PyDict_New(); + PyDict_SetItemString(gca_kwargs, "projection", PyString_FromString("3d")); + + PyObject *gca = PyObject_GetAttrString(fig, "gca"); + if (!gca) throw std::runtime_error("No gca"); + Py_INCREF(gca); + PyObject *axis = PyObject_Call( + gca, detail::_interpreter::get().s_python_empty_tuple, gca_kwargs); + + if (!axis) throw std::runtime_error("No axis"); + Py_INCREF(axis); + + Py_DECREF(gca); + Py_DECREF(gca_kwargs); + + PyObject *plot_surface = PyObject_GetAttrString(axis, "plot_surface"); + if (!plot_surface) throw std::runtime_error("No surface"); + Py_INCREF(plot_surface); + PyObject *res = PyObject_Call(plot_surface, args, kwargs); + if (!res) throw std::runtime_error("failed surface"); + Py_DECREF(plot_surface); + + Py_DECREF(axis); + Py_DECREF(args); + Py_DECREF(kwargs); + if (res) Py_DECREF(res); +} + +template +void contour(const std::vector<::std::vector> &x, + const std::vector<::std::vector> &y, + const std::vector<::std::vector> &z, + const std::map &keywords = {}) +{ + detail::_interpreter::get(); + + // using numpy arrays + PyObject *xarray = detail::get_2darray(x); + PyObject *yarray = detail::get_2darray(y); + PyObject *zarray = detail::get_2darray(z); + + // construct positional args + PyObject *args = PyTuple_New(3); + PyTuple_SetItem(args, 0, xarray); + PyTuple_SetItem(args, 1, yarray); + PyTuple_SetItem(args, 2, zarray); + + // Build up the kw args. + PyObject *kwargs = PyDict_New(); + + PyObject *python_colormap_coolwarm = PyObject_GetAttrString( + detail::_interpreter::get().s_python_colormap, "coolwarm"); + + PyDict_SetItemString(kwargs, "cmap", python_colormap_coolwarm); + + for (std::map::const_iterator it = keywords.begin(); + it != keywords.end(); ++it) { + PyDict_SetItemString(kwargs, it->first.c_str(), + PyString_FromString(it->second.c_str())); + } + + PyObject *res = PyObject_Call(detail::_interpreter::get().s_python_function_contour, args, kwargs); + if (!res) + throw std::runtime_error("failed contour"); + + Py_DECREF(args); + Py_DECREF(kwargs); + if (res) Py_DECREF(res); +} + +template +void spy(const std::vector<::std::vector> &x, + const double markersize = -1, // -1 for default matplotlib size + const std::map &keywords = {}) +{ + detail::_interpreter::get(); + + PyObject *xarray = detail::get_2darray(x); + + PyObject *kwargs = PyDict_New(); + if (markersize != -1) { + PyDict_SetItemString(kwargs, "markersize", PyFloat_FromDouble(markersize)); + } + for (std::map::const_iterator it = keywords.begin(); + it != keywords.end(); ++it) { + PyDict_SetItemString(kwargs, it->first.c_str(), + PyString_FromString(it->second.c_str())); + } + + PyObject *plot_args = PyTuple_New(1); + PyTuple_SetItem(plot_args, 0, xarray); + + PyObject *res = PyObject_Call( + detail::_interpreter::get().s_python_function_spy, plot_args, kwargs); + + Py_DECREF(plot_args); + Py_DECREF(kwargs); + if (res) Py_DECREF(res); +} +#endif // WITHOUT_NUMPY + +template +void plot3(const std::vector &x, + const std::vector &y, + const std::vector &z, + const std::map &keywords = + std::map(), + const long fig_number=0) +{ + detail::_interpreter::get(); + + // Same as with plot_surface: We lazily load the modules here the first time + // this function is called because I'm not sure that we can assume "matplotlib + // installed" implies "mpl_toolkits installed" on all platforms, and we don't + // want to require it for people who don't need 3d plots. + static PyObject *mpl_toolkitsmod = nullptr, *axis3dmod = nullptr; + if (!mpl_toolkitsmod) { + detail::_interpreter::get(); + + PyObject* mpl_toolkits = PyString_FromString("mpl_toolkits"); + PyObject* axis3d = PyString_FromString("mpl_toolkits.mplot3d"); + if (!mpl_toolkits || !axis3d) { throw std::runtime_error("couldnt create string"); } + + mpl_toolkitsmod = PyImport_Import(mpl_toolkits); + Py_DECREF(mpl_toolkits); + if (!mpl_toolkitsmod) { throw std::runtime_error("Error loading module mpl_toolkits!"); } + + axis3dmod = PyImport_Import(axis3d); + Py_DECREF(axis3d); + if (!axis3dmod) { throw std::runtime_error("Error loading module mpl_toolkits.mplot3d!"); } + } + + assert(x.size() == y.size()); + assert(y.size() == z.size()); + + PyObject *xarray = detail::get_array(x); + PyObject *yarray = detail::get_array(y); + PyObject *zarray = detail::get_array(z); + + // construct positional args + PyObject *args = PyTuple_New(3); + PyTuple_SetItem(args, 0, xarray); + PyTuple_SetItem(args, 1, yarray); + PyTuple_SetItem(args, 2, zarray); + + // Build up the kw args. + PyObject *kwargs = PyDict_New(); + + for (std::map::const_iterator it = keywords.begin(); + it != keywords.end(); ++it) { + PyDict_SetItemString(kwargs, it->first.c_str(), + PyString_FromString(it->second.c_str())); + } + + PyObject *fig_args = PyTuple_New(1); + PyObject* fig = nullptr; + PyTuple_SetItem(fig_args, 0, PyLong_FromLong(fig_number)); + PyObject *fig_exists = + PyObject_CallObject(detail::_interpreter::get().s_python_function_fignum_exists, fig_args); + if (!PyObject_IsTrue(fig_exists)) { + fig = PyObject_CallObject(detail::_interpreter::get().s_python_function_figure, + detail::_interpreter::get().s_python_empty_tuple); + } else { + fig = PyObject_CallObject(detail::_interpreter::get().s_python_function_figure, + fig_args); + } + if (!fig) throw std::runtime_error("Call to figure() failed."); + + PyObject *gca_kwargs = PyDict_New(); + PyDict_SetItemString(gca_kwargs, "projection", PyString_FromString("3d")); + + PyObject *gca = PyObject_GetAttrString(fig, "gca"); + if (!gca) throw std::runtime_error("No gca"); + Py_INCREF(gca); + PyObject *axis = PyObject_Call( + gca, detail::_interpreter::get().s_python_empty_tuple, gca_kwargs); + + if (!axis) throw std::runtime_error("No axis"); + Py_INCREF(axis); + + Py_DECREF(gca); + Py_DECREF(gca_kwargs); + + PyObject *plot3 = PyObject_GetAttrString(axis, "plot"); + if (!plot3) throw std::runtime_error("No 3D line plot"); + Py_INCREF(plot3); + PyObject *res = PyObject_Call(plot3, args, kwargs); + if (!res) throw std::runtime_error("Failed 3D line plot"); + Py_DECREF(plot3); + + Py_DECREF(axis); + Py_DECREF(args); + Py_DECREF(kwargs); + if (res) Py_DECREF(res); +} + +template +bool stem(const std::vector &x, const std::vector &y, const std::map& keywords) +{ + assert(x.size() == y.size()); + + detail::_interpreter::get(); + + // using numpy arrays + PyObject* xarray = detail::get_array(x); + PyObject* yarray = detail::get_array(y); + + // construct positional args + PyObject* args = PyTuple_New(2); + PyTuple_SetItem(args, 0, xarray); + PyTuple_SetItem(args, 1, yarray); + + // construct keyword args + PyObject* kwargs = PyDict_New(); + for (std::map::const_iterator it = + keywords.begin(); it != keywords.end(); ++it) { + PyDict_SetItemString(kwargs, it->first.c_str(), + PyString_FromString(it->second.c_str())); + } + + PyObject* res = PyObject_Call( + detail::_interpreter::get().s_python_function_stem, args, kwargs); + + Py_DECREF(args); + Py_DECREF(kwargs); + if (res) + Py_DECREF(res); + + return res; +} + +template< typename Numeric > +bool fill(const std::vector& x, const std::vector& y, const std::map& keywords) +{ + assert(x.size() == y.size()); + + detail::_interpreter::get(); + + // using numpy arrays + PyObject* xarray = detail::get_array(x); + PyObject* yarray = detail::get_array(y); + + // construct positional args + PyObject* args = PyTuple_New(2); + PyTuple_SetItem(args, 0, xarray); + PyTuple_SetItem(args, 1, yarray); + + // construct keyword args + PyObject* kwargs = PyDict_New(); + for (auto it = keywords.begin(); it != keywords.end(); ++it) { + PyDict_SetItemString(kwargs, it->first.c_str(), PyUnicode_FromString(it->second.c_str())); + } + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_fill, args, kwargs); + + Py_DECREF(args); + Py_DECREF(kwargs); + + if (res) Py_DECREF(res); + + return res; +} + +template< typename Numeric > +bool fill_between(const std::vector& x, const std::vector& y1, const std::vector& y2, const std::map& keywords) +{ + assert(x.size() == y1.size()); + assert(x.size() == y2.size()); + + detail::_interpreter::get(); + + // using numpy arrays + PyObject* xarray = detail::get_array(x); + PyObject* y1array = detail::get_array(y1); + PyObject* y2array = detail::get_array(y2); + + // construct positional args + PyObject* args = PyTuple_New(3); + PyTuple_SetItem(args, 0, xarray); + PyTuple_SetItem(args, 1, y1array); + PyTuple_SetItem(args, 2, y2array); + + // construct keyword args + PyObject* kwargs = PyDict_New(); + for(std::map::const_iterator it = keywords.begin(); it != keywords.end(); ++it) { + PyDict_SetItemString(kwargs, it->first.c_str(), PyUnicode_FromString(it->second.c_str())); + } + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_fill_between, args, kwargs); + + Py_DECREF(args); + Py_DECREF(kwargs); + if(res) Py_DECREF(res); + + return res; +} + +template +bool arrow(Numeric x, Numeric y, Numeric end_x, Numeric end_y, const std::string& fc = "r", + const std::string ec = "k", Numeric head_length = 0.25, Numeric head_width = 0.1625) { + PyObject* obj_x = PyFloat_FromDouble(x); + PyObject* obj_y = PyFloat_FromDouble(y); + PyObject* obj_end_x = PyFloat_FromDouble(end_x); + PyObject* obj_end_y = PyFloat_FromDouble(end_y); + + PyObject* kwargs = PyDict_New(); + PyDict_SetItemString(kwargs, "fc", PyString_FromString(fc.c_str())); + PyDict_SetItemString(kwargs, "ec", PyString_FromString(ec.c_str())); + PyDict_SetItemString(kwargs, "head_width", PyFloat_FromDouble(head_width)); + PyDict_SetItemString(kwargs, "head_length", PyFloat_FromDouble(head_length)); + + PyObject* plot_args = PyTuple_New(4); + PyTuple_SetItem(plot_args, 0, obj_x); + PyTuple_SetItem(plot_args, 1, obj_y); + PyTuple_SetItem(plot_args, 2, obj_end_x); + PyTuple_SetItem(plot_args, 3, obj_end_y); + + PyObject* res = + PyObject_Call(detail::_interpreter::get().s_python_function_arrow, plot_args, kwargs); + + Py_DECREF(plot_args); + Py_DECREF(kwargs); + if (res) + Py_DECREF(res); + + return res; +} + +template< typename Numeric> +bool hist(const std::vector& y, long bins=10,std::string color="b", + double alpha=1.0, bool cumulative=false) +{ + detail::_interpreter::get(); + + PyObject* yarray = detail::get_array(y); + + PyObject* kwargs = PyDict_New(); + PyDict_SetItemString(kwargs, "bins", PyLong_FromLong(bins)); + PyDict_SetItemString(kwargs, "color", PyString_FromString(color.c_str())); + PyDict_SetItemString(kwargs, "alpha", PyFloat_FromDouble(alpha)); + PyDict_SetItemString(kwargs, "cumulative", cumulative ? Py_True : Py_False); + + PyObject* plot_args = PyTuple_New(1); + + PyTuple_SetItem(plot_args, 0, yarray); + + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_hist, plot_args, kwargs); + + + Py_DECREF(plot_args); + Py_DECREF(kwargs); + if(res) Py_DECREF(res); + + return res; +} + +#ifndef WITHOUT_NUMPY +namespace detail { + +inline void imshow(void *ptr, const NPY_TYPES type, const int rows, const int columns, const int colors, const std::map &keywords, PyObject** out) +{ + assert(type == NPY_UINT8 || type == NPY_FLOAT); + assert(colors == 1 || colors == 3 || colors == 4); + + detail::_interpreter::get(); + + // construct args + npy_intp dims[3] = { rows, columns, colors }; + PyObject *args = PyTuple_New(1); + PyTuple_SetItem(args, 0, PyArray_SimpleNewFromData(colors == 1 ? 2 : 3, dims, type, ptr)); + + // construct keyword args + PyObject* kwargs = PyDict_New(); + for(std::map::const_iterator it = keywords.begin(); it != keywords.end(); ++it) + { + PyDict_SetItemString(kwargs, it->first.c_str(), PyUnicode_FromString(it->second.c_str())); + } + + PyObject *res = PyObject_Call(detail::_interpreter::get().s_python_function_imshow, args, kwargs); + Py_DECREF(args); + Py_DECREF(kwargs); + if (!res) + throw std::runtime_error("Call to imshow() failed"); + if (out) + *out = res; + else + Py_DECREF(res); +} + +} // namespace detail + +inline void imshow(const unsigned char *ptr, const int rows, const int columns, const int colors, const std::map &keywords = {}, PyObject** out = nullptr) +{ + detail::imshow((void *) ptr, NPY_UINT8, rows, columns, colors, keywords, out); +} + +inline void imshow(const float *ptr, const int rows, const int columns, const int colors, const std::map &keywords = {}, PyObject** out = nullptr) +{ + detail::imshow((void *) ptr, NPY_FLOAT, rows, columns, colors, keywords, out); +} + +#ifdef WITH_OPENCV +void imshow(const cv::Mat &image, const std::map &keywords = {}) +{ + // Convert underlying type of matrix, if needed + cv::Mat image2; + NPY_TYPES npy_type = NPY_UINT8; + switch (image.type() & CV_MAT_DEPTH_MASK) { + case CV_8U: + image2 = image; + break; + case CV_32F: + image2 = image; + npy_type = NPY_FLOAT; + break; + default: + image.convertTo(image2, CV_MAKETYPE(CV_8U, image.channels())); + } + + // If color image, convert from BGR to RGB + switch (image2.channels()) { + case 3: + cv::cvtColor(image2, image2, CV_BGR2RGB); + break; + case 4: + cv::cvtColor(image2, image2, CV_BGRA2RGBA); + } + + detail::imshow(image2.data, npy_type, image2.rows, image2.cols, image2.channels(), keywords); +} +#endif // WITH_OPENCV +#endif // WITHOUT_NUMPY + +template +bool scatter(const std::vector& x, + const std::vector& y, + const double s=1.0, // The marker size in points**2 + const std::map & keywords = {}) +{ + detail::_interpreter::get(); + + assert(x.size() == y.size()); + + PyObject* xarray = detail::get_array(x); + PyObject* yarray = detail::get_array(y); + + PyObject* kwargs = PyDict_New(); + PyDict_SetItemString(kwargs, "s", PyLong_FromLong(s)); + for (const auto& it : keywords) + { + PyDict_SetItemString(kwargs, it.first.c_str(), PyString_FromString(it.second.c_str())); + } + + PyObject* plot_args = PyTuple_New(2); + PyTuple_SetItem(plot_args, 0, xarray); + PyTuple_SetItem(plot_args, 1, yarray); + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_scatter, plot_args, kwargs); + + Py_DECREF(plot_args); + Py_DECREF(kwargs); + if(res) Py_DECREF(res); + + return res; +} + +template + bool scatter_colored(const std::vector& x, + const std::vector& y, + const std::vector& colors, + const double s=1.0, // The marker size in points**2 + const std::map & keywords = {}) + { + detail::_interpreter::get(); + + assert(x.size() == y.size()); + + PyObject* xarray = detail::get_array(x); + PyObject* yarray = detail::get_array(y); + PyObject* colors_array = detail::get_array(colors); + + PyObject* kwargs = PyDict_New(); + PyDict_SetItemString(kwargs, "s", PyLong_FromLong(s)); + PyDict_SetItemString(kwargs, "c", colors_array); + + for (const auto& it : keywords) + { + PyDict_SetItemString(kwargs, it.first.c_str(), PyString_FromString(it.second.c_str())); + } + + PyObject* plot_args = PyTuple_New(2); + PyTuple_SetItem(plot_args, 0, xarray); + PyTuple_SetItem(plot_args, 1, yarray); + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_scatter, plot_args, kwargs); + + Py_DECREF(plot_args); + Py_DECREF(kwargs); + if(res) Py_DECREF(res); + + return res; + } + + +template +bool scatter(const std::vector& x, + const std::vector& y, + const std::vector& z, + const double s=1.0, // The marker size in points**2 + const std::map & keywords = {}, + const long fig_number=0) { + detail::_interpreter::get(); + + // Same as with plot_surface: We lazily load the modules here the first time + // this function is called because I'm not sure that we can assume "matplotlib + // installed" implies "mpl_toolkits installed" on all platforms, and we don't + // want to require it for people who don't need 3d plots. + static PyObject *mpl_toolkitsmod = nullptr, *axis3dmod = nullptr; + if (!mpl_toolkitsmod) { + detail::_interpreter::get(); + + PyObject* mpl_toolkits = PyString_FromString("mpl_toolkits"); + PyObject* axis3d = PyString_FromString("mpl_toolkits.mplot3d"); + if (!mpl_toolkits || !axis3d) { throw std::runtime_error("couldnt create string"); } + + mpl_toolkitsmod = PyImport_Import(mpl_toolkits); + Py_DECREF(mpl_toolkits); + if (!mpl_toolkitsmod) { throw std::runtime_error("Error loading module mpl_toolkits!"); } + + axis3dmod = PyImport_Import(axis3d); + Py_DECREF(axis3d); + if (!axis3dmod) { throw std::runtime_error("Error loading module mpl_toolkits.mplot3d!"); } + } + + assert(x.size() == y.size()); + assert(y.size() == z.size()); + + PyObject *xarray = detail::get_array(x); + PyObject *yarray = detail::get_array(y); + PyObject *zarray = detail::get_array(z); + + // construct positional args + PyObject *args = PyTuple_New(3); + PyTuple_SetItem(args, 0, xarray); + PyTuple_SetItem(args, 1, yarray); + PyTuple_SetItem(args, 2, zarray); + + // Build up the kw args. + PyObject *kwargs = PyDict_New(); + + for (std::map::const_iterator it = keywords.begin(); + it != keywords.end(); ++it) { + PyDict_SetItemString(kwargs, it->first.c_str(), + PyString_FromString(it->second.c_str())); + } + PyObject *fig_args = PyTuple_New(1); + PyObject* fig = nullptr; + PyTuple_SetItem(fig_args, 0, PyLong_FromLong(fig_number)); + PyObject *fig_exists = + PyObject_CallObject(detail::_interpreter::get().s_python_function_fignum_exists, fig_args); + if (!PyObject_IsTrue(fig_exists)) { + fig = PyObject_CallObject(detail::_interpreter::get().s_python_function_figure, + detail::_interpreter::get().s_python_empty_tuple); + } else { + fig = PyObject_CallObject(detail::_interpreter::get().s_python_function_figure, + fig_args); + } + Py_DECREF(fig_exists); + if (!fig) throw std::runtime_error("Call to figure() failed."); + + PyObject *gca_kwargs = PyDict_New(); + PyDict_SetItemString(gca_kwargs, "projection", PyString_FromString("3d")); + + PyObject *gca = PyObject_GetAttrString(fig, "gca"); + if (!gca) throw std::runtime_error("No gca"); + Py_INCREF(gca); + PyObject *axis = PyObject_Call( + gca, detail::_interpreter::get().s_python_empty_tuple, gca_kwargs); + + if (!axis) throw std::runtime_error("No axis"); + Py_INCREF(axis); + + Py_DECREF(gca); + Py_DECREF(gca_kwargs); + + PyObject *plot3 = PyObject_GetAttrString(axis, "scatter"); + if (!plot3) throw std::runtime_error("No 3D line plot"); + Py_INCREF(plot3); + PyObject *res = PyObject_Call(plot3, args, kwargs); + if (!res) throw std::runtime_error("Failed 3D line plot"); + Py_DECREF(plot3); + + Py_DECREF(axis); + Py_DECREF(args); + Py_DECREF(kwargs); + Py_DECREF(fig); + if (res) Py_DECREF(res); + return res; + +} + +template +bool boxplot(const std::vector>& data, + const std::vector& labels = {}, + const std::map & keywords = {}) +{ + detail::_interpreter::get(); + + PyObject* listlist = detail::get_listlist(data); + PyObject* args = PyTuple_New(1); + PyTuple_SetItem(args, 0, listlist); + + PyObject* kwargs = PyDict_New(); + + // kwargs needs the labels, if there are (the correct number of) labels + if (!labels.empty() && labels.size() == data.size()) { + PyDict_SetItemString(kwargs, "labels", detail::get_array(labels)); + } + + // take care of the remaining keywords + for (const auto& it : keywords) + { + PyDict_SetItemString(kwargs, it.first.c_str(), PyString_FromString(it.second.c_str())); + } + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_boxplot, args, kwargs); + + Py_DECREF(args); + Py_DECREF(kwargs); + + if(res) Py_DECREF(res); + + return res; +} + +template +bool boxplot(const std::vector& data, + const std::map & keywords = {}) +{ + detail::_interpreter::get(); + + PyObject* vector = detail::get_array(data); + PyObject* args = PyTuple_New(1); + PyTuple_SetItem(args, 0, vector); + + PyObject* kwargs = PyDict_New(); + for (const auto& it : keywords) + { + PyDict_SetItemString(kwargs, it.first.c_str(), PyString_FromString(it.second.c_str())); + } + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_boxplot, args, kwargs); + + Py_DECREF(args); + Py_DECREF(kwargs); + + if(res) Py_DECREF(res); + + return res; +} + +template +bool bar(const std::vector & x, + const std::vector & y, + std::string ec = "black", + std::string ls = "-", + double lw = 1.0, + const std::map & keywords = {}) +{ + detail::_interpreter::get(); + + PyObject * xarray = detail::get_array(x); + PyObject * yarray = detail::get_array(y); + + PyObject * kwargs = PyDict_New(); + + PyDict_SetItemString(kwargs, "ec", PyString_FromString(ec.c_str())); + PyDict_SetItemString(kwargs, "ls", PyString_FromString(ls.c_str())); + PyDict_SetItemString(kwargs, "lw", PyFloat_FromDouble(lw)); + + for (std::map::const_iterator it = + keywords.begin(); + it != keywords.end(); + ++it) { + PyDict_SetItemString( + kwargs, it->first.c_str(), PyUnicode_FromString(it->second.c_str())); + } + + PyObject * plot_args = PyTuple_New(2); + PyTuple_SetItem(plot_args, 0, xarray); + PyTuple_SetItem(plot_args, 1, yarray); + + PyObject * res = PyObject_Call( + detail::_interpreter::get().s_python_function_bar, plot_args, kwargs); + + Py_DECREF(plot_args); + Py_DECREF(kwargs); + if (res) Py_DECREF(res); + + return res; +} + +template +bool bar(const std::vector & y, + std::string ec = "black", + std::string ls = "-", + double lw = 1.0, + const std::map & keywords = {}) +{ + using T = typename std::remove_reference::type::value_type; + + detail::_interpreter::get(); + + std::vector x; + for (std::size_t i = 0; i < y.size(); i++) { x.push_back(i); } + + return bar(x, y, ec, ls, lw, keywords); +} + + +template +bool barh(const std::vector &x, const std::vector &y, std::string ec = "black", std::string ls = "-", double lw = 1.0, const std::map &keywords = { }) { + PyObject *xarray = detail::get_array(x); + PyObject *yarray = detail::get_array(y); + + PyObject *kwargs = PyDict_New(); + + PyDict_SetItemString(kwargs, "ec", PyString_FromString(ec.c_str())); + PyDict_SetItemString(kwargs, "ls", PyString_FromString(ls.c_str())); + PyDict_SetItemString(kwargs, "lw", PyFloat_FromDouble(lw)); + + for (std::map::const_iterator it = keywords.begin(); it != keywords.end(); ++it) { + PyDict_SetItemString(kwargs, it->first.c_str(), PyUnicode_FromString(it->second.c_str())); + } + + PyObject *plot_args = PyTuple_New(2); + PyTuple_SetItem(plot_args, 0, xarray); + PyTuple_SetItem(plot_args, 1, yarray); + + PyObject *res = PyObject_Call(detail::_interpreter::get().s_python_function_barh, plot_args, kwargs); + + Py_DECREF(plot_args); + Py_DECREF(kwargs); + if (res) Py_DECREF(res); + + return res; +} + + +inline bool subplots_adjust(const std::map& keywords = {}) +{ + detail::_interpreter::get(); + + PyObject* kwargs = PyDict_New(); + for (std::map::const_iterator it = + keywords.begin(); it != keywords.end(); ++it) { + PyDict_SetItemString(kwargs, it->first.c_str(), + PyFloat_FromDouble(it->second)); + } + + + PyObject* plot_args = PyTuple_New(0); + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_subplots_adjust, plot_args, kwargs); + + Py_DECREF(plot_args); + Py_DECREF(kwargs); + if(res) Py_DECREF(res); + + return res; +} + +template< typename Numeric> +bool named_hist(std::string label,const std::vector& y, long bins=10, std::string color="b", double alpha=1.0) +{ + detail::_interpreter::get(); + + PyObject* yarray = detail::get_array(y); + + PyObject* kwargs = PyDict_New(); + PyDict_SetItemString(kwargs, "label", PyString_FromString(label.c_str())); + PyDict_SetItemString(kwargs, "bins", PyLong_FromLong(bins)); + PyDict_SetItemString(kwargs, "color", PyString_FromString(color.c_str())); + PyDict_SetItemString(kwargs, "alpha", PyFloat_FromDouble(alpha)); + + + PyObject* plot_args = PyTuple_New(1); + PyTuple_SetItem(plot_args, 0, yarray); + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_hist, plot_args, kwargs); + + Py_DECREF(plot_args); + Py_DECREF(kwargs); + if(res) Py_DECREF(res); + + return res; +} + +template +bool plot(const std::vector& x, const std::vector& y, const std::string& s = "") +{ + assert(x.size() == y.size()); + + detail::_interpreter::get(); + + PyObject* xarray = detail::get_array(x); + PyObject* yarray = detail::get_array(y); + + PyObject* pystring = PyString_FromString(s.c_str()); + + PyObject* plot_args = PyTuple_New(3); + PyTuple_SetItem(plot_args, 0, xarray); + PyTuple_SetItem(plot_args, 1, yarray); + PyTuple_SetItem(plot_args, 2, pystring); + + PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_plot, plot_args); + + Py_DECREF(plot_args); + if(res) Py_DECREF(res); + + return res; +} + +template +bool contour(const std::vector& x, const std::vector& y, + const std::vector& z, + const std::map& keywords = {}) { + assert(x.size() == y.size() && x.size() == z.size()); + + PyObject* xarray = detail::get_array(x); + PyObject* yarray = detail::get_array(y); + PyObject* zarray = detail::get_array(z); + + PyObject* plot_args = PyTuple_New(3); + PyTuple_SetItem(plot_args, 0, xarray); + PyTuple_SetItem(plot_args, 1, yarray); + PyTuple_SetItem(plot_args, 2, zarray); + + // construct keyword args + PyObject* kwargs = PyDict_New(); + for (std::map::const_iterator it = keywords.begin(); + it != keywords.end(); ++it) { + PyDict_SetItemString(kwargs, it->first.c_str(), PyUnicode_FromString(it->second.c_str())); + } + + PyObject* res = + PyObject_Call(detail::_interpreter::get().s_python_function_contour, plot_args, kwargs); + + Py_DECREF(kwargs); + Py_DECREF(plot_args); + if (res) + Py_DECREF(res); + + return res; +} + +template +bool quiver(const std::vector& x, const std::vector& y, const std::vector& u, const std::vector& w, const std::map& keywords = {}) +{ + assert(x.size() == y.size() && x.size() == u.size() && u.size() == w.size()); + + detail::_interpreter::get(); + + PyObject* xarray = detail::get_array(x); + PyObject* yarray = detail::get_array(y); + PyObject* uarray = detail::get_array(u); + PyObject* warray = detail::get_array(w); + + PyObject* plot_args = PyTuple_New(4); + PyTuple_SetItem(plot_args, 0, xarray); + PyTuple_SetItem(plot_args, 1, yarray); + PyTuple_SetItem(plot_args, 2, uarray); + PyTuple_SetItem(plot_args, 3, warray); + + // construct keyword args + PyObject* kwargs = PyDict_New(); + for(std::map::const_iterator it = keywords.begin(); it != keywords.end(); ++it) + { + PyDict_SetItemString(kwargs, it->first.c_str(), PyUnicode_FromString(it->second.c_str())); + } + + PyObject* res = PyObject_Call( + detail::_interpreter::get().s_python_function_quiver, plot_args, kwargs); + + Py_DECREF(kwargs); + Py_DECREF(plot_args); + if (res) + Py_DECREF(res); + + return res; +} + +template +bool quiver(const std::vector& x, const std::vector& y, const std::vector& z, const std::vector& u, const std::vector& w, const std::vector& v, const std::map& keywords = {}) +{ + //set up 3d axes stuff + static PyObject *mpl_toolkitsmod = nullptr, *axis3dmod = nullptr; + if (!mpl_toolkitsmod) { + detail::_interpreter::get(); + + PyObject* mpl_toolkits = PyString_FromString("mpl_toolkits"); + PyObject* axis3d = PyString_FromString("mpl_toolkits.mplot3d"); + if (!mpl_toolkits || !axis3d) { throw std::runtime_error("couldnt create string"); } + + mpl_toolkitsmod = PyImport_Import(mpl_toolkits); + Py_DECREF(mpl_toolkits); + if (!mpl_toolkitsmod) { throw std::runtime_error("Error loading module mpl_toolkits!"); } + + axis3dmod = PyImport_Import(axis3d); + Py_DECREF(axis3d); + if (!axis3dmod) { throw std::runtime_error("Error loading module mpl_toolkits.mplot3d!"); } + } + + //assert sizes match up + assert(x.size() == y.size() && x.size() == u.size() && u.size() == w.size() && x.size() == z.size() && x.size() == v.size() && u.size() == v.size()); + + //set up parameters + detail::_interpreter::get(); + + PyObject* xarray = detail::get_array(x); + PyObject* yarray = detail::get_array(y); + PyObject* zarray = detail::get_array(z); + PyObject* uarray = detail::get_array(u); + PyObject* warray = detail::get_array(w); + PyObject* varray = detail::get_array(v); + + PyObject* plot_args = PyTuple_New(6); + PyTuple_SetItem(plot_args, 0, xarray); + PyTuple_SetItem(plot_args, 1, yarray); + PyTuple_SetItem(plot_args, 2, zarray); + PyTuple_SetItem(plot_args, 3, uarray); + PyTuple_SetItem(plot_args, 4, warray); + PyTuple_SetItem(plot_args, 5, varray); + + // construct keyword args + PyObject* kwargs = PyDict_New(); + for(std::map::const_iterator it = keywords.begin(); it != keywords.end(); ++it) + { + PyDict_SetItemString(kwargs, it->first.c_str(), PyUnicode_FromString(it->second.c_str())); + } + + //get figure gca to enable 3d projection + PyObject *fig = + PyObject_CallObject(detail::_interpreter::get().s_python_function_figure, + detail::_interpreter::get().s_python_empty_tuple); + if (!fig) throw std::runtime_error("Call to figure() failed."); + + PyObject *gca_kwargs = PyDict_New(); + PyDict_SetItemString(gca_kwargs, "projection", PyString_FromString("3d")); + + PyObject *gca = PyObject_GetAttrString(fig, "gca"); + if (!gca) throw std::runtime_error("No gca"); + Py_INCREF(gca); + PyObject *axis = PyObject_Call( + gca, detail::_interpreter::get().s_python_empty_tuple, gca_kwargs); + + if (!axis) throw std::runtime_error("No axis"); + Py_INCREF(axis); + Py_DECREF(gca); + Py_DECREF(gca_kwargs); + + //plot our boys bravely, plot them strongly, plot them with a wink and clap + PyObject *plot3 = PyObject_GetAttrString(axis, "quiver"); + if (!plot3) throw std::runtime_error("No 3D line plot"); + Py_INCREF(plot3); + PyObject* res = PyObject_Call( + plot3, plot_args, kwargs); + if (!res) throw std::runtime_error("Failed 3D plot"); + Py_DECREF(plot3); + Py_DECREF(axis); + Py_DECREF(kwargs); + Py_DECREF(plot_args); + if (res) + Py_DECREF(res); + + return res; +} + +template +bool stem(const std::vector& x, const std::vector& y, const std::string& s = "") +{ + assert(x.size() == y.size()); + + detail::_interpreter::get(); + + PyObject* xarray = detail::get_array(x); + PyObject* yarray = detail::get_array(y); + + PyObject* pystring = PyString_FromString(s.c_str()); + + PyObject* plot_args = PyTuple_New(3); + PyTuple_SetItem(plot_args, 0, xarray); + PyTuple_SetItem(plot_args, 1, yarray); + PyTuple_SetItem(plot_args, 2, pystring); + + PyObject* res = PyObject_CallObject( + detail::_interpreter::get().s_python_function_stem, plot_args); + + Py_DECREF(plot_args); + if (res) + Py_DECREF(res); + + return res; +} + +template +bool semilogx(const std::vector& x, const std::vector& y, const std::string& s = "") +{ + assert(x.size() == y.size()); + + detail::_interpreter::get(); + + PyObject* xarray = detail::get_array(x); + PyObject* yarray = detail::get_array(y); + + PyObject* pystring = PyString_FromString(s.c_str()); + + PyObject* plot_args = PyTuple_New(3); + PyTuple_SetItem(plot_args, 0, xarray); + PyTuple_SetItem(plot_args, 1, yarray); + PyTuple_SetItem(plot_args, 2, pystring); + + PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_semilogx, plot_args); + + Py_DECREF(plot_args); + if(res) Py_DECREF(res); + + return res; +} + +template +bool semilogy(const std::vector& x, const std::vector& y, const std::string& s = "") +{ + assert(x.size() == y.size()); + + detail::_interpreter::get(); + + PyObject* xarray = detail::get_array(x); + PyObject* yarray = detail::get_array(y); + + PyObject* pystring = PyString_FromString(s.c_str()); + + PyObject* plot_args = PyTuple_New(3); + PyTuple_SetItem(plot_args, 0, xarray); + PyTuple_SetItem(plot_args, 1, yarray); + PyTuple_SetItem(plot_args, 2, pystring); + + PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_semilogy, plot_args); + + Py_DECREF(plot_args); + if(res) Py_DECREF(res); + + return res; +} + +template +bool loglog(const std::vector& x, const std::vector& y, const std::string& s = "") +{ + assert(x.size() == y.size()); + + detail::_interpreter::get(); + + PyObject* xarray = detail::get_array(x); + PyObject* yarray = detail::get_array(y); + + PyObject* pystring = PyString_FromString(s.c_str()); + + PyObject* plot_args = PyTuple_New(3); + PyTuple_SetItem(plot_args, 0, xarray); + PyTuple_SetItem(plot_args, 1, yarray); + PyTuple_SetItem(plot_args, 2, pystring); + + PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_loglog, plot_args); + + Py_DECREF(plot_args); + if(res) Py_DECREF(res); + + return res; +} + +template +bool errorbar(const std::vector &x, const std::vector &y, const std::vector &yerr, const std::map &keywords = {}) +{ + assert(x.size() == y.size()); + + detail::_interpreter::get(); + + PyObject* xarray = detail::get_array(x); + PyObject* yarray = detail::get_array(y); + PyObject* yerrarray = detail::get_array(yerr); + + // construct keyword args + PyObject* kwargs = PyDict_New(); + for(std::map::const_iterator it = keywords.begin(); it != keywords.end(); ++it) + { + PyDict_SetItemString(kwargs, it->first.c_str(), PyString_FromString(it->second.c_str())); + } + + PyDict_SetItemString(kwargs, "yerr", yerrarray); + + PyObject *plot_args = PyTuple_New(2); + PyTuple_SetItem(plot_args, 0, xarray); + PyTuple_SetItem(plot_args, 1, yarray); + + PyObject *res = PyObject_Call(detail::_interpreter::get().s_python_function_errorbar, plot_args, kwargs); + + Py_DECREF(kwargs); + Py_DECREF(plot_args); + + if (res) + Py_DECREF(res); + else + throw std::runtime_error("Call to errorbar() failed."); + + return res; +} + +template +bool named_plot(const std::string& name, const std::vector& y, const std::string& format = "") +{ + detail::_interpreter::get(); + + PyObject* kwargs = PyDict_New(); + PyDict_SetItemString(kwargs, "label", PyString_FromString(name.c_str())); + + PyObject* yarray = detail::get_array(y); + + PyObject* pystring = PyString_FromString(format.c_str()); + + PyObject* plot_args = PyTuple_New(2); + + PyTuple_SetItem(plot_args, 0, yarray); + PyTuple_SetItem(plot_args, 1, pystring); + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_plot, plot_args, kwargs); + + Py_DECREF(kwargs); + Py_DECREF(plot_args); + if (res) Py_DECREF(res); + + return res; +} + +template +bool named_plot(const std::string& name, const std::vector& x, const std::vector& y, const std::string& format = "") +{ + detail::_interpreter::get(); + + PyObject* kwargs = PyDict_New(); + PyDict_SetItemString(kwargs, "label", PyString_FromString(name.c_str())); + + PyObject* xarray = detail::get_array(x); + PyObject* yarray = detail::get_array(y); + + PyObject* pystring = PyString_FromString(format.c_str()); + + PyObject* plot_args = PyTuple_New(3); + PyTuple_SetItem(plot_args, 0, xarray); + PyTuple_SetItem(plot_args, 1, yarray); + PyTuple_SetItem(plot_args, 2, pystring); + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_plot, plot_args, kwargs); + + Py_DECREF(kwargs); + Py_DECREF(plot_args); + if (res) Py_DECREF(res); + + return res; +} + +template +bool named_semilogx(const std::string& name, const std::vector& x, const std::vector& y, const std::string& format = "") +{ + detail::_interpreter::get(); + + PyObject* kwargs = PyDict_New(); + PyDict_SetItemString(kwargs, "label", PyString_FromString(name.c_str())); + + PyObject* xarray = detail::get_array(x); + PyObject* yarray = detail::get_array(y); + + PyObject* pystring = PyString_FromString(format.c_str()); + + PyObject* plot_args = PyTuple_New(3); + PyTuple_SetItem(plot_args, 0, xarray); + PyTuple_SetItem(plot_args, 1, yarray); + PyTuple_SetItem(plot_args, 2, pystring); + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_semilogx, plot_args, kwargs); + + Py_DECREF(kwargs); + Py_DECREF(plot_args); + if (res) Py_DECREF(res); + + return res; +} + +template +bool named_semilogy(const std::string& name, const std::vector& x, const std::vector& y, const std::string& format = "") +{ + detail::_interpreter::get(); + + PyObject* kwargs = PyDict_New(); + PyDict_SetItemString(kwargs, "label", PyString_FromString(name.c_str())); + + PyObject* xarray = detail::get_array(x); + PyObject* yarray = detail::get_array(y); + + PyObject* pystring = PyString_FromString(format.c_str()); + + PyObject* plot_args = PyTuple_New(3); + PyTuple_SetItem(plot_args, 0, xarray); + PyTuple_SetItem(plot_args, 1, yarray); + PyTuple_SetItem(plot_args, 2, pystring); + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_semilogy, plot_args, kwargs); + + Py_DECREF(kwargs); + Py_DECREF(plot_args); + if (res) Py_DECREF(res); + + return res; +} + +template +bool named_loglog(const std::string& name, const std::vector& x, const std::vector& y, const std::string& format = "") +{ + detail::_interpreter::get(); + + PyObject* kwargs = PyDict_New(); + PyDict_SetItemString(kwargs, "label", PyString_FromString(name.c_str())); + + PyObject* xarray = detail::get_array(x); + PyObject* yarray = detail::get_array(y); + + PyObject* pystring = PyString_FromString(format.c_str()); + + PyObject* plot_args = PyTuple_New(3); + PyTuple_SetItem(plot_args, 0, xarray); + PyTuple_SetItem(plot_args, 1, yarray); + PyTuple_SetItem(plot_args, 2, pystring); + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_loglog, plot_args, kwargs); + + Py_DECREF(kwargs); + Py_DECREF(plot_args); + if (res) Py_DECREF(res); + + return res; +} + +template +bool plot(const std::vector& y, const std::string& format = "") +{ + std::vector x(y.size()); + for(size_t i=0; i +bool plot(const std::vector& y, const std::map& keywords) +{ + std::vector x(y.size()); + for(size_t i=0; i +bool stem(const std::vector& y, const std::string& format = "") +{ + std::vector x(y.size()); + for (size_t i = 0; i < x.size(); ++i) x.at(i) = i; + return stem(x, y, format); +} + +template +void text(Numeric x, Numeric y, const std::string& s = "") +{ + detail::_interpreter::get(); + + PyObject* args = PyTuple_New(3); + PyTuple_SetItem(args, 0, PyFloat_FromDouble(x)); + PyTuple_SetItem(args, 1, PyFloat_FromDouble(y)); + PyTuple_SetItem(args, 2, PyString_FromString(s.c_str())); + + PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_text, args); + if(!res) throw std::runtime_error("Call to text() failed."); + + Py_DECREF(args); + Py_DECREF(res); +} + +inline void colorbar(PyObject* mappable = NULL, const std::map& keywords = {}) +{ + if (mappable == NULL) + throw std::runtime_error("Must call colorbar with PyObject* returned from an image, contour, surface, etc."); + + detail::_interpreter::get(); + + PyObject* args = PyTuple_New(1); + PyTuple_SetItem(args, 0, mappable); + + PyObject* kwargs = PyDict_New(); + for(std::map::const_iterator it = keywords.begin(); it != keywords.end(); ++it) + { + PyDict_SetItemString(kwargs, it->first.c_str(), PyFloat_FromDouble(it->second)); + } + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_colorbar, args, kwargs); + if(!res) throw std::runtime_error("Call to colorbar() failed."); + + Py_DECREF(args); + Py_DECREF(kwargs); + Py_DECREF(res); +} + + +inline long figure(long number = -1) +{ + detail::_interpreter::get(); + + PyObject *res; + if (number == -1) + res = PyObject_CallObject(detail::_interpreter::get().s_python_function_figure, detail::_interpreter::get().s_python_empty_tuple); + else { + assert(number > 0); + + // Make sure interpreter is initialised + detail::_interpreter::get(); + + PyObject *args = PyTuple_New(1); + PyTuple_SetItem(args, 0, PyLong_FromLong(number)); + res = PyObject_CallObject(detail::_interpreter::get().s_python_function_figure, args); + Py_DECREF(args); + } + + if(!res) throw std::runtime_error("Call to figure() failed."); + + PyObject* num = PyObject_GetAttrString(res, "number"); + if (!num) throw std::runtime_error("Could not get number attribute of figure object"); + const long figureNumber = PyLong_AsLong(num); + + Py_DECREF(num); + Py_DECREF(res); + + return figureNumber; +} + +inline bool fignum_exists(long number) +{ + detail::_interpreter::get(); + + PyObject *args = PyTuple_New(1); + PyTuple_SetItem(args, 0, PyLong_FromLong(number)); + PyObject *res = PyObject_CallObject(detail::_interpreter::get().s_python_function_fignum_exists, args); + if(!res) throw std::runtime_error("Call to fignum_exists() failed."); + + bool ret = PyObject_IsTrue(res); + Py_DECREF(res); + Py_DECREF(args); + + return ret; +} + +inline void figure_size(size_t w, size_t h) +{ + detail::_interpreter::get(); + + const size_t dpi = 100; + PyObject* size = PyTuple_New(2); + PyTuple_SetItem(size, 0, PyFloat_FromDouble((double)w / dpi)); + PyTuple_SetItem(size, 1, PyFloat_FromDouble((double)h / dpi)); + + PyObject* kwargs = PyDict_New(); + PyDict_SetItemString(kwargs, "figsize", size); + PyDict_SetItemString(kwargs, "dpi", PyLong_FromSize_t(dpi)); + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_figure, + detail::_interpreter::get().s_python_empty_tuple, kwargs); + + Py_DECREF(kwargs); + + if(!res) throw std::runtime_error("Call to figure_size() failed."); + Py_DECREF(res); +} + +inline void legend() +{ + detail::_interpreter::get(); + + PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_legend, detail::_interpreter::get().s_python_empty_tuple); + if(!res) throw std::runtime_error("Call to legend() failed."); + + Py_DECREF(res); +} + +inline void legend(const std::map& keywords) +{ + detail::_interpreter::get(); + + // construct keyword args + PyObject* kwargs = PyDict_New(); + for(std::map::const_iterator it = keywords.begin(); it != keywords.end(); ++it) + { + PyDict_SetItemString(kwargs, it->first.c_str(), PyString_FromString(it->second.c_str())); + } + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_legend, detail::_interpreter::get().s_python_empty_tuple, kwargs); + if(!res) throw std::runtime_error("Call to legend() failed."); + + Py_DECREF(kwargs); + Py_DECREF(res); +} + +template +inline void set_aspect(Numeric ratio) +{ + detail::_interpreter::get(); + + PyObject* args = PyTuple_New(1); + PyTuple_SetItem(args, 0, PyFloat_FromDouble(ratio)); + PyObject* kwargs = PyDict_New(); + + PyObject *ax = + PyObject_CallObject(detail::_interpreter::get().s_python_function_gca, + detail::_interpreter::get().s_python_empty_tuple); + if (!ax) throw std::runtime_error("Call to gca() failed."); + Py_INCREF(ax); + + PyObject *set_aspect = PyObject_GetAttrString(ax, "set_aspect"); + if (!set_aspect) throw std::runtime_error("Attribute set_aspect not found."); + Py_INCREF(set_aspect); + + PyObject *res = PyObject_Call(set_aspect, args, kwargs); + if (!res) throw std::runtime_error("Call to set_aspect() failed."); + Py_DECREF(set_aspect); + + Py_DECREF(ax); + Py_DECREF(args); + Py_DECREF(kwargs); +} + +inline void set_aspect_equal() +{ + // expect ratio == "equal". Leaving error handling to matplotlib. + detail::_interpreter::get(); + + PyObject* args = PyTuple_New(1); + PyTuple_SetItem(args, 0, PyString_FromString("equal")); + PyObject* kwargs = PyDict_New(); + + PyObject *ax = + PyObject_CallObject(detail::_interpreter::get().s_python_function_gca, + detail::_interpreter::get().s_python_empty_tuple); + if (!ax) throw std::runtime_error("Call to gca() failed."); + Py_INCREF(ax); + + PyObject *set_aspect = PyObject_GetAttrString(ax, "set_aspect"); + if (!set_aspect) throw std::runtime_error("Attribute set_aspect not found."); + Py_INCREF(set_aspect); + + PyObject *res = PyObject_Call(set_aspect, args, kwargs); + if (!res) throw std::runtime_error("Call to set_aspect() failed."); + Py_DECREF(set_aspect); + + Py_DECREF(ax); + Py_DECREF(args); + Py_DECREF(kwargs); +} + +template +void ylim(Numeric left, Numeric right) +{ + detail::_interpreter::get(); + + PyObject* list = PyList_New(2); + PyList_SetItem(list, 0, PyFloat_FromDouble(left)); + PyList_SetItem(list, 1, PyFloat_FromDouble(right)); + + PyObject* args = PyTuple_New(1); + PyTuple_SetItem(args, 0, list); + + PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_ylim, args); + if(!res) throw std::runtime_error("Call to ylim() failed."); + + Py_DECREF(args); + Py_DECREF(res); +} + +template +void xlim(Numeric left, Numeric right) +{ + detail::_interpreter::get(); + + PyObject* list = PyList_New(2); + PyList_SetItem(list, 0, PyFloat_FromDouble(left)); + PyList_SetItem(list, 1, PyFloat_FromDouble(right)); + + PyObject* args = PyTuple_New(1); + PyTuple_SetItem(args, 0, list); + + PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_xlim, args); + if(!res) throw std::runtime_error("Call to xlim() failed."); + + Py_DECREF(args); + Py_DECREF(res); +} + + +inline std::array xlim() +{ + PyObject* args = PyTuple_New(0); + PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_xlim, args); + + if(!res) throw std::runtime_error("Call to xlim() failed."); + + Py_DECREF(res); + + PyObject* left = PyTuple_GetItem(res,0); + PyObject* right = PyTuple_GetItem(res,1); + return { PyFloat_AsDouble(left), PyFloat_AsDouble(right) }; +} + + +inline std::array ylim() +{ + PyObject* args = PyTuple_New(0); + PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_ylim, args); + + if(!res) throw std::runtime_error("Call to ylim() failed."); + + Py_DECREF(res); + + PyObject* left = PyTuple_GetItem(res,0); + PyObject* right = PyTuple_GetItem(res,1); + return { PyFloat_AsDouble(left), PyFloat_AsDouble(right) }; +} + +template +inline void xticks(const std::vector &ticks, const std::vector &labels = {}, const std::map& keywords = {}) +{ + assert(labels.size() == 0 || ticks.size() == labels.size()); + + detail::_interpreter::get(); + + // using numpy array + PyObject* ticksarray = detail::get_array(ticks); + + PyObject* args; + if(labels.size() == 0) { + // construct positional args + args = PyTuple_New(1); + PyTuple_SetItem(args, 0, ticksarray); + } else { + // make tuple of tick labels + PyObject* labelstuple = PyTuple_New(labels.size()); + for (size_t i = 0; i < labels.size(); i++) + PyTuple_SetItem(labelstuple, i, PyUnicode_FromString(labels[i].c_str())); + + // construct positional args + args = PyTuple_New(2); + PyTuple_SetItem(args, 0, ticksarray); + PyTuple_SetItem(args, 1, labelstuple); + } + + // construct keyword args + PyObject* kwargs = PyDict_New(); + for(std::map::const_iterator it = keywords.begin(); it != keywords.end(); ++it) + { + PyDict_SetItemString(kwargs, it->first.c_str(), PyString_FromString(it->second.c_str())); + } + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_xticks, args, kwargs); + + Py_DECREF(args); + Py_DECREF(kwargs); + if(!res) throw std::runtime_error("Call to xticks() failed"); + + Py_DECREF(res); +} + +template +inline void xticks(const std::vector &ticks, const std::map& keywords) +{ + xticks(ticks, {}, keywords); +} + +template +inline void yticks(const std::vector &ticks, const std::vector &labels = {}, const std::map& keywords = {}) +{ + assert(labels.size() == 0 || ticks.size() == labels.size()); + + detail::_interpreter::get(); + + // using numpy array + PyObject* ticksarray = detail::get_array(ticks); + + PyObject* args; + if(labels.size() == 0) { + // construct positional args + args = PyTuple_New(1); + PyTuple_SetItem(args, 0, ticksarray); + } else { + // make tuple of tick labels + PyObject* labelstuple = PyTuple_New(labels.size()); + for (size_t i = 0; i < labels.size(); i++) + PyTuple_SetItem(labelstuple, i, PyUnicode_FromString(labels[i].c_str())); + + // construct positional args + args = PyTuple_New(2); + PyTuple_SetItem(args, 0, ticksarray); + PyTuple_SetItem(args, 1, labelstuple); + } + + // construct keyword args + PyObject* kwargs = PyDict_New(); + for(std::map::const_iterator it = keywords.begin(); it != keywords.end(); ++it) + { + PyDict_SetItemString(kwargs, it->first.c_str(), PyString_FromString(it->second.c_str())); + } + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_yticks, args, kwargs); + + Py_DECREF(args); + Py_DECREF(kwargs); + if(!res) throw std::runtime_error("Call to yticks() failed"); + + Py_DECREF(res); +} + +template +inline void yticks(const std::vector &ticks, const std::map& keywords) +{ + yticks(ticks, {}, keywords); +} + +template inline void margins(Numeric margin) +{ + // construct positional args + PyObject* args = PyTuple_New(1); + PyTuple_SetItem(args, 0, PyFloat_FromDouble(margin)); + + PyObject* res = + PyObject_CallObject(detail::_interpreter::get().s_python_function_margins, args); + if (!res) + throw std::runtime_error("Call to margins() failed."); + + Py_DECREF(args); + Py_DECREF(res); +} + +template inline void margins(Numeric margin_x, Numeric margin_y) +{ + // construct positional args + PyObject* args = PyTuple_New(2); + PyTuple_SetItem(args, 0, PyFloat_FromDouble(margin_x)); + PyTuple_SetItem(args, 1, PyFloat_FromDouble(margin_y)); + + PyObject* res = + PyObject_CallObject(detail::_interpreter::get().s_python_function_margins, args); + if (!res) + throw std::runtime_error("Call to margins() failed."); + + Py_DECREF(args); + Py_DECREF(res); +} + + +inline void tick_params(const std::map& keywords, const std::string axis = "both") +{ + detail::_interpreter::get(); + + // construct positional args + PyObject* args; + args = PyTuple_New(1); + PyTuple_SetItem(args, 0, PyString_FromString(axis.c_str())); + + // construct keyword args + PyObject* kwargs = PyDict_New(); + for (std::map::const_iterator it = keywords.begin(); it != keywords.end(); ++it) + { + PyDict_SetItemString(kwargs, it->first.c_str(), PyString_FromString(it->second.c_str())); + } + + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_tick_params, args, kwargs); + + Py_DECREF(args); + Py_DECREF(kwargs); + if (!res) throw std::runtime_error("Call to tick_params() failed"); + + Py_DECREF(res); +} + +inline void subplot(long nrows, long ncols, long plot_number) +{ + detail::_interpreter::get(); + + // construct positional args + PyObject* args = PyTuple_New(3); + PyTuple_SetItem(args, 0, PyFloat_FromDouble(nrows)); + PyTuple_SetItem(args, 1, PyFloat_FromDouble(ncols)); + PyTuple_SetItem(args, 2, PyFloat_FromDouble(plot_number)); + + PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_subplot, args); + if(!res) throw std::runtime_error("Call to subplot() failed."); + + Py_DECREF(args); + Py_DECREF(res); +} + +inline void subplot2grid(long nrows, long ncols, long rowid=0, long colid=0, long rowspan=1, long colspan=1) +{ + detail::_interpreter::get(); + + PyObject* shape = PyTuple_New(2); + PyTuple_SetItem(shape, 0, PyLong_FromLong(nrows)); + PyTuple_SetItem(shape, 1, PyLong_FromLong(ncols)); + + PyObject* loc = PyTuple_New(2); + PyTuple_SetItem(loc, 0, PyLong_FromLong(rowid)); + PyTuple_SetItem(loc, 1, PyLong_FromLong(colid)); + + PyObject* args = PyTuple_New(4); + PyTuple_SetItem(args, 0, shape); + PyTuple_SetItem(args, 1, loc); + PyTuple_SetItem(args, 2, PyLong_FromLong(rowspan)); + PyTuple_SetItem(args, 3, PyLong_FromLong(colspan)); + + PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_subplot2grid, args); + if(!res) throw std::runtime_error("Call to subplot2grid() failed."); + + Py_DECREF(shape); + Py_DECREF(loc); + Py_DECREF(args); + Py_DECREF(res); +} + +inline void title(const std::string &titlestr, const std::map &keywords = {}) +{ + detail::_interpreter::get(); + + PyObject* pytitlestr = PyString_FromString(titlestr.c_str()); + PyObject* args = PyTuple_New(1); + PyTuple_SetItem(args, 0, pytitlestr); + + PyObject* kwargs = PyDict_New(); + for (auto it = keywords.begin(); it != keywords.end(); ++it) { + PyDict_SetItemString(kwargs, it->first.c_str(), PyUnicode_FromString(it->second.c_str())); + } + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_title, args, kwargs); + if(!res) throw std::runtime_error("Call to title() failed."); + + Py_DECREF(args); + Py_DECREF(kwargs); + Py_DECREF(res); +} + +inline void suptitle(const std::string &suptitlestr, const std::map &keywords = {}) +{ + detail::_interpreter::get(); + + PyObject* pysuptitlestr = PyString_FromString(suptitlestr.c_str()); + PyObject* args = PyTuple_New(1); + PyTuple_SetItem(args, 0, pysuptitlestr); + + PyObject* kwargs = PyDict_New(); + for (auto it = keywords.begin(); it != keywords.end(); ++it) { + PyDict_SetItemString(kwargs, it->first.c_str(), PyUnicode_FromString(it->second.c_str())); + } + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_suptitle, args, kwargs); + if(!res) throw std::runtime_error("Call to suptitle() failed."); + + Py_DECREF(args); + Py_DECREF(kwargs); + Py_DECREF(res); +} + +inline void axis(const std::string &axisstr) +{ + detail::_interpreter::get(); + + PyObject* str = PyString_FromString(axisstr.c_str()); + PyObject* args = PyTuple_New(1); + PyTuple_SetItem(args, 0, str); + + PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_axis, args); + if(!res) throw std::runtime_error("Call to title() failed."); + + Py_DECREF(args); + Py_DECREF(res); +} + +inline void axhline(double y, double xmin = 0., double xmax = 1., const std::map& keywords = std::map()) +{ + detail::_interpreter::get(); + + // construct positional args + PyObject* args = PyTuple_New(3); + PyTuple_SetItem(args, 0, PyFloat_FromDouble(y)); + PyTuple_SetItem(args, 1, PyFloat_FromDouble(xmin)); + PyTuple_SetItem(args, 2, PyFloat_FromDouble(xmax)); + + // construct keyword args + PyObject* kwargs = PyDict_New(); + for(std::map::const_iterator it = keywords.begin(); it != keywords.end(); ++it) + { + PyDict_SetItemString(kwargs, it->first.c_str(), PyString_FromString(it->second.c_str())); + } + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_axhline, args, kwargs); + + Py_DECREF(args); + Py_DECREF(kwargs); + + if(res) Py_DECREF(res); +} + +inline void axvline(double x, double ymin = 0., double ymax = 1., const std::map& keywords = std::map()) +{ + detail::_interpreter::get(); + + // construct positional args + PyObject* args = PyTuple_New(3); + PyTuple_SetItem(args, 0, PyFloat_FromDouble(x)); + PyTuple_SetItem(args, 1, PyFloat_FromDouble(ymin)); + PyTuple_SetItem(args, 2, PyFloat_FromDouble(ymax)); + + // construct keyword args + PyObject* kwargs = PyDict_New(); + for(std::map::const_iterator it = keywords.begin(); it != keywords.end(); ++it) + { + PyDict_SetItemString(kwargs, it->first.c_str(), PyString_FromString(it->second.c_str())); + } + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_axvline, args, kwargs); + + Py_DECREF(args); + Py_DECREF(kwargs); + + if(res) Py_DECREF(res); +} + +inline void axvspan(double xmin, double xmax, double ymin = 0., double ymax = 1., const std::map& keywords = std::map()) +{ + // construct positional args + PyObject* args = PyTuple_New(4); + PyTuple_SetItem(args, 0, PyFloat_FromDouble(xmin)); + PyTuple_SetItem(args, 1, PyFloat_FromDouble(xmax)); + PyTuple_SetItem(args, 2, PyFloat_FromDouble(ymin)); + PyTuple_SetItem(args, 3, PyFloat_FromDouble(ymax)); + + // construct keyword args + PyObject* kwargs = PyDict_New(); + for (auto it = keywords.begin(); it != keywords.end(); ++it) { + if (it->first == "linewidth" || it->first == "alpha") { + PyDict_SetItemString(kwargs, it->first.c_str(), + PyFloat_FromDouble(std::stod(it->second))); + } else { + PyDict_SetItemString(kwargs, it->first.c_str(), + PyString_FromString(it->second.c_str())); + } + } + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_axvspan, args, kwargs); + Py_DECREF(args); + Py_DECREF(kwargs); + + if(res) Py_DECREF(res); +} + +inline void xlabel(const std::string &str, const std::map &keywords = {}) +{ + detail::_interpreter::get(); + + PyObject* pystr = PyString_FromString(str.c_str()); + PyObject* args = PyTuple_New(1); + PyTuple_SetItem(args, 0, pystr); + + PyObject* kwargs = PyDict_New(); + for (auto it = keywords.begin(); it != keywords.end(); ++it) { + PyDict_SetItemString(kwargs, it->first.c_str(), PyUnicode_FromString(it->second.c_str())); + } + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_xlabel, args, kwargs); + if(!res) throw std::runtime_error("Call to xlabel() failed."); + + Py_DECREF(args); + Py_DECREF(kwargs); + Py_DECREF(res); +} + +inline void ylabel(const std::string &str, const std::map& keywords = {}) +{ + detail::_interpreter::get(); + + PyObject* pystr = PyString_FromString(str.c_str()); + PyObject* args = PyTuple_New(1); + PyTuple_SetItem(args, 0, pystr); + + PyObject* kwargs = PyDict_New(); + for (auto it = keywords.begin(); it != keywords.end(); ++it) { + PyDict_SetItemString(kwargs, it->first.c_str(), PyUnicode_FromString(it->second.c_str())); + } + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_ylabel, args, kwargs); + if(!res) throw std::runtime_error("Call to ylabel() failed."); + + Py_DECREF(args); + Py_DECREF(kwargs); + Py_DECREF(res); +} + +inline void set_zlabel(const std::string &str, const std::map& keywords = {}) +{ + detail::_interpreter::get(); + + // Same as with plot_surface: We lazily load the modules here the first time + // this function is called because I'm not sure that we can assume "matplotlib + // installed" implies "mpl_toolkits installed" on all platforms, and we don't + // want to require it for people who don't need 3d plots. + static PyObject *mpl_toolkitsmod = nullptr, *axis3dmod = nullptr; + if (!mpl_toolkitsmod) { + PyObject* mpl_toolkits = PyString_FromString("mpl_toolkits"); + PyObject* axis3d = PyString_FromString("mpl_toolkits.mplot3d"); + if (!mpl_toolkits || !axis3d) { throw std::runtime_error("couldnt create string"); } + + mpl_toolkitsmod = PyImport_Import(mpl_toolkits); + Py_DECREF(mpl_toolkits); + if (!mpl_toolkitsmod) { throw std::runtime_error("Error loading module mpl_toolkits!"); } + + axis3dmod = PyImport_Import(axis3d); + Py_DECREF(axis3d); + if (!axis3dmod) { throw std::runtime_error("Error loading module mpl_toolkits.mplot3d!"); } + } + + PyObject* pystr = PyString_FromString(str.c_str()); + PyObject* args = PyTuple_New(1); + PyTuple_SetItem(args, 0, pystr); + + PyObject* kwargs = PyDict_New(); + for (auto it = keywords.begin(); it != keywords.end(); ++it) { + PyDict_SetItemString(kwargs, it->first.c_str(), PyUnicode_FromString(it->second.c_str())); + } + + PyObject *ax = + PyObject_CallObject(detail::_interpreter::get().s_python_function_gca, + detail::_interpreter::get().s_python_empty_tuple); + if (!ax) throw std::runtime_error("Call to gca() failed."); + Py_INCREF(ax); + + PyObject *zlabel = PyObject_GetAttrString(ax, "set_zlabel"); + if (!zlabel) throw std::runtime_error("Attribute set_zlabel not found."); + Py_INCREF(zlabel); + + PyObject *res = PyObject_Call(zlabel, args, kwargs); + if (!res) throw std::runtime_error("Call to set_zlabel() failed."); + Py_DECREF(zlabel); + + Py_DECREF(ax); + Py_DECREF(args); + Py_DECREF(kwargs); + if (res) Py_DECREF(res); +} + +inline void grid(bool flag) +{ + detail::_interpreter::get(); + + PyObject* pyflag = flag ? Py_True : Py_False; + Py_INCREF(pyflag); + + PyObject* args = PyTuple_New(1); + PyTuple_SetItem(args, 0, pyflag); + + PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_grid, args); + if(!res) throw std::runtime_error("Call to grid() failed."); + + Py_DECREF(args); + Py_DECREF(res); +} + +inline void show(const bool block = true) +{ + detail::_interpreter::get(); + + PyObject* res; + if(block) + { + res = PyObject_CallObject( + detail::_interpreter::get().s_python_function_show, + detail::_interpreter::get().s_python_empty_tuple); + } + else + { + PyObject *kwargs = PyDict_New(); + PyDict_SetItemString(kwargs, "block", Py_False); + res = PyObject_Call( detail::_interpreter::get().s_python_function_show, detail::_interpreter::get().s_python_empty_tuple, kwargs); + Py_DECREF(kwargs); + } + + + if (!res) throw std::runtime_error("Call to show() failed."); + + Py_DECREF(res); +} + +inline void close() +{ + detail::_interpreter::get(); + + PyObject* res = PyObject_CallObject( + detail::_interpreter::get().s_python_function_close, + detail::_interpreter::get().s_python_empty_tuple); + + if (!res) throw std::runtime_error("Call to close() failed."); + + Py_DECREF(res); +} + +inline void xkcd() { + detail::_interpreter::get(); + + PyObject* res; + PyObject *kwargs = PyDict_New(); + + res = PyObject_Call(detail::_interpreter::get().s_python_function_xkcd, + detail::_interpreter::get().s_python_empty_tuple, kwargs); + + Py_DECREF(kwargs); + + if (!res) + throw std::runtime_error("Call to show() failed."); + + Py_DECREF(res); +} + +inline void draw() +{ + detail::_interpreter::get(); + + PyObject* res = PyObject_CallObject( + detail::_interpreter::get().s_python_function_draw, + detail::_interpreter::get().s_python_empty_tuple); + + if (!res) throw std::runtime_error("Call to draw() failed."); + + Py_DECREF(res); +} + +template +inline void pause(Numeric interval) +{ + detail::_interpreter::get(); + + PyObject* args = PyTuple_New(1); + PyTuple_SetItem(args, 0, PyFloat_FromDouble(interval)); + + PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_pause, args); + if(!res) throw std::runtime_error("Call to pause() failed."); + + Py_DECREF(args); + Py_DECREF(res); +} + +inline void save(const std::string& filename, const int dpi=0) +{ + detail::_interpreter::get(); + + PyObject* pyfilename = PyString_FromString(filename.c_str()); + + PyObject* args = PyTuple_New(1); + PyTuple_SetItem(args, 0, pyfilename); + + PyObject* kwargs = PyDict_New(); + + if(dpi > 0) + { + PyDict_SetItemString(kwargs, "dpi", PyLong_FromLong(dpi)); + } + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_save, args, kwargs); + if (!res) throw std::runtime_error("Call to save() failed."); + + Py_DECREF(args); + Py_DECREF(kwargs); + Py_DECREF(res); +} + +inline void rcparams(const std::map& keywords = {}) { + detail::_interpreter::get(); + PyObject* args = PyTuple_New(0); + PyObject* kwargs = PyDict_New(); + for (auto it = keywords.begin(); it != keywords.end(); ++it) { + if ("text.usetex" == it->first) + PyDict_SetItemString(kwargs, it->first.c_str(), PyLong_FromLong(std::stoi(it->second.c_str()))); + else PyDict_SetItemString(kwargs, it->first.c_str(), PyString_FromString(it->second.c_str())); + } + + PyObject * update = PyObject_GetAttrString(detail::_interpreter::get().s_python_function_rcparams, "update"); + PyObject * res = PyObject_Call(update, args, kwargs); + if(!res) throw std::runtime_error("Call to rcParams.update() failed."); + Py_DECREF(args); + Py_DECREF(kwargs); + Py_DECREF(update); + Py_DECREF(res); +} + +inline void clf() { + detail::_interpreter::get(); + + PyObject *res = PyObject_CallObject( + detail::_interpreter::get().s_python_function_clf, + detail::_interpreter::get().s_python_empty_tuple); + + if (!res) throw std::runtime_error("Call to clf() failed."); + + Py_DECREF(res); +} + +inline void cla() { + detail::_interpreter::get(); + + PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_cla, + detail::_interpreter::get().s_python_empty_tuple); + + if (!res) + throw std::runtime_error("Call to cla() failed."); + + Py_DECREF(res); +} + +inline void ion() { + detail::_interpreter::get(); + + PyObject *res = PyObject_CallObject( + detail::_interpreter::get().s_python_function_ion, + detail::_interpreter::get().s_python_empty_tuple); + + if (!res) throw std::runtime_error("Call to ion() failed."); + + Py_DECREF(res); +} + +inline std::vector> ginput(const int numClicks = 1, const std::map& keywords = {}) +{ + detail::_interpreter::get(); + + PyObject *args = PyTuple_New(1); + PyTuple_SetItem(args, 0, PyLong_FromLong(numClicks)); + + // construct keyword args + PyObject* kwargs = PyDict_New(); + for(std::map::const_iterator it = keywords.begin(); it != keywords.end(); ++it) + { + PyDict_SetItemString(kwargs, it->first.c_str(), PyUnicode_FromString(it->second.c_str())); + } + + PyObject* res = PyObject_Call( + detail::_interpreter::get().s_python_function_ginput, args, kwargs); + + Py_DECREF(kwargs); + Py_DECREF(args); + if (!res) throw std::runtime_error("Call to ginput() failed."); + + const size_t len = PyList_Size(res); + std::vector> out; + out.reserve(len); + for (size_t i = 0; i < len; i++) { + PyObject *current = PyList_GetItem(res, i); + std::array position; + position[0] = PyFloat_AsDouble(PyTuple_GetItem(current, 0)); + position[1] = PyFloat_AsDouble(PyTuple_GetItem(current, 1)); + out.push_back(position); + } + Py_DECREF(res); + + return out; +} + +// Actually, is there any reason not to call this automatically for every plot? +inline void tight_layout() { + detail::_interpreter::get(); + + PyObject *res = PyObject_CallObject( + detail::_interpreter::get().s_python_function_tight_layout, + detail::_interpreter::get().s_python_empty_tuple); + + if (!res) throw std::runtime_error("Call to tight_layout() failed."); + + Py_DECREF(res); +} + +// Support for variadic plot() and initializer lists: + +namespace detail { + +template +using is_function = typename std::is_function>>::type; + +template +struct is_callable_impl; + +template +struct is_callable_impl +{ + typedef is_function type; +}; // a non-object is callable iff it is a function + +template +struct is_callable_impl +{ + struct Fallback { void operator()(); }; + struct Derived : T, Fallback { }; + + template struct Check; + + template + static std::true_type test( ... ); // use a variadic function to make sure (1) it accepts everything and (2) its always the worst match + + template + static std::false_type test( Check* ); + +public: + typedef decltype(test(nullptr)) type; + typedef decltype(&Fallback::operator()) dtype; + static constexpr bool value = type::value; +}; // an object is callable iff it defines operator() + +template +struct is_callable +{ + // dispatch to is_callable_impl or is_callable_impl depending on whether T is of class type or not + typedef typename is_callable_impl::value, T>::type type; +}; + +template +struct plot_impl { }; + +template<> +struct plot_impl +{ + template + bool operator()(const IterableX& x, const IterableY& y, const std::string& format) + { + detail::_interpreter::get(); + + // 2-phase lookup for distance, begin, end + using std::distance; + using std::begin; + using std::end; + + auto xs = distance(begin(x), end(x)); + auto ys = distance(begin(y), end(y)); + assert(xs == ys && "x and y data must have the same number of elements!"); + + PyObject* xlist = PyList_New(xs); + PyObject* ylist = PyList_New(ys); + PyObject* pystring = PyString_FromString(format.c_str()); + + auto itx = begin(x), ity = begin(y); + for(size_t i = 0; i < xs; ++i) { + PyList_SetItem(xlist, i, PyFloat_FromDouble(*itx++)); + PyList_SetItem(ylist, i, PyFloat_FromDouble(*ity++)); + } + + PyObject* plot_args = PyTuple_New(3); + PyTuple_SetItem(plot_args, 0, xlist); + PyTuple_SetItem(plot_args, 1, ylist); + PyTuple_SetItem(plot_args, 2, pystring); + + PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_plot, plot_args); + + Py_DECREF(plot_args); + if(res) Py_DECREF(res); + + return res; + } +}; + +template<> +struct plot_impl +{ + template + bool operator()(const Iterable& ticks, const Callable& f, const std::string& format) + { + if(begin(ticks) == end(ticks)) return true; + + // We could use additional meta-programming to deduce the correct element type of y, + // but all values have to be convertible to double anyways + std::vector y; + for(auto x : ticks) y.push_back(f(x)); + return plot_impl()(ticks,y,format); + } +}; + +} // end namespace detail + +// recursion stop for the above +template +bool plot() { return true; } + +template +bool plot(const A& a, const B& b, const std::string& format, Args... args) +{ + return detail::plot_impl::type>()(a,b,format) && plot(args...); +} + +/* + * This group of plot() functions is needed to support initializer lists, i.e. calling + * plot( {1,2,3,4} ) + */ +inline bool plot(const std::vector& x, const std::vector& y, const std::string& format = "") { + return plot(x,y,format); +} + +inline bool plot(const std::vector& y, const std::string& format = "") { + return plot(y,format); +} + +inline bool plot(const std::vector& x, const std::vector& y, const std::map& keywords) { + return plot(x,y,keywords); +} + +/* + * This class allows dynamic plots, ie changing the plotted data without clearing and re-plotting + */ +class Plot +{ +public: + // default initialization with plot label, some data and format + template + Plot(const std::string& name, const std::vector& x, const std::vector& y, const std::string& format = "") { + detail::_interpreter::get(); + + assert(x.size() == y.size()); + + PyObject* kwargs = PyDict_New(); + if(name != "") + PyDict_SetItemString(kwargs, "label", PyString_FromString(name.c_str())); + + PyObject* xarray = detail::get_array(x); + PyObject* yarray = detail::get_array(y); + + PyObject* pystring = PyString_FromString(format.c_str()); + + PyObject* plot_args = PyTuple_New(3); + PyTuple_SetItem(plot_args, 0, xarray); + PyTuple_SetItem(plot_args, 1, yarray); + PyTuple_SetItem(plot_args, 2, pystring); + + PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_plot, plot_args, kwargs); + + Py_DECREF(kwargs); + Py_DECREF(plot_args); + + if(res) + { + line= PyList_GetItem(res, 0); + + if(line) + set_data_fct = PyObject_GetAttrString(line,"set_data"); + else + Py_DECREF(line); + Py_DECREF(res); + } + } + + // shorter initialization with name or format only + // basically calls line, = plot([], []) + Plot(const std::string& name = "", const std::string& format = "") + : Plot(name, std::vector(), std::vector(), format) {} + + template + bool update(const std::vector& x, const std::vector& y) { + assert(x.size() == y.size()); + if(set_data_fct) + { + PyObject* xarray = detail::get_array(x); + PyObject* yarray = detail::get_array(y); + + PyObject* plot_args = PyTuple_New(2); + PyTuple_SetItem(plot_args, 0, xarray); + PyTuple_SetItem(plot_args, 1, yarray); + + PyObject* res = PyObject_CallObject(set_data_fct, plot_args); + if (res) Py_DECREF(res); + return res; + } + return false; + } + + // clears the plot but keep it available + bool clear() { + return update(std::vector(), std::vector()); + } + + // definitely remove this line + void remove() { + if(line) + { + auto remove_fct = PyObject_GetAttrString(line,"remove"); + PyObject* args = PyTuple_New(0); + PyObject* res = PyObject_CallObject(remove_fct, args); + if (res) Py_DECREF(res); + } + decref(); + } + + ~Plot() { + decref(); + } +private: + + void decref() { + if(line) + Py_DECREF(line); + if(set_data_fct) + Py_DECREF(set_data_fct); + } + + + PyObject* line = nullptr; + PyObject* set_data_fct = nullptr; +}; + +} // end namespace matplotlibcpp \ No newline at end of file diff --git a/blaser_ros/include/blaser_ros/tic_toc.h b/blaser_ros/include/blaser_ros/tic_toc.h new file mode 100644 index 0000000..8885273 --- /dev/null +++ b/blaser_ros/include/blaser_ros/tic_toc.h @@ -0,0 +1,29 @@ +#pragma once + +#include +#include +#include + +class TicToc +{ + public: + TicToc() + { + tic(); + } + + void tic() + { + start = std::chrono::system_clock::now(); + } + + double toc() + { + end = std::chrono::system_clock::now(); + std::chrono::duration elapsed_seconds = end - start; + return elapsed_seconds.count() * 1000; + } + + private: + std::chrono::time_point start, end; +}; diff --git a/blaser_ros/include/blaser_ros/util/cv_click_handler.h b/blaser_ros/include/blaser_ros/util/cv_click_handler.h new file mode 100644 index 0000000..315f173 --- /dev/null +++ b/blaser_ros/include/blaser_ros/util/cv_click_handler.h @@ -0,0 +1,25 @@ +// +// Created by dcheng on 6/22/20. +// + +#ifndef VIO_BLASER_CV_CLICK_HANDLER_H +#define VIO_BLASER_CV_CLICK_HANDLER_H + +class CVClickHandler +{ +public: + CVClickHandler(); + static void onMouse(int event, int x, int y, int flags, void* param); + static int getX(); + static int getY(); + static void reset(); + +private: + static int x_; + + +private: + static int y_; +}; + +#endif //VIO_BLASER_CV_CLICK_HANDLER_H diff --git a/blaser_ros/include/blaser_ros/util/geometry_util.h b/blaser_ros/include/blaser_ros/util/geometry_util.h new file mode 100644 index 0000000..b25c5ae --- /dev/null +++ b/blaser_ros/include/blaser_ros/util/geometry_util.h @@ -0,0 +1,42 @@ +// +// Created by dcheng on 5/28/20. +// + +#ifndef VIO_BLASER_GEOMETRY_UTIL_H +#define VIO_BLASER_GEOMETRY_UTIL_H + +#include + +void interpRotation(const Matrix3d& R0, const Matrix3d& R1, double ratio, + Matrix3d& R); + +void interpRotation(const Quaterniond& R0, const Quaterniond& R1, double ratio, + Quaterniond& R); + +void interpTrans(const Matrix3d& R0, const Vector3d& t0, + const Matrix3d& R1, const Vector3d& t1, double ratio, + Matrix3d& R, Vector3d& t); + +void interpTrans(const Matrix4d& T0, const Matrix4d& T1, + double ts0, double ts1, double ts, Matrix4d& T); + +void invT(const Matrix4d& T, Matrix4d& T_inv); + +Matrix4d invT(const Matrix4d& T); + +void transformPoint(const Matrix4d& T, const Vector3d& p, Vector3d& p_out); + +Vector3d transformPoint(const Matrix4d& T, const Vector3d& p); + +void T2Rt(const Matrix4d& T, Matrix3d& R, Vector3d& t); + +void Rt2T(const Matrix3d& R, const Vector3d& t, Matrix4d& T); + +void T2PoseMsg(const Matrix4d& T, geometry_msgs::Pose& pose_msg); + +void PoseMsg2T(const geometry_msgs::Pose& pose_msg, Matrix4d& T); + +Matrix4d PoseMsg2T(const geometry_msgs::Pose& pose_msg); + + +#endif //VIO_BLASER_GEOMETRY_UTIL_H diff --git a/blaser_ros/launch/blaser_driver.launch b/blaser_ros/launch/blaser_driver.launch new file mode 100644 index 0000000..6b24694 --- /dev/null +++ b/blaser_ros/launch/blaser_driver.launch @@ -0,0 +1,11 @@ + + + + + + + + + + + diff --git a/blaser_ros/launch/blaser_open_serial.sh b/blaser_ros/launch/blaser_open_serial.sh new file mode 100644 index 0000000..edb7118 --- /dev/null +++ b/blaser_ros/launch/blaser_open_serial.sh @@ -0,0 +1,7 @@ +#!/bin/bash + +# open Blaser serial port +sudo chmod 666 /dev/ttyACM0 + +# exit gracefully by returning a status +exit 0 \ No newline at end of file diff --git a/blaser_ros/launch/bring_up_blaser.launch b/blaser_ros/launch/bring_up_blaser.launch new file mode 100644 index 0000000..48473ef --- /dev/null +++ b/blaser_ros/launch/bring_up_blaser.launch @@ -0,0 +1,13 @@ + + + + + + + + + + + + + \ No newline at end of file diff --git a/blaser_ros/launch/laser_detector_minia1001.launch b/blaser_ros/launch/laser_detector_minia1001.launch new file mode 100644 index 0000000..8e12578 --- /dev/null +++ b/blaser_ros/launch/laser_detector_minia1001.launch @@ -0,0 +1,4 @@ + + + + diff --git a/blaser_ros/launch/laser_detector_vio.launch b/blaser_ros/launch/laser_detector_vio.launch new file mode 100644 index 0000000..d13d5b7 --- /dev/null +++ b/blaser_ros/launch/laser_detector_vio.launch @@ -0,0 +1,4 @@ + + + + diff --git a/blaser_ros/launch/laser_rgb_estimator.launch b/blaser_ros/launch/laser_rgb_estimator.launch new file mode 100644 index 0000000..b5c2031 --- /dev/null +++ b/blaser_ros/launch/laser_rgb_estimator.launch @@ -0,0 +1,9 @@ + + + + + + + + + diff --git a/blaser_ros/launch/trl6_sensor_proc.launch b/blaser_ros/launch/trl6_sensor_proc.launch new file mode 100644 index 0000000..b62e263 --- /dev/null +++ b/blaser_ros/launch/trl6_sensor_proc.launch @@ -0,0 +1,24 @@ + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/blaser_ros/launch/trl6_slam.launch b/blaser_ros/launch/trl6_slam.launch new file mode 100644 index 0000000..ab8d41d --- /dev/null +++ b/blaser_ros/launch/trl6_slam.launch @@ -0,0 +1,10 @@ + + + + + + + + + + diff --git a/blaser_ros/matlab/numerical_diff.m b/blaser_ros/matlab/numerical_diff.m new file mode 100644 index 0000000..043c02d --- /dev/null +++ b/blaser_ros/matlab/numerical_diff.m @@ -0,0 +1,28 @@ +function [] = numerical_diff(dim) +%NUMERICAL_DIFF Summary of this function goes here +% Detailed explanation goes here +axang = [0.6, 0.0, 0.8, 0.5]; +phi = axang(1:3) * axang(4); +p2 = [1; 2; 2.3]; +p1 = [1.6344; 1.7954; 1.3992]; +trans = [.1; .2; .35]; +normal = [0.3; 0.2; 1.0]; +normal = normal / norm(normal); + +[e1, J1] = p2l_so3(phi, trans, p2, p1, normal); +delta = [0 0 0]; +epsilon = 1e-11; +delta(dim) = epsilon; +[e2, J2] = p2l_so3(phi + delta, trans, p2, p1, normal); +disp("numerical diff:") +disp((e2 - e1) / epsilon); +disp("Jacobian:"); +disp(J1(dim)); + +[e3, J3] = p2l_so3(phi, trans + reshape(delta, 3, 1), p2, p1, normal); +disp("trans numerical diff:") +disp((e3 - e1) / epsilon); +disp("normal:"); +disp(-normal(dim)); + +end diff --git a/blaser_ros/matlab/numerical_diff_p2p.m b/blaser_ros/matlab/numerical_diff_p2p.m new file mode 100644 index 0000000..4b67e3e --- /dev/null +++ b/blaser_ros/matlab/numerical_diff_p2p.m @@ -0,0 +1,22 @@ +function [] = numerical_diff_p2p(dim) +%NUMERICAL_DIFF Summary of this function goes here +% Detailed explanation goes here +axang = [0.6, 0.0, 0.8, 0.5]; +phi = axang(1:3) * axang(4); +p2 = [1; 2; 2.3]; +p1 = [1.6344; 1.7954; 1.3992]; +trans = [.1; .2; .35]; +normal = [0.3; 0.2; 1.0]; +normal = normal / norm(normal); + +[e1, J1] = p2p_so3(phi, trans, p2, p1); +delta = [0 0 0]; +epsilon = 1e-11; +delta(dim) = epsilon; +[e2, J2] = p2p_so3(phi + delta, trans, p2, p1); +disp("numerical diff:") +disp((e2 - e1) / epsilon); +disp("Jacobian:"); +disp(J1(:, dim)); + +end diff --git a/blaser_ros/matlab/p2l_so3.m b/blaser_ros/matlab/p2l_so3.m new file mode 100644 index 0000000..c8dd177 --- /dev/null +++ b/blaser_ros/matlab/p2l_so3.m @@ -0,0 +1,9 @@ +function [e, J] = p2l_so3(phi, trans, dst, src, normal) +%P2L_SO3 Summary of this function goes here +% Detailed explanation goes here + axang = [reshape(phi, [1,3]) / norm(phi), norm(phi)]; + R = axang2rotm(axang); + normal = reshape(normal, [1, 3]); + e = normal * (dst - (R * src + trans)); + J = -cross(R * reshape(src, [3,1]) + trans, normal); +end \ No newline at end of file diff --git a/blaser_ros/matlab/p2p_so3.m b/blaser_ros/matlab/p2p_so3.m new file mode 100644 index 0000000..e3c3f8b --- /dev/null +++ b/blaser_ros/matlab/p2p_so3.m @@ -0,0 +1,8 @@ +function [e, J] = p2p_so3(phi, trans, dst, src) +%P2L_SO3 Summary of this function goes here +% Detailed explanation goes here + axang = [reshape(phi, [1,3]) / norm(phi), norm(phi)]; + R = axang2rotm(axang); + e = dst - (R * src + trans); + J = skew_sym(R * reshape(src, [3,1]) + trans); +end \ No newline at end of file diff --git a/blaser_ros/matlab/skew_sym.m b/blaser_ros/matlab/skew_sym.m new file mode 100644 index 0000000..68f329b --- /dev/null +++ b/blaser_ros/matlab/skew_sym.m @@ -0,0 +1,8 @@ +function [X] = skew_sym(x) +%SKEW_SYM Summary of this function goes here +% Detailed explanation goes here +X = [ 0, -x(3), x(2); + x(3), 0, -x(1); + -x(2), x(1), 0]; +end + diff --git a/blaser_ros/package.xml b/blaser_ros/package.xml new file mode 100644 index 0000000..ad76d73 --- /dev/null +++ b/blaser_ros/package.xml @@ -0,0 +1,81 @@ + + + blaser_ros + 0.0.0 + The blaser_ros package + + + + + dcheng + + + + + + TODO + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + catkin + geometry_msgs + pcl_conversions + pcl_ros + roscpp + sensor_msgs + std_msgs + dynamic_reconfigure + + geometry_msgs + pcl_conversions + pcl_ros + roscpp + sensor_msgs + std_msgs + dynamic_reconfigure + + geometry_msgs + pcl_conversions + pcl_ros + roscpp + sensor_msgs + std_msgs + dynamic_reconfigure + + + + + + + diff --git a/blaser_ros/scripts/.ipynb_checkpoints/Untitled-checkpoint.ipynb b/blaser_ros/scripts/.ipynb_checkpoints/Untitled-checkpoint.ipynb new file mode 100644 index 0000000..7fec515 --- /dev/null +++ b/blaser_ros/scripts/.ipynb_checkpoints/Untitled-checkpoint.ipynb @@ -0,0 +1,6 @@ +{ + "cells": [], + "metadata": {}, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/blaser_ros/scripts/.ipynb_checkpoints/Untitled1-checkpoint.ipynb b/blaser_ros/scripts/.ipynb_checkpoints/Untitled1-checkpoint.ipynb new file mode 100644 index 0000000..09c3d25 --- /dev/null +++ b/blaser_ros/scripts/.ipynb_checkpoints/Untitled1-checkpoint.ipynb @@ -0,0 +1,177 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "import cv2\n", + "import numpy as np\n", + "from scipy.spatial.transform import Rotation\n", + "from math import sin, cos, radians, degrees, pi\n", + "np.set_printoptions(suppress=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [], + "source": [ + "def skew(vector):\n", + " return np.array([[0, -vector[2], vector[1]], \n", + " [vector[2], 0, -vector[0]], \n", + " [-vector[1], vector[0], 0]])\n", + "\n", + "def evalRt(R_est, t_est, euler, t):\n", + " euler_est = Rotation.from_matrix(R_est).as_euler('xyz')\n", + " t_est = t_est.reshape(3)\n", + " for i in range(3):\n", + " if euler_est[i] > pi / 2:\n", + " euler_est[i] -= pi\n", + " euler_err = np.linalg.norm(np.minimum(np.abs(euler_est - euler), np.abs(euler - euler_est))) / np.linalg.norm(euler)\n", + " t_est = t_est / np.linalg.norm(t_est) * np.linalg.norm(t) # rescale\n", + " t_err = np.linalg.norm(np.abs(t - t_est)) / np.linalg.norm(t)\n", + " print(\"t ground truth: \", t)\n", + " print(\"t est: \",t_est)\n", + " print(\"euelr gt: \", euler)\n", + " print(\"euler est: \", euler_est)\n", + " print(\"t err: \", t_err)\n", + " print(\"euler err: \", euler_err)\n", + " print(\"\\n\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Generate 3d points and 2d pixels" + ] + }, + { + "cell_type": "code", + "execution_count": 93, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ 0.00017365 0. -0.00001519]\n" + ] + } + ], + "source": [ + "# initialize transformation\n", + "baseline = 0.03162277 # distance from joint to camera optical center, 1cm\n", + "theta = radians(10)\n", + "euler = np.array([0, theta, 0]) # joint rotation angle in degrees\n", + "R = Rotation.from_euler('xyz', euler, degrees=False)\n", + "t = np.array([baseline * sin(theta), 0, -(baseline - baseline * cos(theta))])\n", + "T = np.zeros((4, 4))\n", + "T[:3, :3] = R.as_matrix()\n", + "T[3,3] = 1.\n", + "T[:3, 3] = t\n", + "print(t)\n", + "\n", + "# set initial points (10), x [-0.2, 0.2], y in [-0.15, .15], z in [0.1, .3]\n", + "N_PTS = 50\n", + "pt_w = np.random.random((N_PTS, 3))\n", + "pt_w[:, 0] = pt_w[:, 0] * 0.4 - 0.2\n", + "pt_w[:, 1] = pt_w[:, 1] * 0.3 - 0.15\n", + "pt_w[:, 2] = pt_w[:, 2] * 0.2 + 0.1\n", + "\n", + "pt_w_h = np.ones((N_PTS, 4)) # homogeneous coordinates\n", + "pt_w_h[:, :3] = pt_w\n", + "\n", + "# get pixels in 2d with noise and integer round up error\n", + "K = np.array([[339.4, 0, 321.9], [0, 339.7, 226.2], [0, 0, 1.]])\n", + "puv1 = (np.matmul(K, pt_w_h.T[:3, :]) / np.tile(np.matmul(K, pt_w_h.T[:3, :])[2,:], (3,1)))[:2, :].T\n", + "puv2 = (np.matmul(K, np.matmul(T, pt_w_h.T)[:3, :]) / np.tile(np.matmul(K, np.matmul(T, pt_w_h.T)[:3, :])[2, :], (3,1)))[:2,:].T\n", + "puv1_ni = np.int32(np.rint(puv1 + np.random.normal(scale=3, size=(N_PTS, 2))))\n", + "puv2_ni = np.int32(np.rint(puv2 + np.random.normal(scale=3, size=(N_PTS, 2))))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Estimate fundamental, solve for R t, and eval error rate" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "t ground truth: [ 0.00017365 0. -0.00001519]\n", + "t est: [ 0.00011085 -0.00005606 0.00012229]\n", + "euelr gt: [0. 0.17453293 0. ]\n", + "euler est: [ 0.00236088 0.16613908 -0.01244973]\n", + "t err: 0.9248080861440643\n", + "euler err: 0.08708698848396756\n", + "\n", + "\n", + "t ground truth: [ 0.00017365 0. -0.00001519]\n", + "t est: [-0.00011085 0.00005606 -0.00012229]\n", + "euelr gt: [0. 0.17453293 0. ]\n", + "euler est: [-1.27486603 -1.09307996 -2.37478036]\n", + "t err: 1.7733386602120174\n", + "euler err: 17.065783856553942\n", + "\n", + "\n" + ] + } + ], + "source": [ + "F, mask = cv2.findFundamentalMat(puv1_ni, puv2_ni, cv2.FM_8POINT)\n", + "E = K.T.dot(F).dot(K)\n", + "R1, R2, t_est = cv2.decomposeEssentialMat(E)\n", + "evalRt(R1, t_est, euler, t)\n", + "evalRt(R2, -t_est, euler, t)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "euler_err = np.array([[0.045597, 0.060830479],\n", + " [0.049696935, 0.020570586, 0.044756, 0.0260176, 0.0147433], \n", + " [0.073563, 0.0446892, 0.03898206, 0.037205022, 0.02512616],\n", + " [0.0280946, 0.04086644, 0.11912304, 0.054875145, 0.0382422190]])\n", + "t_err = np.array([[1.062793, 0.661449],\n", + " [0.864721, 0.259404678, 1.760131, 0.8736392, 1.265848], \n", + " [0.15310397, 0.0980089, 0.15720568, 0.26181809, 0.15266775],\n", + " [0.00240634, 0.018018, 0.0529681, 0.0141170, 0.00673846]])" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.9" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/blaser_ros/scripts/.ipynb_checkpoints/laser_calib_test-checkpoint.ipynb b/blaser_ros/scripts/.ipynb_checkpoints/laser_calib_test-checkpoint.ipynb new file mode 100644 index 0000000..2fd6442 --- /dev/null +++ b/blaser_ros/scripts/.ipynb_checkpoints/laser_calib_test-checkpoint.ipynb @@ -0,0 +1,6 @@ +{ + "cells": [], + "metadata": {}, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/blaser_ros/scripts/.ipynb_checkpoints/vis_laser_calib_result-checkpoint.ipynb b/blaser_ros/scripts/.ipynb_checkpoints/vis_laser_calib_result-checkpoint.ipynb new file mode 100644 index 0000000..abc2e8b --- /dev/null +++ b/blaser_ros/scripts/.ipynb_checkpoints/vis_laser_calib_result-checkpoint.ipynb @@ -0,0 +1,911 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "from matplotlib import pyplot as plt\n", + "import math\n", + "%matplotlib notebook\n" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "# read plane parameters and laser points\n", + "result_file = open('../calib_result.txt')\n", + "raw_data = result_file.readlines()\n", + "plane_params = np.fromstring(raw_data[1].strip(), dtype=float, sep=',')\n", + "pts = np.zeros((len(raw_data) - 3, 3))\n", + "for i in range(len(raw_data) - 3):\n", + " pts[i] = np.fromstring(raw_data[i + 3].strip(), dtype=float, sep=',')\n" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "# generate plane\n", + "min_x = np.min(pts[:, 0])\n", + "max_x = np.max(pts[:, 0])\n", + "min_y = np.min(pts[:, 1])\n", + "max_y = np.max(pts[:, 1])\n", + "min_z = np.min(pts[:, 2])\n", + "max_z = np.max(pts[:, 2])\n", + "pl_xx, pl_yy = np.meshgrid(np.linspace(min_x - 0.1, max_x + 0.1),\n", + " np.linspace(min_y - 0.1, np.max(max_y + 0.1))\n", + "pl_z = (-plane_params[0] * pl_xx - plane_params[1] * pl_yy - plane_params[3]) / plane_params[2]" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "application/javascript": [ + "/* Put everything inside the global mpl namespace */\n", + "window.mpl = {};\n", + "\n", + "\n", + "mpl.get_websocket_type = function() {\n", + " if (typeof(WebSocket) !== 'undefined') {\n", + " return WebSocket;\n", + " } else if (typeof(MozWebSocket) !== 'undefined') {\n", + " return MozWebSocket;\n", + " } else {\n", + " alert('Your browser does not have WebSocket support. ' +\n", + " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", + " 'Firefox 4 and 5 are also supported but you ' +\n", + " 'have to enable WebSockets in about:config.');\n", + " };\n", + "}\n", + "\n", + "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", + " this.id = figure_id;\n", + "\n", + " this.ws = websocket;\n", + "\n", + " this.supports_binary = (this.ws.binaryType != undefined);\n", + "\n", + " if (!this.supports_binary) {\n", + " var warnings = document.getElementById(\"mpl-warnings\");\n", + " if (warnings) {\n", + " warnings.style.display = 'block';\n", + " warnings.textContent = (\n", + " \"This browser does not support binary websocket messages. \" +\n", + " \"Performance may be slow.\");\n", + " }\n", + " }\n", + "\n", + " this.imageObj = new Image();\n", + "\n", + " this.context = undefined;\n", + " this.message = undefined;\n", + " this.canvas = undefined;\n", + " this.rubberband_canvas = undefined;\n", + " this.rubberband_context = undefined;\n", + " this.format_dropdown = undefined;\n", + "\n", + " this.image_mode = 'full';\n", + "\n", + " this.root = $('
');\n", + " this._root_extra_style(this.root)\n", + " this.root.attr('style', 'display: inline-block');\n", + "\n", + " $(parent_element).append(this.root);\n", + "\n", + " this._init_header(this);\n", + " this._init_canvas(this);\n", + " this._init_toolbar(this);\n", + "\n", + " var fig = this;\n", + "\n", + " this.waiting = false;\n", + "\n", + " this.ws.onopen = function () {\n", + " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", + " fig.send_message(\"send_image_mode\", {});\n", + " if (mpl.ratio != 1) {\n", + " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", + " }\n", + " fig.send_message(\"refresh\", {});\n", + " }\n", + "\n", + " this.imageObj.onload = function() {\n", + " if (fig.image_mode == 'full') {\n", + " // Full images could contain transparency (where diff images\n", + " // almost always do), so we need to clear the canvas so that\n", + " // there is no ghosting.\n", + " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", + " }\n", + " fig.context.drawImage(fig.imageObj, 0, 0);\n", + " };\n", + "\n", + " this.imageObj.onunload = function() {\n", + " fig.ws.close();\n", + " }\n", + "\n", + " this.ws.onmessage = this._make_on_message_function(this);\n", + "\n", + " this.ondownload = ondownload;\n", + "}\n", + "\n", + "mpl.figure.prototype._init_header = function() {\n", + " var titlebar = $(\n", + " '
');\n", + " var titletext = $(\n", + " '
');\n", + " titlebar.append(titletext)\n", + " this.root.append(titlebar);\n", + " this.header = titletext[0];\n", + "}\n", + "\n", + "\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "\n", + "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "mpl.figure.prototype._init_canvas = function() {\n", + " var fig = this;\n", + "\n", + " var canvas_div = $('
');\n", + "\n", + " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n", + "\n", + " function canvas_keyboard_event(event) {\n", + " return fig.key_event(event, event['data']);\n", + " }\n", + "\n", + " canvas_div.keydown('key_press', canvas_keyboard_event);\n", + " canvas_div.keyup('key_release', canvas_keyboard_event);\n", + " this.canvas_div = canvas_div\n", + " this._canvas_extra_style(canvas_div)\n", + " this.root.append(canvas_div);\n", + "\n", + " var canvas = $('');\n", + " canvas.addClass('mpl-canvas');\n", + " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n", + "\n", + " this.canvas = canvas[0];\n", + " this.context = canvas[0].getContext(\"2d\");\n", + "\n", + " var backingStore = this.context.backingStorePixelRatio ||\n", + "\tthis.context.webkitBackingStorePixelRatio ||\n", + "\tthis.context.mozBackingStorePixelRatio ||\n", + "\tthis.context.msBackingStorePixelRatio ||\n", + "\tthis.context.oBackingStorePixelRatio ||\n", + "\tthis.context.backingStorePixelRatio || 1;\n", + "\n", + " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", + " var rubberband = $('');\n", + " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", + "\n", + " var pass_mouse_events = true;\n", + "\n", + " canvas_div.resizable({\n", + " start: function(event, ui) {\n", + " pass_mouse_events = false;\n", + " },\n", + " resize: function(event, ui) {\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " stop: function(event, ui) {\n", + " pass_mouse_events = true;\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " });\n", + "\n", + " function mouse_event_fn(event) {\n", + " if (pass_mouse_events)\n", + " return fig.mouse_event(event, event['data']);\n", + " }\n", + "\n", + " rubberband.mousedown('button_press', mouse_event_fn);\n", + " rubberband.mouseup('button_release', mouse_event_fn);\n", + " // Throttle sequential mouse events to 1 every 20ms.\n", + " rubberband.mousemove('motion_notify', mouse_event_fn);\n", + "\n", + " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", + " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", + "\n", + " canvas_div.on(\"wheel\", function (event) {\n", + " event = event.originalEvent;\n", + " event['data'] = 'scroll'\n", + " if (event.deltaY < 0) {\n", + " event.step = 1;\n", + " } else {\n", + " event.step = -1;\n", + " }\n", + " mouse_event_fn(event);\n", + " });\n", + "\n", + " canvas_div.append(canvas);\n", + " canvas_div.append(rubberband);\n", + "\n", + " this.rubberband = rubberband;\n", + " this.rubberband_canvas = rubberband[0];\n", + " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", + " this.rubberband_context.strokeStyle = \"#000000\";\n", + "\n", + " this._resize_canvas = function(width, height) {\n", + " // Keep the size of the canvas, canvas container, and rubber band\n", + " // canvas in synch.\n", + " canvas_div.css('width', width)\n", + " canvas_div.css('height', height)\n", + "\n", + " canvas.attr('width', width * mpl.ratio);\n", + " canvas.attr('height', height * mpl.ratio);\n", + " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", + "\n", + " rubberband.attr('width', width);\n", + " rubberband.attr('height', height);\n", + " }\n", + "\n", + " // Set the figure to an initial 600x600px, this will subsequently be updated\n", + " // upon first draw.\n", + " this._resize_canvas(600, 600);\n", + "\n", + " // Disable right mouse context menu.\n", + " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", + " return false;\n", + " });\n", + "\n", + " function set_focus () {\n", + " canvas.focus();\n", + " canvas_div.focus();\n", + " }\n", + "\n", + " window.setTimeout(set_focus, 100);\n", + "}\n", + "\n", + "mpl.figure.prototype._init_toolbar = function() {\n", + " var fig = this;\n", + "\n", + " var nav_element = $('
');\n", + " nav_element.attr('style', 'width: 100%');\n", + " this.root.append(nav_element);\n", + "\n", + " // Define a callback function for later on.\n", + " function toolbar_event(event) {\n", + " return fig.toolbar_button_onclick(event['data']);\n", + " }\n", + " function toolbar_mouse_event(event) {\n", + " return fig.toolbar_button_onmouseover(event['data']);\n", + " }\n", + "\n", + " for(var toolbar_ind in mpl.toolbar_items) {\n", + " var name = mpl.toolbar_items[toolbar_ind][0];\n", + " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", + " var image = mpl.toolbar_items[toolbar_ind][2];\n", + " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", + "\n", + " if (!name) {\n", + " // put a spacer in here.\n", + " continue;\n", + " }\n", + " var button = $('');\n", + " button.click(method_name, toolbar_event);\n", + " button.mouseover(tooltip, toolbar_mouse_event);\n", + " nav_element.append(button);\n", + " }\n", + "\n", + " // Add the status bar.\n", + " var status_bar = $('');\n", + " nav_element.append(status_bar);\n", + " this.message = status_bar[0];\n", + "\n", + " // Add the close button to the window.\n", + " var buttongrp = $('
');\n", + " var button = $('');\n", + " button.click(function (evt) { fig.handle_close(fig, {}); } );\n", + " button.mouseover('Stop Interaction', toolbar_mouse_event);\n", + " buttongrp.append(button);\n", + " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n", + " titlebar.prepend(buttongrp);\n", + "}\n", + "\n", + "mpl.figure.prototype._root_extra_style = function(el){\n", + " var fig = this\n", + " el.on(\"remove\", function(){\n", + "\tfig.close_ws(fig, {});\n", + " });\n", + "}\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function(el){\n", + " // this is important to make the div 'focusable\n", + " el.attr('tabindex', 0)\n", + " // reach out to IPython and tell the keyboard manager to turn it's self\n", + " // off when our div gets focus\n", + "\n", + " // location in version 3\n", + " if (IPython.notebook.keyboard_manager) {\n", + " IPython.notebook.keyboard_manager.register_events(el);\n", + " }\n", + " else {\n", + " // location in version 2\n", + " IPython.keyboard_manager.register_events(el);\n", + " }\n", + "\n", + "}\n", + "\n", + "mpl.figure.prototype._key_event_extra = function(event, name) {\n", + " var manager = IPython.notebook.keyboard_manager;\n", + " if (!manager)\n", + " manager = IPython.keyboard_manager;\n", + "\n", + " // Check for shift+enter\n", + " if (event.shiftKey && event.which == 13) {\n", + " this.canvas_div.blur();\n", + " // select the cell after this one\n", + " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", + " IPython.notebook.select(index + 1);\n", + " }\n", + "}\n", + "\n", + "mpl.figure.prototype.handle_save = function(fig, msg) {\n", + " fig.ondownload(fig, null);\n", + "}\n", + "\n", + "\n", + "mpl.find_output_cell = function(html_output) {\n", + " // Return the cell and output element which can be found *uniquely* in the notebook.\n", + " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", + " // IPython event is triggered only after the cells have been serialised, which for\n", + " // our purposes (turning an active figure into a static one), is too late.\n", + " var cells = IPython.notebook.get_cells();\n", + " var ncells = cells.length;\n", + " for (var i=0; i= 3 moved mimebundle to data attribute of output\n", + " data = data.data;\n", + " }\n", + " if (data['text/html'] == html_output) {\n", + " return [cell, data, j];\n", + " }\n", + " }\n", + " }\n", + " }\n", + "}\n", + "\n", + "// Register the function which deals with the matplotlib target/channel.\n", + "// The kernel may be null if the page has been refreshed.\n", + "if (IPython.notebook.kernel != null) {\n", + " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n", + "}\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "euler_err = np.array([[0.049696935, 0.020570586, 0.044756, 0.0260176, 0.0147433], \n", + " [0.046620757, 0.101748, 0.0957834, 0.0514320, 0.079585],\n", + " [0.073563, 0.0446892, 0.03898206, 0.037205022, 0.02512616],\n", + " [0.047176, 0.025889, 0.0115295, 0.0872496, 0.039396811],\n", + " [0.0280946, 0.04086644, 0.11912304, 0.054875145, 0.0382422190]])\n", + "t_err = np.array([[0.864721, 0.259404678, 1.760131, 0.8736392, 1.265848], \n", + " [0.3701675, 1.0649895, 0.5555488, 0.276301, 0.86642252],\n", + " [0.15310397, 0.0980089, 0.15720568, 0.26181809, 0.15266775],\n", + " [0.04077893, 0.008541906305, 0.065378099, 0.08126958, 0.015522921],\n", + " [0.00240634, 0.018018, 0.0529681, 0.0141170, 0.00673846]])\n", + "euler_err_avr = np.mean(euler_err, axis=1)\n", + "t_err_avr = np.mean(t_err, axis=1)\n", + "baselines = np.array([0.01, 0.03162277, 0.1, 0.3162277, 1.])\n", + "plt.plot(baselines*100, euler_err_avr * 100, label='angular error')\n", + "plt.plot(baselines*100, t_err_avr * 100, label='translational error')\n", + "plt.legend()\n", + "plt.ylabel(\"error rate %\")\n", + "plt.xlabel(\"translational motion (cm)\")\n", + "plt.xscale(\"log\")\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.9" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/blaser_ros/scripts/im_hsv_shower.py b/blaser_ros/scripts/im_hsv_shower.py new file mode 100644 index 0000000..3c5590b --- /dev/null +++ b/blaser_ros/scripts/im_hsv_shower.py @@ -0,0 +1,17 @@ +#!/usr/bin/env python3 +import cv2 +import sys +from matplotlib import pyplot as plt + +if __name__ == '__main__': + if len(sys.argv) != 2: + print("usage: python3 im_hsv_shower.py image_file") + exit(0) + im = cv2.imread(sys.argv[1]) + im_blur = cv2.medianBlur(im, 3) + im_hsv = cv2.cvtColor(im_blur, cv2.COLOR_BGR2HSV) + + f, ax = plt.subplots(1,2) + ax[0].imshow(im_hsv) + ax[1].imshow(cv2.cvtColor(im_blur, cv2.COLOR_BGR2RGB)) + plt.show() diff --git a/blaser_ros/scripts/im_saver.py b/blaser_ros/scripts/im_saver.py new file mode 100644 index 0000000..a82d8bd --- /dev/null +++ b/blaser_ros/scripts/im_saver.py @@ -0,0 +1,34 @@ +#!/usr/bin/env python3 +import rospy +import cv2 +from cv_bridge import CvBridge +from sensor_msgs.msg import Image +import sys + +def image_cb(data): + global image_cnt + img = CvBridge().imgmsg_to_cv2(data, 'bgr8') + cv2.imshow('blaser image', img) + cmd = cv2.waitKey(32) + # save image if pressed 's' or space key + if cmd == ord('s') or cmd == 32: + print("Saved image no. %03d!" % image_cnt) + cv2.imwrite('img'+('%03d' % image_cnt)+'.png', img) + image_cnt += 1 + elif cmd == ord('q'): + print("Exit im_saver") + rospy.signal_shutdown("User commanded exit") + +if __name__ == '__main__': + image_cnt = 1 + rospy.init_node('im_saver') + if len(sys.argv) < 2: + print("Usage: python im_saver topic_name [starting_index]") + exit(0) + if len(sys.argv) >= 3: + image_cnt = int(sys.argv[2]) + image_topic = sys.argv[1] + rospy.Subscriber(image_topic, Image, image_cb) + print('Press "s" to save image or "q" to exit!') + rospy.spin() + diff --git a/blaser_ros/scripts/img001.png b/blaser_ros/scripts/img001.png new file mode 100644 index 0000000000000000000000000000000000000000..aa541e01f848481c5fbe521c1d488fc9122a8f00 GIT binary patch literal 5925169 zcmXt9c{~&T{~t!qV!0*5TtnB~E2iE<7hx7=w)ha828?PBxCT<0#!JF>(0{~ouW=5|~vp(dS|UupcPdzf(Y zq4laXNaKYd8^Y}(gJ9msqr3B1)3gcL{>s?65g0!Jc=<>NuVqsnp2jY?ZCaHmyZI+P z<_d_d=E)pV|Kc>DP{{UntO`%&W3x1I8lUEduz)yt?v9Nz;1XDH#0+xZ?*fm3pd{B< 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assert(time_offset != 0) + imu_values = data.rstrip().split('\t') + assert(len(imu_values) == 7) + msg.header.stamp = rospy.Time(imuTime2machineTime(float(imu_values[0]))) + msg.header.frame_id = "imu" + msg.linear_acceleration.x = float(imu_values[1]) + msg.linear_acceleration.y = float(imu_values[2]) + msg.linear_acceleration.z = float(imu_values[3]) + msg.angular_velocity.x = float(imu_values[4]) / 180 * math.pi + msg.angular_velocity.y = float(imu_values[5]) / 180 * math.pi + msg.angular_velocity.z = float(imu_values[6]) / 180 * math.pi + + return msg + +def initTimestamp(): + global time_offset + # discard frames in the beginning + ser.flushOutput() + ser.flushInput() + for i in range(50): + ser.readline() + + # do a cross time difference + num_cross_td = 1 + time_offset = 0 + for i in range(num_cross_td): + t_machine_1 = rospy.Time.now().to_sec() + data1 = ser.readline() + data2 = ser.readline() + t_machine_2 = rospy.Time.now().to_sec() + + t_imu_1 = float(data1.split('\t')[0]) + t_imu_2 = float(data2.split('\t')[0]) + + time_offset += (t_machine_1 - t_imu_1 + t_machine_2 - t_imu_2) / (2 * num_cross_td) + print("set time offset: ", time_offset) + + +def loop(): + while not rospy.is_shutdown(): + data_str = ser.readline() + msg = str2msg(data_str) + imu_pub.publish(msg) + + +if __name__ == '__main__': + try: + ser = serial.Serial('/dev/ttyACM0', 9600) + except: + ser = serial.Serial('/dev/ttyACM0', 9600) + + rospy.init_node('imu_driver') + initTimestamp() + loop() diff --git a/blaser_ros/scripts/laser_calib_test.ipynb b/blaser_ros/scripts/laser_calib_test.ipynb new file mode 100644 index 0000000..ecbafaf --- /dev/null +++ b/blaser_ros/scripts/laser_calib_test.ipynb @@ -0,0 +1,90 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "from matplotlib import pyplot as plt\n", + "from mpl_toolkits.mplot3d import axes3d, Axes3D\n", + "import math\n", + "import sys" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "def draw_frame(ax, R, t):\n", + " axis_len = 0.1\n", + " origin = t.flatten()\n", + " end_x = (t + axis_len * R[:, 0]).flatten()\n", + " end_y = (t + axis_len * R[:, 1]).flatten()\n", + " end_z = (t + axis_len * R[:, 2]).flatten()\n", + " axes_len = 0.1\n", + " ax.plot([origin[0], end_x[0]], [origin[1], end_x[1]], [origin[2], end_x[2]],\n", + " color='red', linewidth=2)\n", + " ax.plot([origin[0], end_y[0]], [origin[1], end_y[1]], [origin[2], end_y[2]],\n", + " color='green', linewidth=2)\n", + " ax.plot([origin[0], end_z[0]], [origin[1], end_z[1]], [origin[2], end_z[2]],\n", + " color='blue', linewidth=2)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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F5gGVQD6k6/P5JPVVAaC/vx9LS0vs/y8vL0v2N+nv78fJkyd5P/vBD35Q0s/KpCsAMUEDUdXodLqMOBwxkM2DSpMuwzBYX1+HzWZDc3Mz9u3bh7m5Ocm9MSGUIl230UDMxqPRKFQqFUZGRgDwBR9ut5snAODuF6ersaSiGu2Mala6Up/X5/NJbi8cPnwY8/PzsNls6O/vx4kTJ/D8889L+tlbbrkFX/nKV9jcwZdffhlPPfWUpJ+VSZcDsvZF9j8HBwdZ8lpYWEBrayt2794NvV4v+TGVSiW7Q1oJkPgem82G1tZWngCj0vu+6aiH9kKhSCfBXIKPYDDIk8YSnwKx6PZ0VKO/Wi3SzaenSwx4pEClUuHb3/42brnlFiSTSXz605/GzMwMHn30URw6dAi33XYbTp8+jY985CPweDx48cUX8dhjj+Hy5ctob2/HX/zFX+Dw4cMAgEcffZQdquV8Xknf1eBI37FNJpNwuVygKApLS0vo7OzMGYcjhkrt2KZSKaytrWFhYQFtbW04cOBAhtrteiLdSleCUltI2QQfZK2NK/jQaDQZa23ETrGWJcClhNT2QiHH1q233opbb72V97UnnniC/e/Dhw9jeXlZ8Gc//elP49Of/nTez3ldk66QoCGVSmFlZQUulwstLS2S43DEoFKpSkK63FwrLsjrtdvtOS8O1SbdRkaxJK9Wq9HW1sbrR5Lhp5C3rVqtRiQSwdraGi/1oZyoRpuMQMrvlpBurbexrkvSFdqxpWkadrsdGxsb6Ovrg9FoxNjYWNHPVapKN703TIIpFxcX0dXVhcOHD+fsDZaTdKUc6NdTe6EU4O4Yc29dGYZhfTHi8Tgv9SE9nLIYwUc6qjVIk4poNJpX669auK5IV4hsY7EYbDYbPB4PBgcHccMNN4CiKDZhtViUknRTqRRSqRSWl5extLSE7u5uSWRLUO1Kt9FJt1KgKApqtRpNTU0YHBzkvYZoNMq2KZxOZ4apfHpScD6oVntBKrxeb027ixFcF6QrJGgIh8Ow2WwIBAIYGRnB9PR0WW5LSkW6FEVhcXERGxsb2LZtW0FtD5l0y4tq95C5gg+hHWPSphASfJCNimym8tUg3XwGhvlsLlQTDU26QoIGbhzOyMgIZmZmynqyFEu6JHLd7XZDp9MVbJoDlI904/E4HA4HmpqaYDQaKyYOqCVUerCVz+53tqRgYqXo9/uxurrKE3xwV9u0Wi2SyWTF/Yzz3dGtdWEE0ICkKyRooCgKXq8XVqsVADLicLI9VrHkUSjp0jSNpaUlOBwO9Pf3o7u7G319fQUTLlC8jDcdxNhnY2MD3d3d8Pl8cDgcrAE5OWnJ341c6dbqtkQ2KBQKnmEMARF8BINBnq9tIpGAXq9HIpHg7RiX833ns6Pr9XrlSreSEBM0uFwu2Gw2aDQaTExMSO75iDly5QulUsmLHskFMtBbXV3FwMAAbrjhBiiVSly5cqVowixVpZtIJGC327G+vo6hoSEcO3aM17oh74Pso5IVqHg8DpqmYTabeWRcrYl4KVGPpCsGIvhIN0Can59HU1MTlEolL/GBmMpzV9tKtZeez46u3F6oEMjaVzKZxIULF7Bnzx4AwMbGBhYWFmA0GjEzM5O3z4BKpcrrKpvtcUKhUM7v4xIZl2wJStEbLtatjKZpxGIxvP322+zQkZz4xNqSQGgfNRgMwmKxoK2tDaFQCEtLS+zUndtbNBqNRQdWNhIJ1sLzAVu/U5PJJBi/w81Cs9lsvGBK7gU23zu1fH0XZNItI4R2bKPRKJaXl7G8vIy2tjbs27dPUhyOEEq96iWGeDzOrqpt376dR2RclKJKVSgUSCQSef8cTdNYXFzE6uoq6w9cSJuDxG53dHTw/B/S04NXV1d5/gXcNoWckbaFWlKkZTOVJ2S8traGYDDI9oXTpdBixU2+Pd3e3t7831iFUXekK5bQsLS0hGAwiGAwmHccjhBIpVssxEg3Ho9jYWEBm5ubGBoaEiXbXI+TD/Il7mQyicXFRaysrKC/vx/Hjh3DmTNnCn5+sZ6uWHowkWQHg0E4nU42I40by0P+rvYqU6NX1kD+2wtCKcFcwUcwGBQ1lSc7xvmSrlzplgHJZBKJRIK10ltcXMTa2hr6+vrQ2dmJ7du35yTcL31JiaUlCs8+S4NjpcpDuUg3FothYWEBLpcLQ0NDGB8fl3TylKrSlfIYZGPC4XCgr6+Pl3xRzDAs358V8y8QS4Lgmo9rNJqKZ6RVknTrVQacTfDBNZUngo9YLAa1Ws0O74xGo+iOsUy6ZQK5RSZxONu3b2dJ4erVq5Jun196SQGzWYEnn0yis1P4xCw16ZJUCY/Hg+HhYUxMTOR10lSi0uUKL3p7ewXX02phA4Eby0OQbj6+uroKv9+PM2fO8NafCCGXmiCvl0q3XM8pZipvs9mgUqnQ1NSUVfCxsbEhk2654PP5cOHCBUHikkqUZLbj84l/T6l6uolEAj6fD+fOnStKhKFUKhGPx4t6LWKky5UU9/T0ZN0FLqbiLidhp5uPx+NxXLlyBbt37+atPy0tLbET9/QWRTHreNUg3WJeb6HPWek2TjKZREtLC9rb20UFHxsbG/jqV7+Kq1ev4s4778SuXbvwgQ98AJ/5zGdEHzdXIGUsFsMnPvEJnD17Fh0dHfjRj36E4eFhJBIJ3HPPPTh37hxomsYnPvEJPPzww3m9p7oj3ebmZlaqmw6ppEs2Yfx+8e8pttKNRCKwWq3w+XxQKpWir1kqSpGTlk6YXLOc7u5uSSq3SrYXigVFUaLrT1xXL5IcnEwm2b4iIWKp3gWVrv6rtb1Qjepa6OKSPgd44YUXcOONN+KXv/wl7HY763Mr9pi5Aimfe+45tLW1wWw248SJE3jooYfwox/9CD/+8Y8Ri8Vw6dIlhMNh7Ny5E3fccQebpSYFdUe6CoVClLxI7ycXmpu3TpBAgAIg3l7IZ7+WIBwOw2q1IhgMYnR0FDt27MBbb71VEpFFqXq6qVQKq6urWFhYkGyWw32MeiHdbBBz9SJ9RTK8I7ey6S0KIdVdo6+MVQP5rG0mEgk0Nzeza6NikBJI+cILL+Dxxx8HANx+++2499572bsZYrsZiUSg0Wjy9nuoO9LNBqlESX5H2doLUvdrCUg4ZSgUwtjYWMnlxaWodMkB89Zbb6GjoyMvsuU+hhD51xKhAoVVnmJ9RSKXDQaDoqq7aDRaMt9kKahWpVtplMNLV0ogJfd7yM65y+XC7bffjhdeeAG9vb0Ih8P427/9W8nm5QR1R7rZiKywSlcYJPEhF4LBIJsEPDY2ho6OjrL09orppZI0CYvFglQqhaNHjxYc21NP7YVSQUwuS9M026IIh8OwWCwwm83QarW8FkU5VHfXU6WbT++63H31U6dOQalUYmVlBR6PB//xP/5HfOhDH2KrZimoO9IFxE9eqX1YqZVutsolEAiwfqZjY2NlTwIuZLDHzUkjUUMWi6WonLRGaS+UAiqVihUF+Hw+DA4OwmAwsCttwWAQbrebvWPirrQVq7qrNOlWK2Je6vskKcxSICWQknzPwMAAaJqGz+dDR0cHnn/+efzu7/4u1Go1uru78f73vx9nzpxpfNIVQ76kGwjk/1h+vx8WiwU0TbNkWwnkU+kyDIPNzU1YLBa0tLSwOWmxWKzovnCxpjmNRLpcEFLi7qEKqe5IhLuQ6o6bGpwL14PsmEAK2efjMCYlkPK2227D97//fdxwww34yU9+ghtvvBEURWFwcBC/+tWvcPfdd7Otuvvuuy+v99NQpCu1vWAybZ34Pp/4h5lOusSpP5VKYWxsTHLMM1CaGHYplS7DMHA6nbBYLDCZTNi3bx90Oh3776UQWBTbXmhU5KoEs0W4iwVVcok4XXVXaRlwrRuY57OjKyWQ8o//+I9x9913Y3x8HO3t7Thx4gQA4LOf/Sw+9alPYWZmBgzD4FOf+lTOwV3G8+f97moAxbYXyAUxW6VLSM7r9cJisQAAxsbGClq+LkUMe7btBYZh4HK5YLFYYDAYsGfPHsHYklog3UavdPNFLtVdulSWtCii0ShisRj0en1FyLcapJvPseL3+/Py0s0VSNnU1IQf//jHGT9nNBoFv54P6pJ0xSC130iOb79f/GD1+/3w+/2w2WwYHx8vyhyZkG4xdndC2wsMw8DtdsNsNkOn0+WMh6+klFgIla50Ky3LLeXz5VLdra+vY2lpCWazmWc6zm1RlPL1VCOUMp+7Q6/XWxcG5kCdkm6xBxPZXhASR7jdblgsFjaDav/+/UU9F1AeCS8hW61Wi127dkmyrizFSVgv1WqlX2MlBk1c1d3y8jJ27twJtVrNMx1P97ktlequGmq0RjS7AeqUdIvFe5Xu1t+kYiST/enpaZhMJvz2t78tyfOVinQZhoHH44HZbIZarcbOnTsz1pjKDTHSbeR+rRRU03uhGNVdNgMZLqrRXsiHdOslNQKoU9LNNbDIdYBwB2mbm5uwWq3Q6XRlI7FSkK7X60UoFMLCwgJ7UagG0itu7qZEKpViT2Typ1QJArWOWjS8kaK629zc5IVUiqnuap10/X4/xsfHy/yKSoO6JN1skJL4QNoLXm8Sa2trorfnpdg6AKQLLYTg8/lgNptBUVTJ2h3FgFvpulwuNnpn9+7dUCgU7G0uN0FAq9WyJ3MymWzIxf5q7LEW8nyFqu7ItgTZrKgE8iF6ub1QRZC1MaFFaYZhsLGxgfl5K4APIhxWYmZmN8TOf0LgpTBEz7fS9fv9MJvNYBiGHeSVqt1RDIiU+PTp01Cr1ewFi6Zp0DSdMYknptVkPzUej+Ps2bMAwLvFreVUCCmolnigVMilunM4HIhGo7h06RJ7IS236q4Ro3qAOiXdbAe30NoYV5nV0tKCgwf3wWhkEAxSCAbf6/GKPVaxZJBPeyEQCMBsNiOZTGJ8fLymDqRAIACHwwGKorB7925JRh/pYoHNzU0cPnw4Y/hDUiFIlAv5I9Xlq9qod9IVA1HdBYNBtLW1oa+vDwzDIBaLsS2KdNUdt0VRjOquEePXgTol3WxQqVSsQIJhGNZNq62tjVVmAVtEGwxuDdPEuKNSOWnAloeD2WxGIpHA+Pi4qPiiGid3OByG2WxGNBpFZ2cnDAZD3s5K6RAa/nCrYkLGxOWLW1WZTKacF8JqJDk0IukScFceSaurqalJkupOqVRmBFRKKWRIuKUU+Hy+vARL1URdkq4U0xuHwwG73Y729nYcPHgwo92wNUyj/v+ubvnTI8Tcz0KhEMxmM2KxGKt+EUOpYuGlEkQ0GoXFYkEgEMD4+Dg6OjrgcDhKEuMuhGwS2nA4jEAgwDMi56q2GinOvRYhpb8qprqjaZqXFixVdZdMJnmKymyQSbdKSKVSCAaDWFxcRG9vryDZEpA7kXIamRMIVbrElSocDrNkm4sIiSqtGNKVQtzxeBw2mw0ulwtjY2PYuXMn+9qK9V4oBGL9Rm5VvLS0xN7i6vV6aLVaxONxxGKxssTzCKHRK91CjztijZh++59NdWc0GuH3+9HU1CSpSIjFYpIJutpoCNLlxs3odDr09/djYmIi68+Qu9pCTG/yBZd0ick58d3NxwqSrMMVq2wTI12aprGwsID19XUMDw9jcnIy47XV0p6ukGqLVMVutxvxeBxXr17lVcWkPaHX62vaSyAbqiFOKcfKWDbVHdmAWVtbw9LSUlbVXT2IdbioS9IlJzg3SJHEzXi93qxRHQQtLVzTG+EPrZQ93VgshsuXLyMQCGBsbAydnZ15E1W5ZLwkVdnhcGBwcDBrHHwx1o6VAKmKlUolfD4fdu/eDYCfILy8vIxQKASGYdiqivwRSoSoNVSjf1wpGTBXdbe+vo6xsTHo9XpR1d38/Dxee+010DSNU6dOYWZmJueufaH5aABw8eJF/Omf/in8fj8UCgVOnz7Nzomkoi5JFwAWFxextLSEnp4eXraXWq0uaU6aFNeybIhGo1hcXITT6cTu3bt5t+r5otRyYu4dQm9vL2644Yac1Uw12gulgFhVTKoq7m4qkc9yq6paqoqrsedcrVBKsr0gprobHx9Hc3Mzzp8/j3/+53/G5cuX8clPflI0lLKYfDSapnHXXXfhX/7lX7B37164XHEdAHkAACAASURBVK6C7jrrlnS1Wq1gaq1UoiSVbjbTG5VKxap18kUsFoPVaoXX60V/fz+SySS6u7sLeiyCUlW6yWQSKysrbEaalEBKgnq8nRMDd/Czbds29utEPpvea9Tr9Wx7wmAwFLUOVQyqFb9ei4q09vZ2HDt2DP39/fjud7+b8zGLyUd7+eWXsWfPHuzduxcAeMPefFC3pNvb2ytIQNVOBI7H47BarXC73Wzkejwex8bGRl6PI4RiK12yknXhwgV0dHRkHTSKoZFIVwxi8tlwOIxQKAS/34+VlRV2HcpoNCIej8Pn87GtjXLieiFdqenD+ajRislHm5ubA0VRuOWWW7C5uYmPf/zjePDBB/N4R1uoW9IVg/SctK2/s5FuPiTHnfgPDw9jamqKrYJK1RsuptIlkt14PI6pqamCq+5SVNuVQKn7nhRF8SK/CRKJBEKhEJxOJ89UJr1XXMqquFrthVpdx6uUMIKmafz617/G6dOnodfrcdNNN+HgwYO46aab8nqcuiVdsQNYKim8Z++Yn7otHYlEAgsLC9jY2MDw8DAmJiYyDs5KiizS4fV6MT8/z0p27XZ7UdsP10Olmw/UajVaW1uh0WgwPT0NgD+BTxcJpPeKC7FarBYB1uqAMR+HsWLy0QYGBvCBD3yA9ay49dZbce7cueuHdMUg9cAoJicN2CJbu92O9fV1DA0NZZ34l+pgzZYekQ4iJ06lUpiammIVZMWSpky6ucGdwHOrYiISCAaDWFtbQzAYZK0WuWSs0+myHjOVjuqpBvI5xvIRRhSTj3bLLbfgG9/4BsLhMDQaDV577TV88YtfzOt9AQ1IulJBKt18ctKArRPHbrdjbW0N27dvz0q2pYZQekQ6uJLdiYmJjIOx2PaA2M/nQwKNLpkVg5BIgFgtksHd+vo6IpEIK53lkjGpihmGqaltinIgX7MbqbL0YvLR2tracP/99+Pw4cOgKAq33norPvzhD+f93uqWdLOdtFIsGaVUutzbeZqmsbi4iNXVVQwMDFSUbAmyEaaQZFfod1Qs6cqVbmnBtVrs6upiv86titfX12GxWNiqmFiFhsPhnFVxvSKXPSsXPp8Pg4ODkh+70Hw0ALjrrrtw1113SX4uIdQt6WaDFHcwQro+n/jjEIKx2WxwOBwYGBjAsWPHqlZlCHk4cAd4o6OjOfeAq0265OcbkShKiWxV8erqKrxeL6xWK8LhcEaMe6nN46vRzuDu6OaC1+vNO5G3mqhb0pVi75iddLeIIxAQfpxkMsnT80sRDuRCsWTDJUwpkt1cj1HsaygEjVgpV+r9kKrYZDKBoiiMjIwAyIxxTzePzyeWRwjVCKVsVC9doI5JNxukrI2JrYylUiksLS1heXkZvb29MBgM7MFdDEirotBgQPIYiUSCrbxzSXaFUA7SJBcAn88Hk8kEo9HI2i9K9W6oZ1Q7qkcoxp143pJeMYnlIatv+VTFcihladGQpCtl1ctoBCiKQShEgaYBheI9H4eenh5W7ba+vl6SFR3ymopJY3W5XHA4HBgZGSm48i5FpUtIk8iI7XY7+vv7MTw8jHA4DJ/Ph+XlZdZohhCx0WisGOFWkgirTbpC4HrecmN5uB4GTqeTtVnkJkGkm8dXS42WT0+3XmwdgTom3VyeurlIl6K2ql2fD5idXYHXa8O2bdsyJLGkQi1FTlohu7pcI3aTyYTu7m5WwlgIFApFUX4SFEUhmUyyw53Ozk4cPXoUSqUS8XgcJpOJJ6mNx+MIBAKsUUkwGMT58+fZk5sQcjF3ANVGLZKuGAoxjyfnUzwer1ikUj53hX6/XybdakOK/8KWlj4Jn0+Fzc043v9+Yf8BUqEWO5jIl3S5Kbutra04ePAg4vE4FhYWinodxbqEeb1e+Hw+OJ1OHDhwgHVYEhu2aDQadHR0sDr1CxcuYGpqivU32NjYYCfz5VRxlRPVIN1SXqSymceHQiFsbGwgHo/j8uXLFYtUomlasnsX2eKoF9Qt6eYapImRLrdyNBiOAVCho2MEanX50yOkki43ZXffvn3sAUXTdEldxvJBIBBgtecGgwEzMzMFPT9FUVAqldDpdBk9yGg0ikAgwFNxEccvUhHXYjpENUi3Es+nUChgMpkQj8cBAGNjYwD45uOLi4s88/j0oNFy56ORAqLWjolsqFvSBcSHMmq1mr09ImAYBmtra7DZbGyET2enFmZz6fwXskHK4/h8PszNzfFSdrkol59uNkQiEZjNZkQiEUxOTsJkMuH06dOC3yuVfMRM0Mm+arq3gVA6BLf/aDKZKhYLLoRqkG4le6zp7Yxs5vHBYLAkkUr59pHr4Y6IoK5JVwzc6pQkAVutVrS1tfGctfj2jtWrdMUku/k8hlRI9cMlbmkejwfj4+Os6XoqlRJtT0g58PPdXhBy/CK3vaT/uLCwwFuRMplMUCqVDTm0Ayq/Nys1Hy3fSKVsVbHUSjefgVutoCFJV61WIx6Ps2Tb0tLC6z8SSHEaK3dOWjbJbjoqUekmk0nY7Xasrq5muKUBxcf1lGJljNz2pg+DyIpUIBCA1+tFIBDA2bNneRVxOQzJq5E8XMnb6WK2F7KZx5PPaXl5OcM8PhqNSvqd5iMBrhXUNekKncAMw8Dn82FzcxMqlYrXE02HFE9dIrksFtzHkSrZFXqMcvV0U6kUVlZWYLfb0dfXJ6q8q9XbuPQVqWAwCLvdjqmpKVFDcu4qW76+wlzU0/ZCIUgmkyXdWhBLDea2ksLhMK5cuQKGYTKqYm6kUr3t6AJ1TrpcMAwDp9MJi8XCOvznGvZITY8oBemqVCqEw2HMzs5KluymoxQndjrpki0Js9mMjo6OvFIkCkElxREURUGlUqG1tZV3YnIrLW7/kTuVN5lMkhVc1wPpVuIWnttKWltbw6FDh3g2memRShcvXoTNZmP7yXq9PudzFJOPBmzFhO3cuROPP/44HnjggYLeZ12TLjmB3W43zGYzdDod9uzZA51OhzfffDPnz5NKN5v/gkqlyvA7yBc0TWNjYwNutxtTU1OSJbvlAJd0PR4P5ubmYDAYBNsv5UAtKNLEKi2ugsvpdLIKLm6VJbRTfD2QbrX8e7nm8emRSolEAu+++y5sNhtuuukmRKNRPP/889ixY4fg4xWTj0Zw//334/d+7/eKel91TbperxdXr16FVqsVnPbnAvESEfNfAIqrdIl/w/LyMtrb29HX15dhmFxpKBQKxONxnDt3DgAkpaeWErVAumIQ2lUlvgaBQIDn9kV2itODEiuBSpNuNWTAuaBWq3H06FGsra2hp6cHX/va13K23orJR6MoCj/96U8xMjKSN8+ko65JFwB27txZMGmYTKS9IP49hZCuUMqu3+/H6upqQa+zVIhGo5ibm4Pf78eBAwfqSsVTLYj5GnBveb1eL0KhEM6dO8frE5drp7hR2wuFgNvTzfUai8lHa2pqwtNPP41XXnkFzzzzTFGvua5Jt62tLSsh5rrtK3VOGhFe2Gw2dHd38/qjpdr3LQSJRAJWq5XNb4vH41Uj3FqudKUiPRnC5/NhbW0NIyMjojvFXDIutmfe6KSbz0ocSdsuNx5//HF88YtfLMldYV2TbjZIcfUqVU5aumT30KFDGdPwUpKu1B5iMpnE4uIiVlZWMDQ0hImJCdZFrVpoBNJNB/k8xNajSHuCa7vIjegxmUx5SZ4bnXTztXWUqo4sJh/t7bffxk9+8hM8+OCD8Hq9UCgUaGpqwr333iv9jf1/1DXp5jK9SSQSOUh36+9i2gtikt10lDoRONtJwDAMVlZWsLCwgN7e3oz1r2qm+dbqylkxyHYRFNspFovoSW9PCH3OMum+B7/fLzkJuJh8tDfeeIP9nscffxxGo7EgwgXqnHSzQUqFSj6rQtoLuSS7Uh8nX5DHEToJuBV3e3s7Dh8+nLFfWQuVZiWev5LvMd/thWwRPUTcQXaK0/dUTSbTdbEtkY+to9Q93WLy0UqJuiZdKZVuNpBBWrbthXRXLqmS3XSUutJNh9frxdzcHHQ6XdaKu9qVZqX3dCuBUpGg2E4x19OAGMxcvHgxw+mrXO+30gq4fA3M85lPFJOPRkC2GwpFXZNuNkipdKXkpBHkK9lNR7GWigTp5B0MBjE/P49UKoUdO3ZUbIWpUKKphUq71Chn5SnkaXDq1ClMT0+zPsWbm5tsVlq65LkefYrLSbq1gPr7RCRCCunqdIBKxSAWoxCLAUJK0Gg0ikgkgosXL+Yl2S0XSKVLpMTBYBATExO84U25kR4umUwmsbCwgJWVFd7+qslk4kk2GxWVvt3n+t+mp0KQPvHa2hqCwSCSyWRGe6IYy8VKIB/SDQaDFd0zLwXqmnSLbS+Q9Ai3e6uvy2mv8VJ2VSoVjhw5UhOenRRFYWFhAYFAAGNjY3lLiUsBQvwURbEDu76+Phw4cIDXl1xZWUEsFuNF9tA0XdVBXjlQK+nGSqVSMEGYSJ65MlpiuUg+l3IYkRcKqT3devTSBeqcdAHx21Wp8t100hVK2T116lTFhwnpSKVSWFxcxMbGBvr7+3Hs2LGqvR6KouByuVi7zEOHDrG/b25fUqFQgKIo0DTN3goTMUG6z0E53L8qhVohXSFwd4rTY5RIVWy32xEOhwVDK6vRnqBpWpKPAkGt/u7FUPekKwYplS5AdnUpeDwpLCwssooUbspusaGSXOR7gnIFFz09Pejv70dHR0fVCJc7Xd+zZw+ampqQSqWQSqWgVqvBMAzruUv+m6IoNDc3w2QyIZFIsNUYGRBxJ/VcIYHJZKqLnmQtk64YhHaK06PcrVYraJpGLBaD1WplP5dyxyhJPdcq7StcKtT+EZ0D2SpdKfJdssHw9ttX8Xu/pxO0NCy1p67UGBKn0wmz2Yy2tjZ2/YtsTlQasVgMZrMZwWAQBoMB09PT0Gg07IHPPfiVSiVO2k/i+cvP49lbnoWCUoCmaTgcDrhcLnR1dfGMTHp6etjPkdwKk5Oe+BxwibgYG8ZyoNLJw+WCkOQ5Fovh3XffhclkEoxR4t6plKoQkEq6gUCgKt4XxaLuSVcMuRKBSQWZTJoAdKK/fwdGR4UPGpVKVdId21wHFNkB1mq1GetfpUyPkBqbQtotIyMj2LFjBy5duoSrV6+ipaWFrWDJPvCcew5fPflV/NzycwDATcM34cauG2GxWNDV1YUjR45ApVKx1TD3bwCsJ253dzdLZLFYjO1Jkmh3jUbDDuuMRiN0Oh2P+Gp5T7cYVMPsRqPRoKuri7dTnB6jFA6H2Z1irsCjEB9eqWkQXq+37rx0gQYgXbGDXSycMl2yu337AN56CwiFVACEK8hSGplnI8xQKIT5+Xkkk0lMT08LXsVLlR6Ri5S4qrb+/n4cPXoUwBYJ79ixg20NOJ1O2Gw2OMNOPL/yPF5YfgE0Q8OgNuDeffdie2g71lPr2LdvH886khBHulKOEDD5A2xdQNvb23mbI6RPTNy/IpEIL8Sy0kkOlSTdWojqEYtRCofDCAQCcLlcsNvtSCQSvBgloQuk0HNKqXTr0cAcaADSFYNQS0BIstvWtnXyBwL5PVYhECPdWCwGi8UCv9+PiYkJnrWg1MfIB7mkxC6XC3Nzc2xbQ6lUsgRIURRP2tre1Y5/OPcP+MaFb8AX80FBKfCRwY/g9o7b0ZxqhjKlhFarhdfrhclkyrrEn4uIuRUxRVFsb5gM7BKJBHvSu91uBAIBnDlzhu0Tk5O+HHE9lao+GYapuPmM1OcT2inmxiilS57TfYrJ80htL/h8PskS4FpCw5Iut5rjSnbT/WOJ6Y3PV5n0CO7j0DQNm82Gzc1NjI6OYseOHTmrGIVCIWlAmOsxhKplErOuVCozhmTpfVuGYfC/5/43/uK1v8CCbwEAcOPQjbh38l60RFswOjqKrq4uxONx+P1+tiINh8NQqVRsWyJXP1CMiIGtiog7sCMnPSHZtbU1jI+Ps33i1dVVBINBXlwPIeJi4mgavdIt5oKSHqNEQNM0awSU/rlEIhF4PJ6cO8VypVsl5LpNOX/+fFbJLrmDr2SlS5y+lpeXsX379rzWv8qRkxaLxTA/P49QKITJyUk0NzfzNg/Sf8enV07j+KvH8dbKWwCAHR078MDeBzAUH0JfWx+2b9/Ovh+tVivYDwwEAvD7/VhYWEAoFGIJk5BxtoqUPDb3d0beTyqVgt/vh9VqRVdXFxiGYX0Otm3bxg7siOEMN02YOH/lK+xo5J5uucxuiFdt+k5xOBzGhQsX2MBKEuPO7ROTneJ8zG5qCXVPukLgSnZ37dqVVSYoNSctHo8X/boUCgWcTidmZ2fR09ODo0eP5r0SVYqeLhmkkZ3kjY0NNrONW9mmn9x2nx2Pvv4ofnLtJwCATn0nHjjwAA4pDqHN0IbR3aOSKkbSo01fVyI92uXlZQSDQTAMwyNBk8kk6kVLEjHMZjPC4TAriRZrT3AVXYQwye6qmLBDrD0ik25pQDZa1Go1xsfH2a/H43F2z9vlciEcDuNb3/oW3G43tm/fjjfeeAN79uzJSsCFZqO98sorOH78ODu8/eu//mvceOONRb3Puidd7sGenrIbCoVyGtJIyUkrxSDN6XTC4XDAaDQKun9JRam2F1ZXV7G+vo6BgQHekIxUttzfqy/mwzNvPYPvnP0OYskYtEot/mzvn+E/t/5n6JV6TExMFB1holQqBc1eQqEQ/H4/NjY2YLFYQNM0r0fb3NwMlUqF5eVlOByOjDZNPgM7Iuxoa2tjfwdcYYfT6UQ4HOb1I00mE/t7qwQamXQB4QuYRqNBR0cHb9bx7LPPskY1P/rRj/DEE0/g5ZdfFvwcislG6+zsxIsvvoi+vj68++67uOWWW+BwOIp6j3VPugBfsstN2bXb7TnXT97LSRN//GLaC6SfrNFoMDAwAK1WW1T/sNhK1+l0wul0gqIowSEZ96ClUzS+d/F7+O+/+e9whp0AgI9OfRT/dfC/Qh/XY3xkvKyeD2JetOFwGH6/H263G/Pz8wiHw7w1s2g0mnWBP9+BHdld5SrsuMIOt9vN3sWUW9jR6KQrtYdsMpmgVCrxh3/4h7jpppuyfm8x2Wj79+9nv2dmZgaRSASxWKyoXfG6J91wOIzTp0+zkl3uiUbWxrL9gog4otSDtHA4jPn5eSQSCbaf7HA4ih6CFVrpBgIBzM7OQq1Wo6urC/39/WybQWhI9pLtJTxy8hFcdV0FABzrO4b7Z+5He6QdQ91D6O3trYoaiNyCAsDa2hqMRiP27dvHvkeilotGo7xd3ubm5oI2J4DMgR15DXq9Hj09PbDb7WyvsdzCjmqQbjFFQiHPl4/DmJRBWjHZaNzh37/927/hwIEDRX+GdU+6er2eJ9nlIh97x2yVbj5EF4/HYbFY4PP5MD4+zvvQlEolotGopMcRQ76VbjQaZfuck5OTMJlMWFpawpUrV3iDq+bmZqjValzauISvnPwKfmX/FQBgpGUEX97/ZUzSk+g2dWNo11BVpbmJRAI2mw1erxeTk5O8k06n06G7u5v9f+7mBLE/JOkM5D1L2ZwQG9gxDAOv1wun04n29vaSCTuyodGTgGvV1vHy5ct46KGH8PLLLxf9WHVPukIDHwIp/gulyknjGuWMjo5ieno640QqRT9W6mNwh2RjY2Po6upi+5cDAwMYGBhgV3acTifOXDuDf7L8E15afwkppNCsacbn930ev2P4HRibjBgfH+eJGyoNItZYXFzE4OAgJiYmchKVRqNBZ2cn78JHNicCgQDsdjuCwSAoiuJdgMitqxDIsUbTNObn5xGLxbB3717odDrB9gQREeQj7MiWJNzo7YVyRPUUk41Gvv8jH/kIfvCDH2BsbCyPdyOMhiBdMeRT6Raak5ZKpbC8vMx+YGJVN3mcUq97pYNhGDgcDtjt9owhGcDv2xqNRii0Cvxg4Qf4m9N/g1AiBJVChTvH7sR/afsvaEo1IRlLglZt+SaQ3malvQ9IKkZraysOHz5cVKUttjnB3VogO6NkYEfImBj6LC8vY3l5GaOjo7yqFpA2sFMoFBnCDu5rIEnCpI3BrYqvB9KV+nyBQEAS6RaTjeb1evHhD38Yf/VXf4X3v//9Bb2ndNQ96QLFmd5wSZdhtjx20yEkm2UYBuvr6+w+qJT1r1JsQWSrdDc3N2E2m9l8tGxDshSTwokrJ/D4G4/DEdiaxt46div+bOzPYIgYWHEDsNWi8Pv98Pl8WFpaQiwWQ1NTE4+QyuE8FY1GMT8/D5qmMTMzU/SGhBiEfGjTU3wtFgtisRgSiQSMRiNGR0fR2tqa9T1LGdhxq2JuGCUhYiLsIKbk0WiUJf9SCDtyoRqDNKkXVamtj2Ky0b797W/DbDbjiSeeYLclXn75ZV4bK19QOTT4dZGrEo/HBUl3dXUVkUiEnVqKoaVFg1iMgtsdg5iN529/+1u8733vA7Alk52fn0dzczPGxsYkV37EW4EMfgoBwzB488032dcC8IdkExMT0Gq1omQLAG8svYGHX30Y59fPAwD2du/FA3seQG+0F/39/RgYGMhaTRFpJ+mX+v1+RKNRaLVaHhHn06vkgpjsbG5uZvTFqwEiHonH4xgaGuK1KMgkm9sbz/cCJDSw4x7PRGasUCiwvLzM+s2S15Au7Cil/eKlS5cwPj4umrlXaqysrLAtsGxgGAYf+MAHcP78+Vq1dxR9Udd9pQtsVbubm1vVbjbvZL/fj7m5OahUKuzevTvvyqtUO7YEpBKMRCLskCybkszsMeORk4/gRfOLAIBeYy8ePPAg9mAP2vRtGN01Kio+SH8N3KERAZeIyQUvnw0ChmGwsbEBq9WK/v7+qqd1EOXg6uoqxsbGeEKKnp4e9jWTYZnf72ffNxFVEDI2GAw5NyfS3ytpSZDPNBaLwev1orOzEx0dHZKEHVxxSSHhldVoL0ip3Mn5XqOEmxUNQbpiyGXvSNDczGBzk4LfT6GnJ5O8w+EwIpEIZmdnMTk5WbD0sFSJwAzDYH5+nlcJZlOSuSNuPPXmU/jH8/8IOkVDr9bjc/s/h/9k/E9oUjaVRNwACEt+iZrI7/fzNgi4laFer0coFMLs7CwMBgMOHjxY0TUlIZAd4M7OTrZVIwTuBUjofXM3J7h7x83NzVs99SwXFVLdci9GAwMD6O3tzWhNkDWnXMIO8hqkJnZUg3SlVNXBYLAuvXSBBiddMXvHdIgN08j6l9frZb1tpVSCYiiWdMkQJxQKQavVZh2SAUA8Gcd3z38XT7/5NDxRDyhQuGvmLtzdfzc0MU3ZxQ2AsJqI671gsVjg8XjAMAw6OjrQ3NzMxv5Uo8oldw/JZBJ79uwp+LZa6H1ztxaWlpYQDAYBIEPqzO1pRiIRXLt2DRqNRvRilI+wI5VKsY5fUhI7qjG4k+owlkttWqtoCNLN5qkrtb0AvEe6NE3DbrdjbW0NIyMjmJ6exrlz5yriYysEbopER0cHDAYD+vv7Rfu2DMPgxfkX8chrj8DitQAAPjj4QXx++vNoDjdjqKt64gZg6w6ktbUVgUCA9Ulob29nb4/JKlc+JjjFgmTQEWeycvSRVSqVoAdtMBiE3+/H2toa5ufnWbctmqbZ1hG3ik5HvgM7Iuwgx0AqlRJN7IjFYnC5XBVL7Gh0W0egQUhXDPnlpAFeL4OlpSUsLi6iv7+ft/5FNg8qvS7l9/sxOzsLrVaLvXv3QqvVwu/348yZM2wV09zczA6tzq2dw/FXj+M3y78BAEy2T+L4/uMYjA2i29iN4V3DVQ+AJBeQ7u5uHDlyhH096YQkZIIDQPJOrVSQwei2bdsq3kdWKBQZETkulwvXrl2DyWRCZ2cn7HY7zGYzq24j7z2bC1o2hV16rxjgJ3aQ4iAWi+HChQslE3ZIgVTSrdfUCKBBSDfbgSelOiWtoQsXrNi9Oym4/lUqe0epILe50WgUk5OTMBqN7Emyb98+JBIJ+P1++P1+rK+vY8GzgO8tfg8vr28pZjqaOvClg1/CMfUxGLVGjO0cq6q4Adja3iCDyPQkCSEImeCI7dSmE7GUEzcSiWBubg4AWIFDNRGPxzE3NweapnHgwAHe60mPUiere2RjhJBxNhKUMrBjGIbXrlIqlRgaGiqJsEMKpO7p1quXLtAgpCsGKVdgt9uNSCQFoB9tbcOYmBAXNlSCdLnG5tmGZERtpW3W4l/e/hd86/y3EKWj0Cg0uGP0Dvx+6+9DG9UCyq3v9Xq9OU/KciGbdDdfZNupJRcgcosuJG4g32+327G+vp4zqaMSIIKWpaUljI2NCe6AUpRwlDp3Y6QQk3jgvYEd9/Wsr6/DZrOxhMsVdjQ3N7M7yvkIO6SQaaNH9QANTrrZQFISFAoFhof3AgAiETUA4UFXqTYPAGH7ulQqBYfDgcXFRWzfvj3nkCyZSuIHl36AJ379BDbCGwCAP5z8Q3xm9DPQhDSsuCG9Ig6Hw9BoNLztgXIRMZdMpEp3C4GQGxnJ6yJbExaLhZ3Eh8NhdHZ2Sqq2y41AIIBr166hpaWlILVdqU3io9Eorl27BpVKlTG4ExvYAWCtLsnAjmEYVlxChB3JZDJnYofUwZ1MulVGthOZXKXJBxmJRGA2m9kBRWtrK371q62Dr5LpEeTkIkMysp5EeorZxA2/tP0SD598GFecVwAAR3qP4Eu7v4SOcAf6W/oxMDOQURFzB0PECKacROzxeDA/P8/mrFXaJCc9r4tsAQDAyMgIotEo3n33XSQSCeh0Ot57r9TAiHg/i4WQFopCTeJ9Pl/W6j/fgZ1Op0NTUxN6enrY85DsNHODK7nCDvI4uY49v9+P4eHhEvy2Ko+GIN1s4JKl1WqFx+Nhb9vJB1vJnDQu6XKHZPv374dGoxHNJAOAK84r+MrJr+AV2ysAgMHmQRw/eBzTyWm0NrVidKc0cUM5iTgSibC39+WU7koFUbc5nU5MTExkrMhxe6Ver5cnc04n4lJU6dyd28HBwQw70lQzAgAAIABJREFU0nIhm0n8xsYGLl26BIqioFar4XA44Pf72feebWc634EdWaUTE3bEYjGcPn06p7BDrnSrjGwHrVKp3IoIdzoxPDyMqampjO+XmpNWrC0jeT3hcBizs7OIxWIZQzIhsl0PreMvf/OX+J8X/ydSzJYD2H0H78Pv6H8HWqUW4zvGiya3YomYS27j4+M10Scl6099fX04fPiw4G2rUK+UZKiRW3Tiz1us3DccDuPatWvQarU1IQAhvVuPx4MDBw6wikauSbzdbkc8HuddhHJ5bWQb2Am1J0hiR2trK1wuFw4ePAiaplkidjqdiEQioCgKJpMJr776KjY2NiQPPguN6gGAp556Cs899xyUSiW+9a1v4ZZbbsnnVyyIhiBdIaRSKaysrMDj8UCn0+HYsWOijXwyk8lW6ZbCrIYkoF6+fBlTU1Po6OjIqiSLJCL49tlv42/e/hsE4gEoKSXu2XMP7ui9A4qoAhMjE2X1E5VKxAzDIB6Po7OzsyaqW3JRU6vV2L9/f97tAoqi2DBLIZkzV+5LVqgIIQlJbVOpFOslMTk5WTEP2Gxwu92Ym5tDX18fDh06xL5mMgAzGAzo7e0FIH4RkvLeucjWniDbOi0tLWz8EXlsUoiQnWbiNfK5z30OKpUKv//7v4/HHntM8DmLieq5cuUKTpw4gcuXL2NlZQUf+tCH2LTsYtAQpJsuDCBuW52dnejp6UF3d3fWXxRJjyjU3jEXuPaPxJSGHFzk9ac7gP346o/x2BuPYcm/5QN6y+gt+NzU59AUaMJg52DVxA1cIiZeFCReOxwOw2KxVHRYx0UymYTNZoPb7S56S0IIYjJn7vYAWaEi75uILnp7e0Wr7UoikUhgbm4O8Xhc8pqc2EWI+943NjbyNoknj72xsQGbzcZubmQb2BkMBtx333145ZVX8LOf/QwtLS3Y3NwUffxionpeeOEFfPzjH4dWq8XIyAjGx8dx6tQp3HDDDTl/Z9nQEKRL4PF4MDc3B4PBgAMHDqCpqYkNM8yGcuWkcS8AXV1dOHLkCCwWC5aXlxGLxdhbVC7eXH4Tx08ex5nVMwCAXV278NC+h9AX7UO3vhtDO4aqLm4gqbuRSARTU1OCQ6BKDOsI0r0JDh8+XLELkphROol2j8fjUKlU2NzcRDQa5RngVJKAuWtgIyMjbBx9McjHJJ4rcyaCllgshqtXr0KtVuPQoUPsPCJbnzgajeKb3/wmlpaW2LzBdENyLoqJ6nE4HDh27BjvZ4sNpQQahHQZhsE777zDDm/IxBqQ5r9Qjpw0EkjZ1NTEG5INDQ3B4/HA7/ez5KvT6eBT+PDt2W/j5ws/BwBsM2zDg4cexAHFARjUBoxNV1/cwHXdGhkZyTDw5qJSWxPEKKeW+qRra2tYXl7G+Pg4WxXTNM1WhVyZcz4GOIWCbG5otVoeuZUDUk3iY7EYaJrGtm3bWMe2bFAoFLhw4QK+8IUv4LbbboPNZivr+ygnGoJ0KYrC9PS0YO9OrVYjHo9n/Xmpla6UPV0yvSdDMrIGQ/q2Go0G27ZtY4c27ogbT/36KfzTxX9CIpWAVqHF7X234/be26GP69E33Idt27ZV/QAju67btm3L6rqVDaUkYiIi8Xg8mJqaqgkdPtlGaW1t5cmbga3jR2yNy+/38wxw0om40Dsb7kVycnKy7OZGYuAKWiKRCK5evQqj0Yi+vj6Ew2H22CI+wdyKuKmpCbFYDN/4xjdw8uRJPPfcc9izZ4/k5y4mqkfKzxaChiBdYGsnUEjyq1KpEAqFsv4suTv2+4FUChAqNnIN0miahtVqhcvlYqf3qVSKHQqkVzCJZAL/453/ga//5utwR90AgDt23oFPDX4KiqACAwMD7FrZhQsXkEwmYTAYWJ1+uSK+00Gku2q1uixigkKIOBaLweFwYHBwEOPj41X3VKVpGmazGcFgEDt27ODdaWVDNpkzGVgFAgF2n5Z89kajMednHwgEcPXqVV6KSDVBHPIcDgfvAsB972R9z+/3w+v14qWXXsJTTz2FeDyOyclJ3HfffTw1nhQUE9Vz22234c4778T999+PlZUVzM/P48iRI0X/LhqGdMUgpS2gUgF6PYNwmEIo9B4JcyHm48Adkg0ODrIfitiQjGEY/Nzyc3z15Fcx75kHAPyHgf+AL+36EkxBU4a4gTtB5kpdzWYzkskk72QshfkLQSKRgNVqhd/vx8TEREV3IsWImLxvhmGgVCrZwVUlh3VcpMtlhdYR84WYzJkQ8erqKgKBACtz5q5xqdVqJJNJWK1WeL1e7Ny5U/IFoJwIh8NsdZvLm5is77W1teH5559Hb28vvva1ryEajeLcuXPo6OjIi3iLieqZmZnBH/3RH2Hnzp1QqVT4zne+U5LzqyHieoCtakPo9j8QCMBms+W8JRkZ0WB1lYLZHINYUgg3sid9SDY8PJxTSXZ+/Ty+8upX8PrS6wCA8bZxHD94HKPxrbyt0VFp4gYCrucA6RemV0UmkymvPiFXujs0VF0LSAKi3vL7/ZiammIdubgVMbGJrNTWBNm5bWpqwvj4eMV7ydwMN/L+SYZbW1sbBgYGcgobyg2GYbC4uIjV1VVMT09LvnCfPXsW9913Hz760Y/igQceqLiasURo7LiebJA6ADOZGKyuUggEKOS61vh8PszOzkKv10tSkq0EVvD4G4/j+cvPgwGD9qZ2fOnQl/B+7fuhUWgwsXsC+mw5QSLgDmJIr4lbFZHb0633Z+LdngoRcbWlu+kgQ6mFhQVB9VY1JM6pVIoV20xNTVVNFcX97Ds7O9kW0ODgIOuBu7CwgEQiwfZJyedfCSIOBoO4evUqeyxJqRCj0SieeuopvPnmm/jBD36AmZmZsr/OaqDhSVdqZA+5m8u2q5tKpfDOO+8gkUhgenqajcQWI9tgPIi/O/V3+LvTf4cIHYFaocaf7PsTfLT7o2AiDMZHxku+KC/kz8od2CwuLrKTc+5J6HA4wDAMdu3aVdAFoNQgC/BGozGviXs5iZj47vb09NTEzi3DMFhdXYXdbs9wJ+O2pUif1OPxZCjMpHjz5gPi4La5uYnp6WnJ6Q6nT5/G/fffj4997GM4efJk1S/45UTDvDOxA0aqkow7TEsH6W9GIhFMTEygu7sbyWRSdEiWTCXxr5f/FU+88QTWQmsAgD+Y+AP8+cSfQ+VXYaBzgDUBqQSEBjZkSmu32+Hz+aBWq6HVarG0tMSejIUEGRaLRCIBi8WCYDAougOcL4ol4lgshrm5OdbLuNqre8B77Q2dTpf1osTtk3LDNKPRKPx+f4Y3L5eI85U5k+FdZ2cnDh06JOmiFIlE8PWvfx2nT5/Gv/7rv2LHjh2Sn69e0TCkKwapBw0xvfH732svkJWb5eVlDA0NoaWlBc3NzSyJC1W3r9pfxcOvPoxLm5cAAAd7DuLBfQ+iM9SJbl03hqarL24g/eiFhQX09/dj3759UCgUGdllXG/W9ISKcrymlZUVLC4uinpklBJSiTiVSoGmafT29mJgYKDiySHpIAq39fX1gtsbXIUZ12+Cm2rMlfrmuiNIpVKsmVQ+w7u3334bDzzwAO6880786le/aujqlouGeZfFnqDkLsjne0/hZLFY2EgZhUKBWCyGs2fPQqPRsARMVGWzrll89bWv4v9a/i8AYMA0gOOHj2MXswt6hR7j+8erfsIC78XIG43GDDGB0GI7N803vSLkvv9ifv9kv7W5ubmqvWQuEZO+fXt7O9ra2hAMBjE/P181iTPw3iyBJBSXsr0hlmrMJWLy+XPj5SmKwsLCAnp6enDw4EHJ1e2TTz6Jc+fO4fnnn8fU1FTJ3kc9oGFINxdyeXSSSndzM4rTpy9Ar9fjwIEDUKvVbN92aGgIw8PDiMVi8Pl88Pv9uGS9hOfMz+H/rP0fJJkkDCoDPn/g8/jd1t8FRVOYnJqsiajoWCwGs9mMaDSa1227UKot1/hlZWWF58DFJeJc4MqJ89lvLSdIeyMUCvGqNiHPgUoZw3O9dyttKKTVaqHVajPuCHw+H2uQrtFoeDJn0poSIuA333wTX/7yl3H33XfjmWeeqfpdXzXQMKSb7QAnarJsFZROlwCggt3uzTkk02q1aG5vxv9a+F/4xtvfgD/uh4JS4GPjH8Mfdf0RNHENooGtA9DtdoOmaTQ3N1flAOOm3JI0iWLJIN34hdyaEiIi8uampibeHQGpqrlraaXyASgW3E2JXDu3+fSIuVsDhRAxWUvcvn17xbx3cyEUCsFisaC/vx8DAwOgKIrnuWCz2di0CpPJhHfffRednZ34+c9/jsuXL+PEiROYnJys9tuoGhqGdLOB+C8IkS4ZkgWDegDj0Ot7odfHRIdkDMPg32b/DY++/ijsPjsA4EPDH8IXZ74IrU+LgYEB9Pf3g6IodoeWRGtzd2hbWlrKprUnr9PpdBYt3ZUC7q0pqQi5wxru1FytViMcDqO1tRX79u2rehgk8J5/Q1NTU8HeBKUm4lgshtnZWQDAgQMHaqI1RZR34XA4w6FMqDVFQix/+MMf4uWXX4bX60Vvby+++c1v4tlnn6369ke1cN2QbvoGQ/qQbGZmy2XI52PYVkT6yXBq5RSOv3ocb69suRTt6NyBhw8+jO3R7WhVtWLk0AjvhCVxMX19fexzcrX2gUCAt7pFrPCKrWaCwSDm5uag0WiqNm1PH9aQpNtIJIKhoSHEYjFcvnwZiUSCJ29ubm6uWE+XGK+7XK6yWEEWQsQmkwkejwdLS0s8w5xqw+VyYW5uDoODg5KHnLFYDE899RSuXLmCf//3f8f4+DjrdXy9Ei7QQKSb7SDg7uqKDclMpi0lmd+fWd3afXY8+vqj+Mm1nwAAuvRdeOjwQzisOgw1o8bELmniBoVCkSHxJNWAz+eD1WrN2BhoaWmRPKjiSncnJydrwgSGBG4uLy9jdHQ0w5mMm1TADZBMJ+JSV+lk57a3t1fyelMpkI2IXS4Xm+NmMBjg8XiQTCarluIMbB1TxMBp//79ki7gDMPg17/+NR566CHcc889+Pu//3v28yOComKQKwni9ddfx3333YeLFy/ixIkTuP3229l/+/73v48nn3wSAPDII4/gk5/8ZFGvpRA0jAwY2Dp4hd4PcaTXaDSYm5uDXq/H+Pg4OyQDgF/+UoWPfKQJN96YxIsvxgAAvpgPf/3WX+PZs88iloyhSdWE/7b/v+EPOv4AqUgKExPlSW7gVkN+vx+RSARarZbXH+XebtaidBcAvF4v5ubm0N7ejpGREcnEKSRvTqVSGaq6Qog4Go1ibm4ODMNgamqqJnZuuckS09PTaGlpEZU4F9sjzgeknzw8PCx5rzwYDOKxxx7D3Nwc/vEf/xFjY2MlfU3JZBKTk5O8JIgf/vCHPFPyhYUF+P1+PPPMM7jttttY0nW73Th06BDOnDkDiqJw8OBBnD17tlxJHtevDBjYIiWLxQKNRoMdO3bAYDBkDMm4ijQ6ReOf3/ln/OVv/hLOiBMA8LEdH8NnRj8D+ID+zv6yihuEqiHuMvvi4iLi8Tj0ej3UajU8Hg+7RlQLu46xWAzz8/NIJBIFKdxKLW8Gto6BpaUlrKyssMGktQCv14vZ2Vl0d3fz1sAqOaxLRzwex+zsLBiGkdxPZhgGb7zxBo4fP44/+ZM/wXe+852y3D1ISYIg+Wbpz//SSy/h5ptvZvvON998M37xi1/gjjvuKPnrzIbqn6ElBEVRvEqXrP+sr6+jq6sLO3bsEFWSESPzVVcIR793FNdcW7d5N/TfgAf3PojmQDO26bZhcGqwKlsI6YMqokiKRqNoaWmB3+/HmTNnYDAY2Iq4lK5jUsD1bx0bGytpP1JM3kyImPjRcrO1SI+cSIprxeYQeG8oFQqFsHv3bkkXpkoQ8fr6OqxWK0ZHRyW7eQUCATz66KOwWq346U9/ypJeOSAlCSKfny1FEkS+aCjSJSBrUg6HA8PDw2hpaYHH40E8HodCoRAcknlTdgDTcDgDgOsaRtXb8NV9X8aY4RAMlAFj+8dqYoJMcsC4vr0E3Nty4tDPMAx7Ara0tJQtJsbtdmN+fp6tuCtBbEI2iFyfCZKXxjAMOjs7odfrEYlESjKsLAZkplAKO8hSEXEsFsO1a9egVColb3AwDIPXXnsNDz/8MP78z/8c//AP/3BdD8ikoqFIl+xaWq1WbNu2DUePHgVFUYhGo9jc3MTZs2dBURRvSEX8Bbb5VwFMA9EW/M1LwGdPrUObfADJvj4whw8jdfAgUocOIbV//3vytSq8t4WFBbaXlX6AC92Wk2qQ+CwEg0E2PJBUxMV4LJAU12QyiT179lR9BYwQcSQSQSgUwtTUFDo7O1kiJsNKpVLJG9RVwmciGo2yk/tyRgvlS8SpVAoul4v1FZGCQCCARx55BIuLi/jZz36GoaGhsryXdBST5tDf34+TJ0/yfvaDH/xgiV9hbjTUIO3KlSuIRqMYGxvjDcm4lW0ymWR7o36/n1XUGI3NePHVy9i15sKB5Tex7f+1d+ZRTd3pG38uEAxrWK0ssibsCgRwGX86HemI0tYZO2511BmPnWNn6jhjrXU7HdFaUan2zAyO1o61VkV0tFY7rdvReqpTSVisIjuColLKHiAkgSTf3x9wrzfIEggJAe7nHM8RvEluMLz3e5/v8z7vo0fg5+aC6jLDh1AUSEgIU4Q1sbEg4eGAEePy6HlrDg4OzHszBHpeF/1zGEhrL7vpwpw0UrlcjsLCQp3N0u5ob2/X2aw0RnszDXtqgjn9rJqamlBQUACgo1B3Have3YqYEIIbN25g8+bNWL16NVauXGnS1a1arUZQUBCuXbsGLy8vxMXFIS0trdsYyN///vd45ZVXdDbSYmJikJOTA6DD/5ydnW2sMUY9fnBGVNFta2uDRqNhRjd3JyN0h0qlQnl5OaqqqmBtbc0kMzna28O1thaCoiJY3bkDi6wsWOTmguoy6JKMGQNtZGRHIe4sxiQwsPu5P/2ga+uuMdtk6dZOuggplUqd+D/a/QE8s1u98MIL8PX1NYtbSvb49YHOTOvJNcIuxP2NQGxpaUFhYSEcHR0RGBhoFnoy7XZ58uQJRCKRjkTVk2siMzMTWq0WmZmZkMlkOHToEHx8fIbk/L/55hv89a9/ZSZBbNmyRWcSRGZmJubNm4eGhgbw+XyMGzcOeXl5AIBPP/0UO3fuBABs2bIFK1asMNZpjo6iu379eiZ/NSYmBg4ODn3+gtTX16O0tBTOzs7w8/MDj8djMkjZRYgejeNkYwOXx4/hUFAAy+xsWGRnw6K4+LnnJU5O0IrFHZJEbCw0YjHQmXHaF8Zo3e0v7I4y+g89wZXH48HPzw/u7u5m4Zaora1FaWkpPD094e3tPagXAaVSyUgT3V2Mutr3aOiw87q6un7lyhobhUKB/Px82NvbQygU6nURUKlU+OSTT3Du3DmoVCpotVq4uLjg9OnTZrNqN0NGR9EtKipCRkYGJBIJcnJy0NbWhoiICMTExCAuLg7h4eHM7WZDQwMePnwIS0tLiESiPrVItmVJJpMxO+WOjo5wpig4P3gA2/v3O4pwVhYsqqqefw5vb53VcFd9uGvrrrmsIulg6qqqKvj4+ICiKKYIabXa51qbTbWaozVSiqIQFBRkEs8tO2eCvii3tbXBxsaGKcJ01KGHhwfGjx9vFv+HbMtcf0bnyGQybN68GdXV1Th48CCz+19TUwMXFxezWLmbKaOj6HZFqVTihx9+QEZGBjIzM5GXlwcej8cEdqekpCAkJGTAvxTdaaP07aiLQgGn4mKMuXu3owjn5PSqDysmTECpqyvUISEIDA01C9M+8GwVOW7cOPj4+Dz3s2JfjOhbUgA6G3WD7ZhgW9O63h4PBfSdUUNDAyoqKpjUNbqrTiAQMIMjhwK5XI6CggIIBAIEBAToVSgJIbh69Sr+9re/4e2338by5csH9f+wr64ylUqF5cuXIzs7G66urjh16hT8/PzQ3t6ON954Azk5OVCr1Vi+fDk2bdo0aOc1iIzOotuVs2fPIikpCYmJieDz+cjKysKjR48YN0BMTAxiY2Ph7Ow84Nt5duyjTCZjmhgEDg5wqakZMn24vygUChQVFTF3Av25CLBtWzKZDHK5XMctIBAIBmzipzNlXV1d4efnZxYrLbq1vKysjOneAsC0N7MlKnZ7s4ODg1HlGXbgOd3ppg+NjY3YtGkT6uvrcfDgQb3dAfqiT1fZv/71L9y7dw8HDx5Eeno6zp07h1OnTiEtLQ0XLlxAeno6WltbERYWhhs3bhjVGzxAuKILdJijXVxcdKQEugVTIpFAIpEgKysLzc3NCA0NZYpwZGTkgFee7GwBuhjTLa3a1lbg7l0E1NXBqaSkQyPWRx+OiQE6f7EHGzoEpra2FiKRaNB2dntyC3QNg+/t8SUlJcymoikzZXtDqVSisLAQPB4PIpGoVxsYIUSnvbmrPDOYDS306BxXV1f4+/vrtUolhODy5ctISkrCO++8g6VLlxpFGrl9+zaSkpJw+fJlAEBycjIA6KxYExISkJSUhKlTp0KtVmPcuHGoqalBeno60tLScO7cOchkMkydOhUZGRnGciAYwuhuA6bp7optYWGBgIAABAQEMO2A7e3tyM3NhUQiwdGjR3Hv3j1YWVlBLBZDLBYjNjYWIpFIr18OiqJgZ2cHOzs7ZlhgbW0tiouLwefzwZs8GblyOSxnzoSjoyOcALiUlcEmNxcW2dmwzMwE9dNPsLx+HZbXrzPPq/X27ijC9IrYQP8wPcKnrKwMnp6egz6ZgMfj9RiGLpPJmAxetjYqEAhgZWXFDF/sTwaAsWFrpEFBQXr90lMU1W3ynFwuh0wm02lo6VqI9f2/YG/ghYaG6h1W39DQgI0bN6KpqQmXLl1izs8Y6NNVxj7GysoKAoEAdXV1mD9/Ps6fPw8PDw+0trbio48+MseC2yujqujqC4/HYwrsH//4RxBC0NzcjKysLEgkErz//vsoLS3F2LFjmdVwbGxsn2HcCoUCxZ0r2aioKJ3WTzoEWiaTocrTE61OThjz0ksQODrCubUVzqWlsP7hB0YftnjyBBZPngBffgnAMP8wHbfH4/EQHR1tss677sLQlUolZDIZ6uvrmQkO1tbW8PT0BJ/P7zOM3hQ0NzejsLAQTk5OBnffsRtaaNgRoE+ePEFLSwsA9NlZSPtux44dq3dyGiEEFy9exLZt27BhwwYsWbLELDb+ekIqlcLS0hKVlZVoaGjA9OnT8dJLLzFZDMMBrujqAe1SmDlzJmbOnAng2SBFWpY4cOAAc0tOW9bEYjFsbW3R1NSER48eMdOEu7sydxcCTVu26ghBua8v2jw8YDd/PqMPOxYW6ujDFgUFsCgoAI4f7zhHtj7cuSpm68Nsb6sx8mT7C53Ba21tzbhDxGIxrKysdMLguyaO9WclaAgajQZlZWVobOyYLmKsMUzdRYCydXK6s5DOo7C3t2e084iICL2ll/r6emzYsAEKhQJXrlxh7sSMjT5dZfQx3t7ezORqV1dXpKWlYfbs2eDxeBg7diymTZuGrKysYVV0R5Wma2w0Gg0KCgogkUiQmZmJ7Oxs1NbWMrusr776KsLCwga8UmNrgjKZDM3NzUy2gmDMGLg8eQL7/Hy9/MPNoaF49MILsPvFL+ARHW0Wt+wAmExdT09PjB8/vtvzYq8EaccEvWJkOyYG8z3V19ejuLi41/MyNWq1Gj/++CPKy8thbW0NQshz05u7a28mhODrr7/G+++/j82bN2Px4sUmfT/6dJXt378fubm5zEbaF198gdOnT2P37t0oLCzEkSNHIJfLERcXh/T0dEycONFk568n3EaaqSGE4JVXXoGvry8SExNRVFQEiUSCwsJCCAQCxjscGxsLLy+vAa/U2NkKTU1NTLaCQCBg9GH+vXs6+nBXdPRh2j9s4mGabM9tcHBwvyUOOgyebd8bjPHxbW1tKCkpQVtbG0LNyMqn0WhQWlqKlpYWhIaGMlIVLVPRFyS5XA4ejwdHR0dIpVIEBgbi0KFD0Gg02L9/v95JYoNNX11lSqUSy5Ytw507d+Di4oL09HQEBASgpaUFK1asQH5+PgghWLFiBdavXz8k76EPuKI7FMhksudsOnQDBC1LSKVSJg2N1obFYjEEAsGAVx+0U4AuxHQ7q0atBlVZidDmZjgVF3eshvvwDxs7X8KYntuefg60LtpTNxmgGzDU3cSLoYRedbPn8fUG3eK9ceNGSKVSZqU5c+ZMc/W4jgS4omvOaLValJaWMkU4Ozsbra2tCA8PZwpxRETEgDa42Mlrzs7OjD6qVqs7PKOd+RIOBQX6+4c7rWskMBAwoBDRAd5ubm4m89yyW5vZPmr2ilitVqOgoAB8Ph8ikWjImhq6olarUVxcDJVK1a9Vd21tLdatWweKopCamoqxY8cyF5QpU6YY+axHLVzRHW60tbXhhx9+YArx/fv3wefzER0dzRTigICAXmWJlpYWFBUVwdbWFoGBgToeUlofpleBOp1kY8bA5fFj2OXldejDOTmD6h82J88tO2dDJpOhpqYGbW1tcHJygpubG9NNNtRNGLW1tSgpKenXOCZCCL788kvs2rUL7733HhYsWDCoq/WBdpUBwL1797Bq1So0NTXBwsICmZmZZiPdDBJc0R3uEELQ2NiIzMxMZqOurKwMXl5eEIvFTEedm5sbY7ei9VF9w1boHXJ27CXtkXQC4PzggUH6MCGE8dz6+/v3abEzJU1NTSgsLISrqyt8fX2hUCh0mhiAjunOtCzR22igwaS9vR1FRUXQaDQICQnR+26nuroa69atA4/Hwz//+c9BnypsSFeZWq2GWCzGsWPHEBkZibq6Ojg5OQ35hW2Q4YruSITWQzMyMiCVSiGVSvHw4UMQQrBw4UIkJiYiKirKoLlZdNQfXYiVSmVHA4ODA1wUCgiKijr8w33ow6qIbaDCAAASEUlEQVTISDzx8IA6Jgaes2aBZyYdZRqNBg8ePEBTUxNCQkJ6jM/sbsOSPUKIHYg/WNATJvqjKRNC8MUXX2DPnj1ISkrCa6+9ZpQLmyFdZRcvXkRaWhqOd1obRyhcR9pIxMLCAr6+vvD19cWiRYuwaNEiREZGYtGiRcjPz0d6ejo2btwIiqIQFRXFNHIEBwfrvaroOoWA3cBQrdGgxMcHGi8v2C9apKMPW+bk6PiHbQoKIOp8TmPowwOBDvPx8vKCSCTqtTh1NxqIHXhEN3LweLznWpsH4pgoLCxkJtbqO2Hip59+wrp162BjY4Nvv/3WqLGLhnSVFRcXg6IoJCQkoKamBosXL8a7775rtHM1N7iiO4I4fPgws1KbPn06Vq1aBUIIWlpakJ2dDYlEgl27dqG4uBiurq6IiYlBTEwMJk2apHd7Ld3AYGNjwwS7sFtZH9naojkoCFRwMHjLl6O1vh5+Mhl8qqqe+YdLSmAplcJSKmWelzg7P9OHY2KMmi9BT7vVarWIiooasJZoZWX1XEML+86gsrKy1zD4rrAdE0KhUG9JQKvV4uzZs/jwww+xfft2/PrXvzYb2aY71Go1bt26hczMTNja2iI+Ph4xMTGIj48f6lMzCcOu6Boi3icnJ+Pw4cOwtLTEP/7xDyQkJAzBOzAe3d0a09NxX3zxRWYeFP3LLZVKkZGRgcOHDzNjd2j/cHR0NOzt7fX65e3aykonlGk0Gozz80OdXI4KDw9YT57M5A87lZaCn5sLi6ysZ/kS167B8to15nkH2z/M1pQDAwP1ngfWH3q6M2hqakJjYyMqKip0HBP0Rp1Go2GCc/QdDAkAVVVVePvtt+Hg4IAbN26YLObSkK4yb29vzJgxg/kZJSYmIicnZ9QU3WGl6Roi3ufn5+P111+HVCpFZWUlXnrpJRQXF4808X7AaDQaFBcXM/rwnTt30NbWhgkTJjCFOCwsrNdiwJ540Z3nlj0SSCaTQaVSdRQflj7Mo21rd+707B+mV8P9zJcoKCiAnZ0dhELhkOY3dE2eq62thUqlgpOTE9zd3fVKG9NqtTh9+jQ++ugj7NixA3Pnzh02XWUNDQ2Ij4/HrVu3YG1tjdmzZ2Pt2rV4+eWXTXb+JmBkbKQZIt7v2rVL51j2cRzdo1QqcefOHZ0QeHt7e52QHzrYvKSkBPX19XB3d4efn5/eYSs9jUWi8yW66sP99Q/TUy+qq6sRHBw85PkSbBQKBQoKCmBra4uAgACdLGa2ha9ryE1VVRX+8pe/wMXFZUhTtgbaVQYAx48fR3JyMiiKQmJiIvbs2TMk78GIjIyie+bMGVy6dAn//ve/AQDHjh2DRCJBamoqc0xERAQuXboEb29vAEBgYCAkEgmSkpIwZcoULF26FACwcuVKzJkzh5kUytE3hBDU1dUhMzOTKcRlZWWMhLF582aDQ+C7jkWicxUcHR3hxOfDuaICtvfv6+jDz51npz7cOmECyt3cYD1tGrz1TN0yBezpwMHBwXB2du72uK5h8Hv27EF+fj7q6+uxbNky/OEPf4BIJDKb98WhA+de4DAciqLg5uaGOXPmYM6cOcjOzsbKlSuxcuVKuLi44Ntvv0VKSgpaWloQFhbGrIgnTpyo92YV24ZFXzjZLoFCgQCt0dGwnjxZxz885t695/Rhh2vXQMegmEO+BPBsdI6jo2OfsZCWlpZwcnKCk5MTfvzxR6hUKkyaNAnz5s1DUVERNm/ejH379sHX19eE74DDUIZV0TVEvNfnsd0x0I27q1evYuPGjWhra4O1tTVSUlKYWMiRQlhYGG7evMlsoP32t78F0KHd0iHwR44cQW5uLpPVS+vDQqFQ7xVady4BOgC9USZDhbs7VP/3f7CdNQtWlpZoLSmBsL4e7g8fwrJTH+4xf5jVTUciIgAjtfwSQvDo0aN+j87RarVIS0tDamoqkpOTkZiYaDZdZQBQUVGBsLAwZtoER98MK3nBEPE+Ly8PS5YsYTbS4uPjUVJS0utKw5CNuzt37uCFF16Ap6cn7t+/j4SEBDx9+tSoPx9zhRCCpqYmJgReKpUyE4/Z+rAhoTJKpRL5+flob2+Hvb095HI5k7srcHCAc3W1wfrwQGlpaUFBQQGcnZ37bN1mU1lZiTVr1sDDwwN79+4ddD3akM83zfz580FRFCZPnswVXV1GhrxgZWWF1NRUJCQkMOJ9eHi4jni/cuVKLFu2DEKhkBHvASA8PBwLFy5k8mz379/fp3NBKpVCKBQy4v/ixYtx/vx5nQ/l+fPnkZSUBKDjA7h69WoQQhAdHc0cEx4eDoVCAZVKZbKpDOYERVEQCASIj49nbEGEEDx9+hQSiQQZGRnYv38/6urqEBQUxITAR0dH99nlRT/P48ePn/O2snN3y/l8tIhEsAwJgeObbzL5Eja5ufr7h2NjoRGL9fYP0/P3amtr+zU6R6vV4vjx4zhw4AB2796NhIQEozgTDPl8UxSFL7/8Ev7+/mYzr264MKyKLtDh6UtMTNT53vbt25m/8/l8/Oc//+n2sVu2bMGWLVv0fi1Dum7Y3UBnz56FWCwelQW3JyiKgre3N7y9vfGb3/wGQMfKKz8/HxKJBGfOnMGWLVtACMHEiROZ1XBISAhj92poaMCDBw/g4OCAuLi452xg7AkM9P8ReyxSgaMjWqOjMWbKlA59mBA4P3gA67t3defTDcA/TGc5uLu76z06B+iQvdasWYPx48fju+++01uGGAiGfL75fD52796Nq1ev4sMPPzTaOY5Ehl3RHW7k5eVhw4YNuHLlylCfitljaWmJCRMmYMKECXjjjTcYP2t2djakUilSUlJQVFQEgUCAMWPGoLW1FQcOHIBQKNR7JdjbWKR6mQwP3dzQNn067GbPhsDREU5yOZyKi2FFyxK96MOqzz+HJiQEZWVlaGhoQFhYWI9ZDl3RarX4/PPP8fHHHyMlJQW//OUvzbqrLCkpCWvXrtX7/XE8gyu6vWDIxh19/Lx58/D5558jMDDQpOc+EqAnKc+YMQMzZswAANy/fx/Lli1DYGAgPD09sX79elRWVsLf318nBN7R0VHvosXn88Hn85kONbrYy2QyVCoUKPLyAvH0hMPrr8PRzg4uNTUdY5G6zKdrtLFBgVQKDw8PxMbG6v36jx8/xp///GcEBATg5s2beqfCGYohn2/6buTdd99FY2MjLCwswOfzsXr1apOc+3BmWG2kmRpDNu4aGxvx85//HFu3bsVrr702hO9iZFFdXY3m5madixgdAk9302VnZ0OpVD4XAq9vcEx39DYWyYHHgzInB3W+vggLC9OZ8twbWq0Wn332GT755BPs3bsX8fHxw6arjE1SUhLs7e25jTRdRkZzxFAw0K6bHTt2IDk5GSKRiHmuK1eu9Nnvz1l4BgeVSsWEwGdmZjIh8GKxmCnE/v7+BjUWtLe34+nTp3j06BFT0OlwGzpprKdCX1FRgdWrVyMoKAh79uwZstt0Q7rKaLii2y1c0R0OcBYe40GHwEulUqYQl5eXw8vLiynCMTExcHV11Wu1qVarUVJSAoVCgdDQUNjY2IAQotPKK5PJno1FcnRkPLqnTp3CkSNHsHfvXsycOdOstVuOATMyLGMjHc7CYzwoioKzszMSEhKYdDk6oCcjIwM3b97Evn37IJPJEBISwjRxREZGwsbGRue52KNzQkJCmKJJURSjD9NTdtljkQ4ePIjbt29DqVTi1VdfRUVFBdrb2w2SPTiGH1zRNSM4C49psbCwgJ+fH/z8/LB48WIAHZJBXl4eMjIycOLECaxfvx4WFhaIjo5GSEgIrl69iuXLlyMhIUGv1mY6fzgtLQ2FhYU4evQo4uLicPfuXWRlZQ1p2hnH0MAlZYwQOAvP4MDj8RAVFYU333wThw8fRlZWFq5fvw5fX1+kpKRAq9Xigw8+wPz587F161Z89dVXqKqqQk8yXXl5OX71q1+hvLwc//vf//Diiy/Czs4OP/vZz7BmzZpBCau5dOkSgoODIRQKmTQ9NiqVCosWLYJQKMTkyZPx8OFDAMDVq1cRExPDxHdev37d4HPh6BvuMmtGcBYe84OiKGYI5b179+Du7s6EodMh8IcOHUJ1dTUTAh8bG4vIyEicPHkSx44dw9///ndMnz7dKNqtRqPBW2+9pbMPMHfuXB1J6vDhw3B2dkZpaSnS09OxYcMGnDp1Cm5ubvjqq6+4VnVTQwjp7Q+HCWlvbyf+/v6krKyMqFQqMnHiRHL//n2dY1JTU8mqVasIIYScPHmSLFiw4Lnn2bp1K0lJSdHrNS9evEiCgoJIYGAgSU5Ofu7flUolWbhwIQkMDCSTJk0i5eXlzL/dvXuXTJkyhYSFhZGIiAiiUCj68W5HFmq1muTl5ZFPP/2UrFq1ivj6+pIFCxYQuVxu1Nf9/vvvyaxZs5ivd+7cSXbu3KlzzKxZs8j3339PCOn4jLm6uhKtVqtzjFarJc7OzkSpVBr1fEcRPdZVbqVrRhiSLTEQDFklqdVqLF26VGeMtr4jZkYilpaWCAsLQ1hYGFasWMFsbhobrlV9+MEVXTPDkGwJGtrd0BeGuCWuXLmCiRMnIjIyEgBMNptruDCcbGBcq7pp4TbSRjHdrZK6anr6jNEWi8UjcdzKsKA/+wAAuFZ1M4AruhwDgh6jfeLECdy6dQvnzp3DNVYSF4dpiIuLQ0lJCcrLy9HW1ob09HTMnTtX55i5c+fi6NGjADpGXtENGY2NjXj55Zexa9cuTJs2bShOf1TCFd1RjCGrJPYYbVtbW2aMNodpYe8DhIaGYuHChcw+wIULFwB0zAOsq6uDUCjEvn37GFtZamoqSktLsX37dkRFRSEqKgrV1dVD+XZGB73tsg3Bjh+HCTHELVFfX0+io6OJXC4n7e3tJD4+nvz3v//V63UH6phoa2sjy5cvJxERESQkJOS5XXoODjOix7rKFd1Rztdff01EIhEJCAggO3bsIIQQ8t5775Hz588TQghRKBRk/vz5JDAwkMTFxZEHDx4wjz127BgJCwsj4eHhZP369Xq9nlqtJgEBAeTBgwdMoc/Ly9M5Zv/+/TqFfuHChYQQQk6cOEEWLVpECCFELpcTX19fHQsbB4cZ0WNd5QJvOEzK7du3kZSUhMuXLwMAkpOTAQCbNm1ijklISEBSUhKmTp0KtVqNcePGoaamBunp6UhLS8O5c+cgk8kwdepUZGRk6ASSc3CYCT3aVzhNl8OkGOKYmD9/Puzs7ODh4QEfHx+88847I6LgDrSNF+i4aAmFQgQHBzMXMg7zhiu6HMMGqVQKS0tLVFZWory8HHv37kVZWdlQn5ZB0A0qFy9eRH5+Pk6ePIn8/HydY9gNKmvXrsWGDRsAAPn5+UhPT0deXh4uXbqEP/3pT9BoNEPxNjj6AVd0OUyKIY6JtLQ0zJ49GzweD2PHjsW0adOQlZVl0vMfbNgNKtbW1kyDCpvz58/jd7/7HYCOBpVr166BEILz589j8eLFGDNmDPz9/SEUCiFlTTLmME+4osthUgzxlfr4+DBJWHK5HBkZGQgJCdH7tfu6jf/uu+8gFothZWWFM2fO6Pzb0aNHIRKJIBKJmHMbDAyRW/R5LIf5wRVdDpNiiK/0rbfeQktLC8LDwxEXF4cVK1Zg4sSJer2uPrfxPj4++Oyzz7BkyRKd79fX12Pbtm2QSCSQSqXYtm0bGhoaBuGnwTEa6cu9wMExIqAoaiqAJEJIQufXmwCAEJLczbGfAfgvIeRM59evA3iRELKq8+uPAdwghJw0xXlRFHW585jbFEVZAagC4A5gI/tY9nGGnheH8eBWuhyjBS8Aj1lfP+n8nrEf2xeZAEQURflTFGUNYDGAC12OuQDgd51/nw/gOulYLV0AsJiiqDEURfkDEAHgRF0zh0sZ4+AYQgghaoqiVgO4DMASwKeEkDyKorYDyCKEXABwGMAxiqJKAdSjozCj87jTAPIBqAG8RQjh7AtmDld0OUYLTwGMZ33t3fk9fR/7YpfH3hiUswJACPkGwDddvvc31t+VABb08NgPAHwwWOfCYXw4eYFjtKDPbXxPXAYwi6IoZ4qinAHM6vweB0e/4Youx6iAEKIGQN/GFwA4Td/GUxQ1FwAoioqjKOoJOlaVH1MUldf52HoA76OjcGcC2N75PQ6OfsO5Fzg4ODhMyP8DEZT1lFe8kzgAAAAASUVORK5CYII=\n", + "text/plain": [ + "

      " + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure()\n", + "ax = fig.add_subplot(111,projection='3d')\n", + "draw_frame(ax, np.eye(3), np.zeros((3,1)))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.9" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/blaser_ros/scripts/laser_resolution_analyze.py b/blaser_ros/scripts/laser_resolution_analyze.py new file mode 100644 index 0000000..afefd07 --- /dev/null +++ b/blaser_ros/scripts/laser_resolution_analyze.py @@ -0,0 +1,157 @@ +import numpy as np +from matplotlib import pyplot as plt +from matplotlib import cm +from math import sin, cos, pi +from scipy import signal + +im_sensor_size = [4e-3, 3e-3] + + +def calcImPlaneZ(fov): + """ + Assume sensor size is 3 x 4 mm + :param fov: fov of camera + :return: depth of image plane + """ + return im_sensor_size[0] / 2 * cos(fov / 2.) + + +def calcLaserPt(d, theta, phi): + """ + + :param d: + :param theta: + :param phi: + :return: + """ + return np.array([-d * cos(phi) * sin(theta), + -d * sin(phi), + d * cos(phi) * cos(theta)]) + + +def ptInImPlane(pt): + """ + Given 3d point in camera frame, calculate its 2d position on image plane, + i.e. 3d point with z = image plane depth. + :param pt: coordinate in 3d camera frame + """ + return -im_sensor_size[0] / 2 < pt[0] < im_sensor_size[0] / 2 \ + and -im_sensor_size[1] / 2 < pt[1] < im_sensor_size[1] / 2 + + +def calcRes(l, theta, phi, fov, d): + """ + Function to calculate resolution, defined by the projective length of a + unit-length line segment on the laser ray, given the camera's field of view + and configuration of laser. + We make the following assumptions: + 1. Camera is perfect pin-hole. + 2. laser origin has zero depth in camera frame. + :param l: baseline, distance between camera origin and laser origin + :param theta: angle between laser plane and line connecting laser and + camera origin + :param phi: elevation angle of laser ray + :param fov: field of view of camera in degrees. + :param d: distance + :return: resolution + """ + laser_origin = np.array([l, 0., 0.]) + ray1 = calcLaserPt(d, theta, phi) + ray2 = calcLaserPt(d + 0.001, theta, phi) + pt1_cam = laser_origin + ray1 + pt1_im_plane = pt1_cam[0:2] / pt1_cam[2] * calcImPlaneZ(fov) + pt2_cam = laser_origin + ray2 + pt2_im_plane = pt2_cam[0:2] / pt2_cam[2] * calcImPlaneZ(fov) + + if not (ptInImPlane(pt1_im_plane) and ptInImPlane(pt2_im_plane)): + return -1 + else: + return np.linalg.norm(pt2_im_plane - pt1_im_plane) + + +def calcResLine(l, theta, phi, fov): + """ + Calculate average resolution along a line, from 3 to 25 centimeters + :param l: + :param theta: + :param phi: + :param fov: + :return: + """ + gaussian_weights = signal.gaussian(29, std=10)[7:] + res_arr = np.zeros(22) + for i in range(22): + res = calcRes(l, theta, phi, fov, i * 0.01 + 0.03) + if res < 0: + return -1 + else: + res_arr[i] = res + avr_res = res_arr.dot(gaussian_weights) / np.sum(gaussian_weights) + return avr_res + + +def calcShpericalSectorArea(fov): + return 1 - cos(fov/2) + + +if __name__ == '__main__': + l = 0.02 + d = 0.1 + # analyze theta and fov at d = 0.1 + + thetas = np.linspace(0, pi * 4 / 9, 100) # 0 ~ 80 degrees + fovs = np.linspace(pi / 3, pi / 9 * 8, 100) # 60 ~ 160 degrees + X, Y = np.meshgrid(thetas, fovs) + Z = np.zeros((100, 100)) + for i in range(100): + for j in range(100): + res = calcResLine(l, thetas[i], 0, fovs[j]) + if res > 0: + Z[j,i] = res + else: + Z[j,i] = np.nan + + fig = plt.figure() + ax = fig.gca(projection="3d") + surf = ax.plot_surface(X / pi * 180, Y / pi * 180, Z, cmap=cm.coolwarm, + vmin=np.nanmin(Z), vmax=np.nanmax(Z)) + ax.set_xlabel("Angle") + ax.set_ylabel("FoV") + ax.set_zlabel("Resolution") + ax.set_zlim(0, 1e-5) + + # at 160 degrees, plot resolution to distance at given theta + fig2 = plt.figure() + res_30 = np.zeros(100) + res_60 = np.zeros(100) + res_80 = np.zeros(100) + d = np.linspace(0.03, 0.3, 100) + for i in range(100): + res_30[i] = calcRes(l, pi / 6, 0, 160 / 180.0 * pi, d[i]) + res_60[i] = calcRes(l, pi / 3, 0, 160 / 180.0 * pi, d[i]) + res_80[i] = calcRes(l, 80.0 / 180 * pi, 0, 160 / 180.0 * pi, d[i]) + plt.plot(d, res_30, label="30 Degrees") + plt.plot(d, res_60, label="60 Degrees") + plt.plot(d, res_80, label="80 Degrees") + gaussian_weights = signal.gaussian(29, std=10)[7:] * 2e-5 + plt.plot(np.linspace(0.03, 0.25, 22), gaussian_weights, label="Weights") + plt.ylim(0, 5e-5) + plt.xlabel("distance (m)") + plt.ylabel("resolution") + plt.legend() + + # resolutin to information + theta = pi/4 + res_45 = np.zeros(100) + info_45 = np.zeros(100) + for i in range(100): + res_45[i] = calcResLine(l, theta, 0, fovs[i]) + info_45[i] = calcShpericalSectorArea(fovs[i]) + fig3 = plt.figure() + plt.plot(fovs / pi * 180, res_45, label="Resolution") + plt.plot(fovs / pi * 180, info_45 * 1e-5, label="Visible Area") + plt.legend() + plt.ylim(0, 1e-5) + plt.xlabel("FoV (degrees)") + plt.ylabel("Scaled Value") + plt.show() diff --git a/blaser_ros/scripts/pub_cam_odom.py b/blaser_ros/scripts/pub_cam_odom.py new file mode 100644 index 0000000..121ec34 --- /dev/null +++ b/blaser_ros/scripts/pub_cam_odom.py @@ -0,0 +1,53 @@ +#!/usr/bin/env python +import rospy +import roslib +import tf +from nav_msgs.msg import Odometry +import sys +from sensor_msgs.msg import Image + +def im_cb(im): + listener.waitForTransform(frame1_name, world_frame_name, im.header.stamp, rospy.Duration(1.0)) + try: + (trans,rot) = listener.lookupTransform(frame1_name, world_frame_name, im.header.stamp) + except (tf.LookupException, tf.ConnectivityException, tf.ExtrapolationException) as e: + print(e) + return + print(im.header.stamp) + odom_msg = Odometry() + odom_msg.header.frame_id = "base" + odom_msg.header.stamp = im.header.stamp + odom_msg.pose.pose.position.x = trans[0] + odom_msg.pose.pose.position.y = trans[1] + odom_msg.pose.pose.position.z = trans[2] + odom_msg.pose.pose.orientation.x = rot[0] + odom_msg.pose.pose.orientation.y = rot[1] + odom_msg.pose.pose.orientation.z = rot[2] + odom_msg.pose.pose.orientation.w = rot[3] + + odom_pub.publish(odom_msg) + +frame1_name = '' +world_frame_name = '' +odom_topic = '' +camera_topic = '' +if len(sys.argv) != 5: + print("usage: python pub_cam_odom.py frame_name world_frame_name odom_topic camera_topic") + exit(0) + +frame1_name = sys.argv[1] +world_frame_name = sys.argv[2] +odom_topic = sys.argv[3] +camera_topic = sys.argv[4] + +rospy.init_node('tf2odom') + +listener = tf.TransformListener() + +odom_pub = rospy.Publisher(odom_topic, Odometry, queue_size = 20) + +listener.waitForTransform(frame1_name, world_frame_name, rospy.Time(), rospy.Duration(4.0)) + +rospy.Subscriber(camera_topic, Image, im_cb) + +rospy.spin() diff --git a/blaser_ros/scripts/static_tf_blaser_vio.py b/blaser_ros/scripts/static_tf_blaser_vio.py new file mode 100644 index 0000000..dcfbf41 --- /dev/null +++ b/blaser_ros/scripts/static_tf_blaser_vio.py @@ -0,0 +1,16 @@ +#!/usr/bin/env python +import rospy +import tf +import time + +if __name__ == '__main__': + rospy.init_node("static_tf_publisher") + br = tf.TransformBroadcaster() + while not rospy.is_shutdown(): + br.sendTransform((0,0,0), + tf.transformations.quaternion_from_euler(0, 0, 0), + rospy.Time.now(), + 'blaser_640', + 'camera') + + time.sleep(0.001) diff --git a/blaser_ros/scripts/vis_laser_calib_result.ipynb b/blaser_ros/scripts/vis_laser_calib_result.ipynb new file mode 100644 index 0000000..f555d8b --- /dev/null +++ b/blaser_ros/scripts/vis_laser_calib_result.ipynb @@ -0,0 +1,902 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "from matplotlib import pyplot as plt\n", + "import math\n", + "%matplotlib notebook\n" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "# read plane parameters and laser points\n", + "result_file = open('../calib_result.txt')\n", + "raw_data = result_file.readlines()\n", + "plane_params = np.fromstring(raw_data[1].strip(), dtype=float, sep=',')\n", + "pts = np.zeros((len(raw_data) - 3, 3))\n", + "for i in range(len(raw_data) - 3):\n", + " pts[i] = np.fromstring(raw_data[i + 3].strip(), dtype=float, sep=',')\n" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [], + "source": [ + "# generate plane\n", + "min_x = np.min(pts[:, 0])\n", + "max_x = np.max(pts[:, 0])\n", + "min_y = np.min(pts[:, 1])\n", + "max_y = np.max(pts[:, 1])\n", + "min_z = np.min(pts[:, 2])\n", + "max_z = np.max(pts[:, 2])\n", + "pl_xx, pl_yy = np.meshgrid(np.linspace(min_x - 0.1, max_x + 0.1),\n", + " np.linspace(min_y - 0.1, max_y + 0.1))\n", + "pl_z = (-plane_params[0] * pl_xx - plane_params[1] * pl_yy - plane_params[3]) / plane_params[2]" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [ + { + "data": { + "application/javascript": [ + "/* Put everything inside the global mpl namespace */\n", + "window.mpl = {};\n", + "\n", + "\n", + "mpl.get_websocket_type = function() {\n", + " if (typeof(WebSocket) !== 'undefined') {\n", + " return WebSocket;\n", + " } else if (typeof(MozWebSocket) !== 'undefined') {\n", + " return MozWebSocket;\n", + " } else {\n", + " alert('Your browser does not have WebSocket support. ' +\n", + " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", + " 'Firefox 4 and 5 are also supported but you ' +\n", + " 'have to enable WebSockets in about:config.');\n", + " };\n", + "}\n", + "\n", + "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", + " this.id = figure_id;\n", + "\n", + " this.ws = websocket;\n", + "\n", + " this.supports_binary = (this.ws.binaryType != undefined);\n", + "\n", + " if (!this.supports_binary) {\n", + " var warnings = document.getElementById(\"mpl-warnings\");\n", + " if (warnings) {\n", + " warnings.style.display = 'block';\n", + " warnings.textContent = (\n", + " \"This browser does not support binary websocket messages. \" +\n", + " \"Performance may be slow.\");\n", + " }\n", + " }\n", + "\n", + " this.imageObj = new Image();\n", + "\n", + " this.context = undefined;\n", + " this.message = undefined;\n", + " this.canvas = undefined;\n", + " this.rubberband_canvas = undefined;\n", + " this.rubberband_context = undefined;\n", + " this.format_dropdown = undefined;\n", + "\n", + " this.image_mode = 'full';\n", + "\n", + " this.root = $('
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