MYNT® EYE S SDK¶

PRODUCT¶

Product Description¶

MYNT® EYE S Series includes MYNT EYE S, MYNT EYE SE and MYNT EYE SC. The “Binocular + IMU” inertial navigation solution for MYNT® EYE S Series provides accurate six-axis complementary data for vSLAM applications and is more accurate and robust than other single solutions.

Combined with self-developed camera synchronization, auto exposure, and white balance control camera technology, MYNT® EYE S Series provides a CUDA-based GPU real-time acceleration solution that outputs high-precision, synchronized image sources to help reduce the difficulty of algorithm development and speed up the efficiency of algorithm research and development. At the same time, MYNT EYE S is equipped with a six-axis sensor (IMU) and an infrared active light (IR). Among them, six-axis sensor (IMU) can provide data complementation and correction for the research of visual positioning algorithm, suitable for algorithm research of visual inertial odometer (VIO), help improve positioning accuracy; infrared active light (IR) can help solve the problem of identifying indoor white walls and non-textured objects, and improve the recognition accuracy of image sources. The difference between MYNT EYE SE and MYNT EYE S is that MYNT EYE SE does not include IR and offers customers with lower cost hardware. MYNT EYE SC provides 8cm/12cm optional baseline solution, super wide angle 146°FOV, providing a wider depth recognition range and accuracy level, with color image sensor, upgraded brand new BMI088 six-axis IMU, IR active light, I2C time synchronization Chip, global shutter, etc., with resolutions up to 2560x800@30fps and accuracy is up to centimeters. In addition, MYNT EYE S Series also provides a rich SDK interface and VSLAM open source project support, which can help customers quickly integrate solutions, accelerate the product development process, and achieve rapid productization and implementation.

As a hardware product for research and development of stereo vision computing applications, MYNT® EYE S Series can be widely used in a field of visual positioning navigation (vSLAM), including visual real-time positioning navigation system of driverless vehicle and robots, visual positioning system of UAV, obstacle avoidance navigation system for driverless Vehicle, Augmented Reality (AR), Virtual Reality (VR), etc. At the same time, it can be used in a field of visual recognition, including Stereoscopic face recognition, three-dimensional object recognition, space motion tracking, three-dimensional gestures, and somatosensory recognition. And of course, you can use it for measurement which includes assisted driving system (ADAS), binocular volume calculation, industrial visual screening, etc. At present, MYNTAI has carried out service and cooperation with more than 500 domestic and foreign enterprise clients.

In order to ensure the quality of the output data of the camera products, we have calibrated the binocular and IMU. The product has passed various hardware stability tests, such as high- temperature and humidity continuous work and operation, low-temperature dynamic aging, high-temperature operation, low-temperature storage, whole-machine thermal shock, sinusoidal vibration and random vibration tests to ensure the stability and reliability of the product. In addition to the research and development of products and technologies, it can also be directly applied to mass production, accelerating the process from R&D to productization.

Product Surface¶

S1030 Size and Structure¶

Shell(mm)	PCBA board(mm)
165x31.5x29.6	149x24

Camera:please pay attention to protect the camera sensor lenses, to avoid imaging quality degradation.
Infrared structured-light transmitter and outlet: the infrared structured-light can effectively solve the problem associated with the visual positioning calculations of white wall non-textured object(For non-IR version, the outlet is reserved but there is no internal structured-light emitter).
USB Micro-B interface and set screw holes: during usage, plug in the USB Micro-B cable and secure it by fastening the set screws to avoid damage to the interface and to ensure stability in connection.
¼ inch standardized set screw hole: for fixing the stereo camera to tripods or other devices.

S2100 Size and Structure¶

Shell(mm)	PCBA board(mm)
125x47x40	100x15

Camera:please pay attention to protect the camera sensor lenses, to avoid imaging quality degradation.
USB Micro-B interface and set screw holes: during usage, plug in the USB Micro-B cable and secure it by fastening the set screws to avoid damage to the interface and to ensure stability in connection.

S2110 Size and Structure¶

Shell(mm)	PCBA board(mm)
125x47x40	100x15

Camera:please pay attention to protect the camera sensor lenses, to avoid imaging quality degradation.
USB Micro-B interface and set screw holes: during usage, plug in the USB Micro-B cable and secure it by fastening the set screws to avoid damage to the interface and to ensure stability in connection.

Product Specification¶

S1030-120/Mono Product Specification¶

Product Specification¶

Model	S1030-120/Mono
Size	165x31.5x31.23mm
Frame Rate	10/15/20/25/30/35/40/45/50/55/60FPS
Resolution	752480; 376240
Depth Resolution	Based on CPU/GPU Up to 752*480@60FPS
Pixel Size	6.0*6.0μm
Baseline	120.0mm
Visual Angle	D:146° H:122° V:76°
Focal Length	2.1mm
Filter	Dual Pass Filter
IR Support	No
IR detectable range	-
Color Mode	Monochrome
Depth Working Distance	0.8-5m+
Scanning Mode	Global Shutter
Power	1W@5V DC from USB
Synchronization Precision	<1ms (up to 0.05ms)
IMU Frequency	100/200/250/333/500Hz
Output data format	Raw data
Data transfer Interface	USB3.0
Weight	160g
UVC MODE	Yes

Software¶

Work Environment¶

Operating Temperature	10°C~50°C
Storage Temperature	-20°C~60°C
Humidity	10% to 90% non-condensing

Package¶

Package Contents

MYNT EYE x1 USB Micro-B Cable x1

Warranty¶

Product Warranty

12 Months Limited Manufacturer’s Warranty

Accuracy¶

Depth Distance Deviation

Less than 4%

S1030-IR-120/Mono Product Specification¶

Product Specification¶

Model	S1030-IR-120/Mono
Size	165x31.5x31.23mm
Frame Rate	10/15/20/25/30/35/40/45/50/55/60FPS
Resolution	752480; 376240
Depth Resolution	Based on CPU/GPU Up to 752*480@60FPS
Pixel Size	6.0*6.0μm
Baseline	120.0mm
Camera Lens	Replacable Standard M12
Visual Angle	D:146° H:122° V:76°
Focal Length	2.1mm
Filter	Dual Pass Filter
IR Support	Yes
IR detectable range	Up to 3m
Color Mode	Monochrome
Depth Working Distance	0.8-5m+
Scanning Mode	Global Shutter
Power	1~2.7W@5V DC from USB
Synchronization Precision	<1ms (up to 0.05ms)
IMU Frequency	100/200/250/333/500Hz
Output data format	Raw data
Data transfer Interface	USB3.0
Weight	184g
UVC MODE	Yes

Software¶

Work Environment¶

Operating Temperature	10°C~50°C
Storage Temperature	-20°C~60°C
Humidity	10% to 90% non-condensing

Package¶

Package Contents

MYNT EYE x1 USB Micro-B Cable x1

Warranty¶

Product Warranty

12 Months Limited Manufacturer’s Warranty

Accuracy¶

Depth Distance Deviation

Less than 4%

S2100-146/Color Product Specification¶

Product Specification¶

Model	S2100-146/Color
Size	PCB dimension:15x100mm Total dimension:125x47x26.6mm
Frame Rate	1280x400@10/20/30/60fps 2560x800@10/20/30fps
Resolution	1280x400; 2560x800
Depth Resolution	Based on CPU/GPU Up to 1280*400@60FPS
Pixel Size	3.0*3.0μm
Baseline	80.0mm
Visual Angle	D:141° H:124° V:87°
Focal Length	0.95mm
IR Support	No
Color Mode	Color
Depth Working Distance	0.26-3m+
Scanning Mode	Global Shutter
Power	1.1W@5V DC from USB
Synchronization Precision	<1ms (up to 0.02ms)
IMU Frequency	200Hz
Output data format	YUYV
Data transfer Interface	USB3.0
Time Sync interface	DF50A
Weight	62g
UVC MODE	Yes

Software¶

Support system	Windows 10、Ubuntu 14.04/16.04/18.04、ROS indigo/kinetic/melodic、Android 7.0+
SDK	http://www.myntai.com/dev/mynteye
Support	ORB_SLAM2、OKVIS、Vins-Mono、Vins-Fusion、VIORB

Work Environment¶

Operating Temperature	-15°C~55°C
Storage Temperature	-20°C~75°C
Humidity	0% to 95% non-condensing

Package¶

Package Contents

MYNT EYE x1 USB Micro-B Cable x1

Warranty¶

Product Warranty

12 Months Limited Manufacturer’s Warranty

Accuracy¶

Depth Distance Deviation

Less than 4%

S2110-95/Color Product Specification¶

Product Specification¶

Model	S2110-95/Color
Size	PCB dimension:17.74x100mm Total dimension:125x47x26.6mm
Frame Rate	1280x400@10/20/30/60fps 2560x800@10/20/30fps
Resolution	1280x400; 2560x800
Depth Resolution	Based on CPU/GPU Up to 1280*400@60FPS
Pixel Size	3.0*3.0μm
Baseline	80.0mm
Visual Angle	D:112° H:95° V:50°
Focal Length	2.63mm
IR Support	No
Color Mode	Color
Depth Working Distance	0.60-7m+
Scanning Mode	Global Shutter
Power	1.1W@5V DC from USB
Synchronization Precision	<1ms (up to 0.02ms)
IMU Frequency	200Hz
Output data format	YUYV
Data transfer Interface	USB3.0
Time Sync interface	DF50A
Weight	100.8g
UVC MODE	Yes

Software¶

Support system	Windows 10、Ubuntu 14.04/16.04/18.04、ROS indigo/kinetic/melodic、Android 7.0+
SDK	http://www.myntai.com/dev/mynteye
Support	ORB_SLAM2、OKVIS、Vins-Mono、Vins-Fusion、VIORB

Work Environment¶

Operating Temperature	-15°C~55°C
Storage Temperature	-20°C~75°C
Humidity	0% to 95% non-condensing

Package¶

Package Contents

MYNT EYE x1 USB Micro-B Cable x1

Warranty¶

Product Warranty

12 Months Limited Manufacturer’s Warranty

Accuracy¶

Depth Distance Deviation

Less than 4%

IMU Coordinate System¶

S1030 Coordinate System¶

IMU coordinate system is right-handed,the axis directions are as follows:

S2100 Coordinate System¶

IMU coordinate system is right-handed,the axis directions are as follows:

S2110 Coordinate System¶

IMU coordinate system is right-handed,the axis directions are as follows:

SDK¶

SDK Description¶

Supported Platforms¶

SDK is built on CMake and can be used cross multiple platforms such as “Linux, Windows, etc. We provides two installation: Download and install, and Compile and install from source code.

These are the platforms that can be used:

Windows 10
Ubuntu 18.04.1 / 16.04.6 / 14.04.5
Jetson TX1/TX2 / Xavier
firefly RK3399

Warning

Due to the requirement of hardware transmission rate, please use the USB 3 interface. In addition, virtual machines have USB driver compatibility problems, thus they are not recommended.

OpenCV Description¶

SDK provides a three-tier interface with OpenCV dependencies:

api, upper interface, with OpenCV dependencies
device, interlayer interface, without OpenCV dependencies
uvc, bottom interface, without OpenCV dependencies

If you don’t want to use OpenCV, edit <sdk>/cmake/Option.cmake , set WITH_API to OFF. This will stop the compilation of the interface api:

option(WITH_API "Build with API layer, need OpenCV" ON)

For samples for the interface device, please refer to device/camera.cc .

SDK Installation¶

Ubuntu PPA Installation¶

Ubuntu 14.04	Ubuntu 16.04	Ubuntu 18.04

x64 PPA installation¶

$ sudo add-apt-repository ppa:slightech/mynt-eye-s-sdk
$ sudo apt-get update
$ sudo apt-get install mynt-eye-s-sdk

armv8 PPA installation¶

$ sudo add-apt-repository ppa:slightech/mynt-eye-s-sdk-arm
$ sudo apt-get update
$ sudo apt-get install mynt-eye-s-sdk

Run samples¶

Tip

samples path: /opt/mynt-eye-s-sdk/samples

$ cd /opt/mynt-eye-s-sdk/samples
$ ./camera_with_junior_device_api

Ubuntu Source Installation¶

Ubuntu 14.04	Ubuntu 16.04	Ubuntu 18.04

Tip

If you used any other Linux distributions without apt-get package manager, you need to install required packages manaully instead of using make init.

Linux	How to install required packages
Debian based	sudo apt-get install build-essential cmake git libv4l-dev
Red Hat based	sudo yum install make gcc gcc-c++ kernel-devel cmake git libv4l-devel
Arch Linux	sudo pacman -S base-devel cmake git v4l-utils

Getting Source Code¶

sudo apt-get install git
git clone https://github.com/slightech/MYNT-EYE-S-SDK.git

Required Packages¶

cd <sdk>
make init

OpenCV

Tip

To build and install Opencv(Not support 4.0+), Please refer to Installation in Linux . Alternatively, refer to the command below:

[compiler] sudo apt-get install build-essential
[required] sudo apt-get install cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev
[optional] sudo apt-get install python-dev python-numpy libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev libjasper-dev libdc1394-22-dev

$ git clone https://github.com/opencv/opencv.git
$ cd opencv/
$ git checkout tags/3.4.1

$ mkdir _build
$ cd _build/

$ cmake \
-DCMAKE_BUILD_TYPE=RELEASE \
-DCMAKE_INSTALL_PREFIX=/usr/local \
\
-DWITH_CUDA=OFF \
\
-DBUILD_DOCS=OFF \
-DBUILD_EXAMPLES=OFF \
-DBUILD_TESTS=OFF \
-DBUILD_PERF_TESTS=OFF \
..

$ make -j4
$ sudo make install

Building code¶

Tip

If opencv is installed in custom directory or if you want to specify a version, you should set the path before building:

# OpenCV_DIR is the directory where your OpenCVConfig.cmake exists
export OpenCV_DIR=~/opencv

Otherwise, CMake will prompt cannot find OpenCV. If you need sdk without OpenCV, please read OpenCV Description .

Build and install:

cd <sdk>
make install

Finally, sdk will install in /usr/local by default.

Building samples¶

cd <sdk>
make samples

Run samples:

./samples/_output/bin/api/camera_a

Tutorial samples, please read SDK Project Demos and SDK Control Samples .

Building tools¶

cd <sdk>
make tools

Installation requirement:

cd <sdk>/tools/
sudo pip install -r requirements.txt

The usage of tools and scripts will be introduced later.

Conclusion¶

If your project will use SDK, you can refer to the settings in samples/CMakeLists.txt for CMake. Alternatively, import the head file and dynamic library in the installation directory.

Windows EXE Installation¶

Windows 10

Download and install SDK¶

Tip

Download here: mynteye-s-x.x.x-win-x64-opencv-3.4.3.exe Google Drive Baidu Pan(key:rj4k) .

After you install the win pack of SDK, there will be a shortcut to the SDK root directory on your desktop.

Goto the <SDK_ROOT_DIR>\\bin\\samples\\tutorials directory and click get_stereo.exe to run.

Generate samples project¶

First, you should install Visual Studio 2017 and CMake .

Second, goto the <SDK_ROOT_DIR>\\samples directory and click generate.bat to generate project.

Tip

Right click sample and select Set as StartUp Project，then launch with Release x64 mode.

The tutorials of samples are here: https://slightech.github.io/MYNT-EYE-S-SDK-Guide/src/data/contents.html.

Start using SDK with Visual Studio 2017¶

Goto the <SDK_ROOT_DIR>\\projects\\vs2017, see the README.md.

Windows Source Installation¶

Windows 10

Tip

Windows does not provide Visual Studio *.sln file directly and requires CMake to build. Firstly, CMake can be used across multiple platforms, it is easy to configure and can be maintained in a sustainable way. Secondly, the third-party codes (Glog, OpenCV) are built using CMake.

Tip

There is currently no binary installer available, which requires you to compile from source. It is also the process of configuring the development environment.

Prerequisites¶

CMake (provide build）¶

CMake，used to build and compile (necessary).
Git， used to get code (optional).
Doxygen， used to generate documents (optional).

After you install the above tools, confirm that you can run this command in CMD (Command Prompt):

>cmake --version
cmake version 3.10.1

>git --version
git version 2.11.1.windows.1

>doxygen --version
1.8.13

Visual Studio (provide compilation)¶

After installing Visual Studio, confirm that the following command can run in the Visual Studio Command Prompt:

>cl
Microsoft (R) C/C++ Optimizing Compiler Version 19.14.26429.4 for x86

>msbuild
Microsoft (R) 生成引擎版本 15.7.179.6572

Tip

Visual Studio Command Prompt can be opened from the Start menu,

You can also open it from the Visual Studio Tools menu.

However, if you do not have the Visual Studio 2015 Tools menu, you can add one yourself.

Open Tools’s External Tools… and Add the following:

Field	Value
Title	Visual Studio Command Prompt
Command	`C:\Windows\System32\cmd.exe`
Arguments	`/k "C:\Program Files (x86)\Microsoft Visual Studio 14.0\Common7\Tools\VsDevCmd.bat"`
Initial Directory	`$(SolutionDir)`

In Visual Studio command Prompt, you can use the compile command cl link lib msbuild, etc.(need finish MSYS2``and ``Getting Source Code steps first)

MSYS2 (provide Linux command)¶

MSYS2
- mirror
- pacman

After installation, verify that the following path has been added to the system environment variable PATH:

C:\msys64\usr\bin

Then, open MSYS2 MSYS, perform the update and install make:

$ pacman -Syu
$ pacman -S make

Finally, the CMD (Command Prompt) can run the following command:

>make --version
GNU Make 4.2.1

Getting Source Code¶

git clone https://github.com/slightech/MYNT-EYE-S-SDK.git

Required Packages¶

>cd <sdk>
>make init
Make init
Init deps
Install cmd: pacman -S
Install deps: git clang-format
pacman -S clang-format (not exists)
error: target not found: clang-format
pip install --upgrade autopep8 cpplint pylint requests
...
Init git hooks
ERROR: clang-format-diff is not installed!
Expect cmake version >= 3.0
cmake version 3.10.1

OpenCV

Tip

The official OpenCV provides the exe for installation. If you want to compile from the source code, see the Official document Installation in Windows . or refer to the following command:

>git clone https://github.com/opencv/opencv.git
>cd opencv
>git checkout tags/3.4.1

>cd opencv
>mkdir _build
>cd _build

>cmake ^
-D CMAKE_BUILD_TYPE=RELEASE ^
-D CMAKE_INSTALL_PREFIX=C:/opencv ^
-D WITH_CUDA=OFF ^
-D BUILD_DOCS=OFF ^
-D BUILD_EXAMPLES=OFF ^
-D BUILD_TESTS=OFF ^
-D BUILD_PERF_TESTS=OFF ^
-G "Visual Studio 15 2017 Win64" ^
..

>msbuild ALL_BUILD.vcxproj /property:Configuration=Release
>msbuild INSTALL.vcxproj /property:Configuration=Release

Building Code¶

Tip

If OpenCV is installed in a custom directory or wants to specify a version, you can set the path as follows before compiling:

# OpenCV_DIR is hte path where OpenCVConfig.cmake in
set OpenCV_DIR=C:\opencv

Otherwise, CMake will prompt that OpenCV could not be found. If you don’t want to rely on OpenCV, read OpenCV Description .

Build and install:

cd <sdk>
make install

Finally, the SDK will install in <sdk>/_install by default.

Building samples¶

cd <sdk>
make samples

Run samples:

.\samples\_output\bin\api\camera_a.bat

For tutorial samples, please read SDK Project Demos and SDK Control Samples .

Tip

All compiled sample programs exe will have a corresponding bat. bat will temporarily set system environment variables and then run exe. So it is recommended to run bat.

If you run``exe`` directly, it may prompt that cannot find dll. Then you should add <sdk>\\_install\\bin %OPENCV_DIR%\\bin to PATH in system environment variable.

How to set the environment variable for OpenCV, refer to the official document Set the OpenCV environment variable and add it to the systems path .

Building tools¶

cd <sdk>
make tools

The usage of tools and scripts will be introduced later.

Tip

The script is based on Python. You need to install Python and its package management tool pip first, and then install the dependencies as follows:

cd <sdk>\tools
pip install -r requirements.txt

Note: Python is also in MSYS2, but fail install Matplotlib in test.

Conclusion¶

If your project will use SDK, you can refer to the settings in samples/CMakeLists.txt for CMake. Or just import the head file and dynamic library in the installation directory.

ROS Wrapper Installation¶

ROS Kinetic	ROS Indigo

Prepare Environment¶

ROS

ROS Melodic (Ubuntu 18.04)¶

sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu $(lsb_release -sc) main" > /etc/apt/sources.list.d/ros-latest.list'
sudo apt-key adv --keyserver hkp://ha.pool.sks-keyservers.net:80 --recv-key 421C365BD9FF1F717815A3895523BAEEB01FA116
sudo apt update
sudo apt install ros-melodic-desktop-full
sudo rosdep init
rosdep update

ROS Kinetic (Ubuntu 16.04)¶

wget https://raw.githubusercontent.com/oroca/oroca-ros-pkg/master/ros_install.sh && \
chmod 755 ./ros_install.sh && bash ./ros_install.sh catkin_ws kinetic

ROS Indigo (Ubuntu 14.04)¶

wget https://raw.githubusercontent.com/oroca/oroca-ros-pkg/master/ros_install.sh && \
chmod 755 ./ros_install.sh && bash ./ros_install.sh catkin_ws indigo

Compiling Code¶

cd <sdk>
make ros

Running node¶

source wrappers/ros/devel/setup.bash
roslaunch mynt_eye_ros_wrapper mynteye.launch  # this node doesn't have preview

Run the node, and preview by RViz:

source wrappers/ros/devel/setup.bash
roslaunch mynt_eye_ros_wrapper display.launch

Testing Services¶

Run the node as follows, provide device information getting service, see follows:

$ source wrappers/ros/devel/setup.bash
$ rosrun mynt_eye_ros_wrapper get_device_info.py
LENS_TYPE: 0000
SPEC_VERSION: 1.0
NOMINAL_BASELINE: 120
HARDWARE_VERSION: 2.0
IMU_TYPE: 0000
SERIAL_NUMBER: 0610243700090720
FIRMWARE_VERSION: 2.0
DEVICE_NAME: MYNT-EYE-S1000

Common issues - ROS Indigo¶

Cannot find `libopencv` while `make ros`¶

make[3]: *** No rule to make target `/usr/lib/x86_64-linux-gnu/libopencv_videostab.so.2.4.8', needed by `/home/john/Workspace/MYNT-EYE-S-SDK/wrappers/ros/devel/lib/libmynteye_wrapper.so'.  Stop.

Solution 1) Install OpenCV 2:

sudo apt-get update
sudo apt-get install libcv-dev

Solution 2) Install OpenCV 3 & re-compiled cv_bridge:

sudo apt-get install ros-indigo-opencv3

git clone https://github.com/ros-perception/vision_opencv.git
mv vision_opencv/cv_bridge/ MYNT-EYE-S-SDK/wrappers/ros/src/

Then run make ros again

Conclusion¶

About more details, check the How to use ROS .

SDK Data Samples¶

Get Device Information¶

Use GetInfo() function to get various current information values.

Reference code snippet:

auto &&api = API::Create(argc, argv);

LOG(INFO) << "Device name: " << api->GetInfo(Info::DEVICE_NAME);
LOG(INFO) << "Serial number: " << api->GetInfo(Info::SERIAL_NUMBER);
LOG(INFO) << "Firmware version: " << api->GetInfo(Info::FIRMWARE_VERSION);
LOG(INFO) << "Hardware version: " << api->GetInfo(Info::HARDWARE_VERSION);
LOG(INFO) << "Spec version: " << api->GetInfo(Info::SPEC_VERSION);
LOG(INFO) << "Lens type: " << api->GetInfo(Info::LENS_TYPE);
LOG(INFO) << "IMU type: " << api->GetInfo(Info::IMU_TYPE);
LOG(INFO) << "Nominal baseline: " << api->GetInfo(Info::NOMINAL_BASELINE);

Reference result on Linux:

$ ./samples/_output/bin/get_device_info
I0503 16:40:21.109391 32106 utils.cc:13] Detecting MYNT EYE devices
I0503 16:40:21.604116 32106 utils.cc:20] MYNT EYE devices:
I0503 16:40:21.604127 32106 utils.cc:24]   index: 0, name: MYNT-EYE-S1000
I0503 16:40:21.604142 32106 utils.cc:30] Only one MYNT EYE device, select index: 0
I0503 16:40:21.615054 32106 get_device_info.cc:10] Device name: MYNT-EYE-S1000
I0503 16:40:21.615113 32106 get_device_info.cc:11] Serial number: 0610243700090720
I0503 16:40:21.615129 32106 get_device_info.cc:12] Firmware version: 2.0
I0503 16:40:21.615139 32106 get_device_info.cc:13] Hardware version: 2.0
I0503 16:40:21.615146 32106 get_device_info.cc:14] Spec version: 1.0
I0503 16:40:21.615155 32106 get_device_info.cc:15] Lens type: 0000
I0503 16:40:21.615164 32106 get_device_info.cc:16] IMU type: 0000
I0503 16:40:21.615171 32106 get_device_info.cc:17] Nominal baseline: 120

Complete code examples, see get_device_info.cc .

Get Image Calibration Parameters¶

Use GetIntrinsics() & GetExtrinsics() to get image calibration parameters.

Tip

The detailed meaning of parameters can reference the files in tools/writer/config , of these the image calibration parameters of S21XX are in tools/writer/config/S21XX the image calibration parameters of S1030 are in tools/writer/config/S1030

Note

Camera Intrinsics/Extrinsics, please ref to: ros CameraInfo.

Reference code snippet:

auto &&api = API::Create(argc, argv);

LOG(INFO) << "Intrinsics left: {" << *api->GetIntrinsicsBase(Stream::LEFT)
          << "}";
LOG(INFO) << "Intrinsics right: {" << *api->GetIntrinsicsBase(Stream::RIGHT)
          << "}";
LOG(INFO) << "Extrinsics right to left: {"
          << api->GetExtrinsics(Stream::RIGHT, Stream::LEFT) << "}";

Reference result on Linux:

$ ./samples/_output/bin/get_img_params
I/utils.cc:48 MYNT EYE devices:
I/utils.cc:51   index: 0, name: MYNT-EYE-S1030, sn: 4B4C192400090712, firmware: 2.4
I/utils.cc:60 Only one MYNT EYE device, select index: 0
I/synthetic.cc:59 camera calib model: kannala_brandt
I/utils.cc:93 MYNT EYE requests:
I/utils.cc:96   index: 0, request: width: 752, height: 480, format: Format::YUYV, fps: 60
I/utils.cc:96   index: 1, request: width: 376, height: 240, format: Format::YUYV, fps: 60
I/utils.cc:107 There are 2 stream requests, select index:
0
I/get_img_params.cc:44 Intrinsics left: {equidistant, width: 752, height: 480, k2: 0.00986113697985857, k3: -0.11937208025856659, k4: 0.19092250072175385, k5: -0.10168315832257743, mu: 356.41566867259672335, mv: 356.31078130432149464, u0: 375.76739787805968263, v0: 246.20025492033516912}
I/get_img_params.cc:45 Intrinsics right: {equidistant, width: 752, height: 480, k2: -0.02246312175999786, k3: 0.01303393297719630, k4: -0.01735983686524734, k5: 0.00675132874903371, mu: 357.96820061652590539, mv: 357.76889287108474491, u0: 397.09281703352422710, v0: 258.93978588846073308}
I/get_img_params.cc:46 Extrinsics right to left: {rotation: [0.99997489222742053, 0.00041828202737396, -0.00707389248605010, -0.00042920419615213, 0.99999871813992847, -0.00154256353448567, 0.00707323819170721, 0.00154556094848940, 0.99997378992793495], translation: [-120.01607586757218371, 0.34488126401045993, 0.64552185106557303]}
ROSMsgInfoPair:
left:
width: 752, height: 480
distortion_model: KANNALA_BRANDT
D: 0.00986114,-0.119372,0.190923,-0.101683,0,
K: 356.416,0,375.767,0,356.311,246.2,0,0,1,
R: 0.999919,-0.00246361,-0.0124477,0.00245407,0.999997,-0.000781093,0.0124496,0.000750482,0.999922,
P: 357.04,0,511.114,0,0,357.04,311.965,0,0,0,1,0,

right:
width: 752, height: 480
distortion_model: KANNALA_BRANDT
D: -0.0224631,0.0130339,-0.0173598,0.00675133,0,
K: 357.968,0,397.093,0,357.769,258.94,0,0,1,
R: 0.999981,-0.00287357,-0.00537853,0.00287782,0.999996,0.000781842,0.00537626,-0.000797306,0.999985,
P: 357.04,0,511.114,-42851.3,0,357.04,311.965,0,0,0,1,0,

Complete code examples, see get_img_params.cc .

Get IMU Calibration Parameters¶

Use GetMotionIntrinsics() & GetMotionExtrinsics() to get current IMU calibration parameters.

Reference commands:

auto &&api = API::Create(argc, argv);

LOG(INFO) << "Motion intrinsics: {" << api->GetMotionIntrinsics() << "}";
LOG(INFO) << "Motion extrinsics left to imu: {"
          << api->GetMotionExtrinsics(Stream::LEFT) << "}";

Complete code examples, see get_imu_params.cc .

Get Original Binocular Image¶

Use Start() or Stop() , to start or stop data capturing. If you only need the image data, use Source::VIDEO_STREAMING .

When data capturing starts, call WaitForStreams() function. Once data capturing begins, use GetStreamData() to get your data.

Reference commands:

auto &&api = API::Create(argc, argv);

api->Start(Source::VIDEO_STREAMING);

cv::namedWindow("frame");

while (true) {
  api->WaitForStreams();

  auto &&left_data = api->GetStreamData(Stream::LEFT);
  auto &&right_data = api->GetStreamData(Stream::RIGHT);

  cv::Mat img;
  cv::hconcat(left_data.frame, right_data.frame, img);
  cv::imshow("frame", img);

  char key = static_cast<char>(cv::waitKey(1));
  if (key == 27 || key == 'q' || key == 'Q') {  // ESC/Q
    break;
  }
}

api->Stop(Source::VIDEO_STREAMING);

The above code uses OpenCV to display the image. When the display window is selected, pressing ESC/Q will end the program.

Complete code examples, see get_stereo.cc .

Get Stereo Camera Correction Image¶

The GetStreamData() API provided can only get the raw data of the hardware, for example, the stereo camera raw image.

The stereo camera correction image belongs to the upper layer of synthetic data. For such data, you need to enable EnableStreamData() before you can get GetStreamData().

In addition, WaitForStreams() waits for the key of the raw data. At the beginning when the synthetic data may still being processed, the value taken out will be null, so it needs to check not empty.

Tip

If you want the synthetic data once it is generated, see get_from_callbacks.

Reference code snippet:

auto &&api = API::Create(argc, argv);

api->EnableStreamData(Stream::LEFT_RECTIFIED);
api->EnableStreamData(Stream::RIGHT_RECTIFIED);

api->Start(Source::VIDEO_STREAMING);

cv::namedWindow("frame");

while (true) {
  api->WaitForStreams();

  auto &&left_data = api->GetStreamData(Stream::LEFT_RECTIFIED);
  auto &&right_data = api->GetStreamData(Stream::RIGHT_RECTIFIED);

  if (!left_data.frame.empty() && !right_data.frame.empty()) {
    cv::Mat img;
    cv::hconcat(left_data.frame, right_data.frame, img);
    cv::imshow("frame", img);
  }

  char key = static_cast<char>(cv::waitKey(1));
  if (key == 27 || key == 'q' || key == 'Q') {  // ESC/Q
    break;
  }
}

api->Stop(Source::VIDEO_STREAMING);

OpenCV is used to display the image above. Select the display window, press ESC/Q to exit the program.

Complete code examples, see get_stereo_rectified.cc .

Get Disparity Image¶

Disparity image belongs to the upper layer of synthetic data. You need to start the EnableStreamData() beforehand, to get it through GetStreamData(). In addition, it should be check not be empty before use.

For detailed process description, please see get_stereo get_stereo_rectified .

It is recommended to use plugin to calculate depth: the depth map will be better with a higher frame rate. Please see get_with_plugin .

Tip

The SetDisparityComputingMethodType method is used to change disparity computing method. Currently, BM and SGBM are available.

Reference code snippet:

auto &&api = API::Create(argc, argv);

// api->EnableStreamData(Stream::DISPARITY);
api->EnableStreamData(Stream::DISPARITY_NORMALIZED);

api->SetDisparityComputingMethodType(DisparityComputingMethod::BM);

api->Start(Source::VIDEO_STREAMING);

cv::namedWindow("frame");
// cv::namedWindow("disparity");
cv::namedWindow("disparity_normalized");

while (true) {
  api->WaitForStreams();

  auto &&left_data = api->GetStreamData(Stream::LEFT);
  auto &&right_data = api->GetStreamData(Stream::RIGHT);

  cv::Mat img;
  cv::hconcat(left_data.frame, right_data.frame, img);
  cv::imshow("frame", img);

  // auto &&disp_data = api->GetStreamData(Stream::DISPARITY);
  // if (!disp_data.frame.empty()) {
  //   cv::imshow("disparity", disp_data.frame);
  // }

  auto &&disp_norm_data = api->GetStreamData(Stream::DISPARITY_NORMALIZED);
  if (!disp_norm_data.frame.empty()) {
    cv::imshow("disparity_normalized", disp_norm_data.frame);  // CV_8UC1
  }

  char key = static_cast<char>(cv::waitKey(1));
  if (key == 27 || key == 'q' || key == 'Q') {  // ESC/Q
    break;
  }
}

api->Stop(Source::VIDEO_STREAMING);

The above code uses OpenCV to display the image. Select the display window, press ESC/Q to exit in the program.

Complete code examples, see get_disparity.cc .

Get Depth Image¶

Depth images belongs to the upper layer of synthetic data. You need to start the EnableStreamData() beforehand, to get it through GetStreamData(). The depth image type is CV_16UC1. In addition, it should be check not be empty before use.

For detailed process description, please see get_stereo get_stereo_rectified.

In addition, it is recommended to use plugins to calculate depth: Depth images work better and operate faster. Please refer to get_with_plugin.

Reference code snippet:

auto &&api = API::Create(argc, argv);

api->EnableStreamData(Stream::DEPTH);

api->Start(Source::VIDEO_STREAMING);

cv::namedWindow("frame");
cv::namedWindow("depth");

while (true) {
  api->WaitForStreams();

  auto &&left_data = api->GetStreamData(Stream::LEFT);
  auto &&right_data = api->GetStreamData(Stream::RIGHT);

  cv::Mat img;
  cv::hconcat(left_data.frame, right_data.frame, img);
  cv::imshow("frame", img);

  auto &&depth_data = api->GetStreamData(Stream::DEPTH);
  if (!depth_data.frame.empty()) {
    cv::imshow("depth", depth_data.frame);  // CV_16UC1
  }

  char key = static_cast<char>(cv::waitKey(1));
  if (key == 27 || key == 'q' || key == 'Q') {  // ESC/Q
    break;
  }
}

api->Stop(Source::VIDEO_STREAMING);

The above code uses OpenCV to display the image. When the display window is selected, pressing ESC/Q will end the program.

Complete code examples, see get_depth.cc .

Preview the value of a region of the depth image, see get_depth_with_region.cc .

Get Point Image¶

Point images belongs to upper layer of synthetic data. To get this kind of data through GetStreamData(), you need to start the EnableStreamData() beforehand. It should be check not empty before use.

For detail process description, please see get_stereo get_stereo_rectified .

Sample code snippet:

auto &&api = API::Create(argc, argv);

api->EnableStreamData(Stream::POINTS);

api->Start(Source::VIDEO_STREAMING);

cv::namedWindow("frame");
PCViewer pcviewer;

while (true) {
  api->WaitForStreams();

  auto &&left_data = api->GetStreamData(Stream::LEFT);
  auto &&right_data = api->GetStreamData(Stream::RIGHT);

  cv::Mat img;
  cv::hconcat(left_data.frame, right_data.frame, img);
  cv::imshow("frame", img);

  auto &&points_data = api->GetStreamData(Stream::POINTS);
  if (!points_data.frame.empty()) {
    pcviewer.Update(points_data.frame);
  }

  char key = static_cast<char>(cv::waitKey(1));
  if (key == 27 || key == 'q' || key == 'Q') {  // ESC/Q
    break;
  }
  if (pcviewer.WasStopped()) {
    break;
  }
}

api->Stop(Source::VIDEO_STREAMING);

PCL is used to display point images above. Program will close when point image window is closed.

Complete code examples, see get_depth_and_points.cc .

Attention

Sample code only compiles when PCL is ready. If your PCL was installed in a different directory, please set CMAKE_PREFIX_PATH in CMakeLists.txt to the path of PCLConfig.cmake . You can find CMAKE_PREFIX_PATH near find_package(PCL) .

Get IMU Data¶

The API offers Start() / Stop() function to start/stop capturing data. You can set the argument to``Source::MOTION_TRACKING`` to capture IMU data only, or set it to Source::ALL to capture both image and IMU data.

During capturing data, you need EnableMotionDatas() to enable caching in order to get IMU data from GetMotionDatas() . Otherwise, IMU data is only available through the callback interface, see get_from_callbacks .

Sample code snippet:

auto &&api = API::Create(argc, argv);

// Enable this will cache the motion datas until you get them.
api->EnableMotionDatas();

api->Start(Source::ALL);

CVPainter painter;

cv::namedWindow("frame");

while (true) {
  api->WaitForStreams();

  auto &&left_data = api->GetStreamData(Stream::LEFT);
  auto &&right_data = api->GetStreamData(Stream::RIGHT);

  cv::Mat img;
  cv::hconcat(left_data.frame, right_data.frame, img);

  auto &&motion_datas = api->GetMotionDatas();
  /*
  for (auto &&data : motion_datas) {
    LOG(INFO) << "Imu frame_id: " << data.imu->frame_id
              << ", timestamp: " << data.imu->timestamp
              << ", accel_x: " << data.imu->accel[0]
              << ", accel_y: " << data.imu->accel[1]
              << ", accel_z: " << data.imu->accel[2]
              << ", gyro_x: " << data.imu->gyro[0]
              << ", gyro_y: " << data.imu->gyro[1]
              << ", gyro_z: " << data.imu->gyro[2]
              << ", temperature: " << data.imu->temperature;
  }
  */

  painter.DrawImgData(img, *left_data.img);
  static std::vector<api::MotionData> motion_datas_s = motion_datas;

  if (!motion_datas.empty() && motion_datas.size() > 0) {
    motion_datas_s = motion_datas;
  }
  if (!motion_datas_s.empty() && motion_datas_s.size() > 0) {
    painter.DrawImuData(img, *motion_datas_s[0].imu);
  }

  cv::imshow("frame", img);

  char key = static_cast<char>(cv::waitKey(1));
  if (key == 27 || key == 'q' || key == 'Q') {  // ESC/Q
    break;
  }
}

api->Stop(Source::ALL);

OpenCV is used to display image and data. When window is selected, press ESC/Q to exit program.

Complete code examples, see get_imu.cc .

Get IMU Data With Timestamp Correspondence¶

If wanna get image with timestamp in the middle of IMU datas, you could call EnableTimestampCorrespondence()` to enable this feature.

Reference code snippet:

auto &&api = API::Create(argc, argv);

// Enable motion datas with timestamp correspondence of some stream
api->EnableTimestampCorrespondence(Stream::LEFT);

api->Start(Source::ALL);

cv::namedWindow("frame");

while (true) {
  api->WaitForStreams();

  auto &&left_data = api->GetStreamData(Stream::LEFT);
  auto &&right_data = api->GetStreamData(Stream::RIGHT);

  auto img_stamp = left_data.img->timestamp;
  LOG(INFO) << "Img timestamp: " << img_stamp
      << ", diff_prev=" << (img_stamp - prev_img_stamp);
  prev_img_stamp = img_stamp;

  cv::Mat img;
  cv::hconcat(left_data.frame, right_data.frame, img);

  auto &&motion_datas = api->GetMotionDatas();
  LOG(INFO) << "Imu count: " << motion_datas.size();
  for (auto &&data : motion_datas) {
    auto imu_stamp = data.imu->timestamp;
    LOG(INFO) << "Imu timestamp: " << imu_stamp
        << ", diff_prev=" << (imu_stamp - prev_imu_stamp)
        << ", diff_img=" << (1.f + imu_stamp - img_stamp);
    prev_imu_stamp = imu_stamp;
  }
  LOG(INFO);

  cv::imshow("frame", img);

  char key = static_cast<char>(cv::waitKey(1));
  if (key == 27 || key == 'q' || key == 'Q') {  // ESC/Q
    break;
  }
}

api->Stop(Source::ALL);

Reference result on Linux:

$ ./samples/_output/bin/get_imu_correspondence
I/utils.cc:30 Detecting MYNT EYE devices
I/utils.cc:40 MYNT EYE devices:
I/utils.cc:43   index: 0, name: MYNT-EYE-S1030, sn: 0281351000090807
I/utils.cc:51 Only one MYNT EYE device, select index: 0
I/synthetic.cc:126 camera calib model: kannala_brandt
I/utils.cc:79 MYNT EYE devices:
I/utils.cc:82   index: 0, request: width: 752, height: 480, format: Format::YUYV, fps: 60
I/utils.cc:87 Only one stream request, select index: 0
I/get_imu_correspondence.cc:50 Img timestamp: 171323050, diff_prev=39990
I/get_imu_correspondence.cc:58 Imu count: 13
I/get_imu_correspondence.cc:61 Imu timestamp: 171318710, diff_prev=171318710, diff_img=-4352
I/get_imu_correspondence.cc:61 Imu timestamp: 171320730, diff_prev=2020, diff_img=-2320
I/get_imu_correspondence.cc:61 Imu timestamp: 171322750, diff_prev=2020, diff_img=-304
I/get_imu_correspondence.cc:61 Imu timestamp: 171324770, diff_prev=2020, diff_img=1712
I/get_imu_correspondence.cc:61 Imu timestamp: 171326790, diff_prev=2020, diff_img=3728
I/get_imu_correspondence.cc:61 Imu timestamp: 171328800, diff_prev=2010, diff_img=5744
I/get_imu_correspondence.cc:61 Imu timestamp: 171330810, diff_prev=2010, diff_img=7760
I/get_imu_correspondence.cc:61 Imu timestamp: 171332840, diff_prev=2030, diff_img=9776
I/get_imu_correspondence.cc:61 Imu timestamp: 171334860, diff_prev=2020, diff_img=11808
I/get_imu_correspondence.cc:61 Imu timestamp: 171336880, diff_prev=2020, diff_img=13824
I/get_imu_correspondence.cc:61 Imu timestamp: 171338900, diff_prev=2020, diff_img=15840
I/get_imu_correspondence.cc:61 Imu timestamp: 171340920, diff_prev=2020, diff_img=17872
I/get_imu_correspondence.cc:61 Imu timestamp: 171342930, diff_prev=2010, diff_img=19872
I/get_imu_correspondence.cc:66
I/get_imu_correspondence.cc:50 Img timestamp: 171403040, diff_prev=79990
I/get_imu_correspondence.cc:58 Imu count: 20
I/get_imu_correspondence.cc:61 Imu timestamp: 171383310, diff_prev=40380, diff_img=-19728
I/get_imu_correspondence.cc:61 Imu timestamp: 171385330, diff_prev=2020, diff_img=-17712
I/get_imu_correspondence.cc:61 Imu timestamp: 171387350, diff_prev=2020, diff_img=-15696
I/get_imu_correspondence.cc:61 Imu timestamp: 171389370, diff_prev=2020, diff_img=-13664
I/get_imu_correspondence.cc:61 Imu timestamp: 171391380, diff_prev=2010, diff_img=-11664
I/get_imu_correspondence.cc:61 Imu timestamp: 171393390, diff_prev=2010, diff_img=-9648
I/get_imu_correspondence.cc:61 Imu timestamp: 171395420, diff_prev=2030, diff_img=-7616
I/get_imu_correspondence.cc:61 Imu timestamp: 171397440, diff_prev=2020, diff_img=-5600
I/get_imu_correspondence.cc:61 Imu timestamp: 171399460, diff_prev=2020, diff_img=-3584
I/get_imu_correspondence.cc:61 Imu timestamp: 171401480, diff_prev=2020, diff_img=-1568
I/get_imu_correspondence.cc:61 Imu timestamp: 171403500, diff_prev=2020, diff_img=464
I/get_imu_correspondence.cc:61 Imu timestamp: 171405510, diff_prev=2010, diff_img=2464
I/get_imu_correspondence.cc:61 Imu timestamp: 171407520, diff_prev=2010, diff_img=4480
I/get_imu_correspondence.cc:61 Imu timestamp: 171409540, diff_prev=2020, diff_img=6496
I/get_imu_correspondence.cc:61 Imu timestamp: 171411570, diff_prev=2030, diff_img=8528
I/get_imu_correspondence.cc:61 Imu timestamp: 171413590, diff_prev=2020, diff_img=10544
I/get_imu_correspondence.cc:61 Imu timestamp: 171415610, diff_prev=2020, diff_img=12576
I/get_imu_correspondence.cc:61 Imu timestamp: 171417630, diff_prev=2020, diff_img=14592
I/get_imu_correspondence.cc:61 Imu timestamp: 171419650, diff_prev=2020, diff_img=16608
I/get_imu_correspondence.cc:61 Imu timestamp: 171421660, diff_prev=2010, diff_img=18624

Complete code examples, see get_imu_correspondence.cc .

Get Data From Callbacks¶

API offers function SetStreamCallback() and SetMotionCallback() to set callbacks for various data.

Attention

Make sure to not block callback. If the data processing time is too long, use the callback as a data producer.

Reference code snippet:

auto &&api = API::Create(argc, argv);

// Attention: must not block the callbacks.

// Get left image from callback
std::atomic_uint left_count(0);
api->SetStreamCallback(
    Stream::LEFT, [&left_count](const api::StreamData &data) {
      CHECK_NOTNULL(data.img);
      ++left_count;
    });

// Get depth image from callback
api->EnableStreamData(Stream::DEPTH);
std::atomic_uint depth_count(0);
cv::Mat depth;
std::mutex depth_mtx;
api->SetStreamCallback(
    Stream::DEPTH,
    [&depth_count, &depth, &depth_mtx](const api::StreamData &data) {
      UNUSED(data)
      ++depth_count;
      {
        std::lock_guard<std::mutex> _(depth_mtx);
        depth = data.frame;
      }
    });

// Get motion data from callback
std::atomic_uint imu_count(0);
std::shared_ptr<mynteye::ImuData> imu;
std::mutex imu_mtx;
api->SetMotionCallback(
    [&imu_count, &imu, &imu_mtx](const api::MotionData &data) {
      CHECK_NOTNULL(data.imu);
      ++imu_count;
      {
        std::lock_guard<std::mutex> _(imu_mtx);
        imu = data.imu;
      }
    });

api->Start(Source::ALL);

CVPainter painter;

cv::namedWindow("frame");
cv::namedWindow("depth");

unsigned int depth_num = 0;
while (true) {
  api->WaitForStreams();

  auto &&left_data = api->GetStreamData(Stream::LEFT);
  auto &&right_data = api->GetStreamData(Stream::RIGHT);

  // Concat left and right as img
  cv::Mat img;
  cv::hconcat(left_data.frame, right_data.frame, img);

  // Draw img data and size
  painter.DrawImgData(img, *left_data.img);

  // Draw imu data
  if (imu) {
    std::lock_guard<std::mutex> _(imu_mtx);
    painter.DrawImuData(img, *imu);
  }

  // Draw counts
  std::ostringstream ss;
  ss << "left: " << left_count << ", depth: " << depth_count
     << ", imu: " << imu_count;
  painter.DrawText(img, ss.str(), CVPainter::BOTTOM_RIGHT);

  // Show img
  cv::imshow("frame", img);

  // Show depth
  if (!depth.empty()) {
    // Is the depth a new one?
    if (depth_num != depth_count || depth_num == 0) {
      std::lock_guard<std::mutex> _(depth_mtx);
      depth_num = depth_count;
      // LOG(INFO) << "depth_num: " << depth_num;
      ss.str("");
      ss.clear();
      ss << "depth: " << depth_count;
      painter.DrawText(depth, ss.str());
      cv::imshow("depth", depth);  // CV_16UC1
    }
  }

  char key = static_cast<char>(cv::waitKey(1));
  if (key == 27 || key == 'q' || key == 'Q') {  // ESC/Q
    break;
  }
}

api->Stop(Source::ALL);

OpenCV is used to display images and data above. When the window is selected, pressing ESC/Q will exit program.

Complete code examples, see get_from_callbacks.cc .

Using The Plugin To Get Data¶

API provides a EnablePlugin() function to enable plugins under a path.

Official provided plugins for calculating binocular parallax are now available in the MYNTEYE_BOX located in the Plugins directory.

Plugins/
├─linux-x86_64/
│  ├─libplugin_b_ocl1.2_opencv3.4.0.so
│  ├─libplugin_g_cuda9.1_opencv2.4.13.5.so
│  ├─libplugin_g_cuda9.1_opencv3.3.1.so
│  └─libplugin_g_cuda9.1_opencv3.4.0.so
├─tegra-armv8/
└─win-x86_64/

The linux-x86_64 directory shows the system and architecture.
- You can find your CPU architecture from system information or uname -a.
The library name libplugin_* shows the plugin identity and the third party dependency.
- b g is a plugin identifier, indicating that different algorithms are used.
- ocl1.2 shows it dependence on OpenCL 1.2, if it exists.
- cuda9.1 shows it dependence on CUDA 9.1, if it exists.
- opencv3.4.0 shows it dependence on OpenCV 3.4.0, if it exists.
- mynteye2.0.0 shows it dependency on MYNT EYE SDK 2.0.0, if it exists.

First, select the plugins that you are going to use depending on your situation. If you relying on third parties, please install a corresponding version.

Then, enable the plugin with the following code:

auto &&api = API::Create(argc, argv);

api->EnablePlugin("plugins/linux-x86_64/libplugin_g_cuda10.1_opencv3.4.1.so");

The path can be an absolute path or a relative path (relative to the current working directory).

Finally, just call the API to get the data as before.

Tip

If the plugin is not enabled, api->Start(Source::VIDEO_STREAMING); will automatically find the appropriate plug-in in the <sdk>/plugins/<platform> directory to load.

In other words, you can move the plug-in directory of the current platform into the < SDK > / plugins directory. To automatically load the official plugin, install the corresponding CUDA OpenCV plugin dependency, recompiling and then run API layer interface program.

Before running, please execute the following commands to ensure that the plugin’s dependency library can be searched:

# Linux
export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH
# /usr/local/lib means the path of dependency library

# macOS
export DYLD_LIBRARY_PATH=/usr/local/lib:$DYLD_LIBRARY_PATH
# /usr/local/lib means the path of dependency library

# Windows
set PATH=C:\opencv\x64\vc14\bin;%PATH%
# add to PATH of system environment

In addition, the following command can be executed to check whether the dependency Library of the plug-in can be searched:

# Linux
ldd *.so
# *.so means plugin path

# macOS
otool -L *.dylib
# *.dylib means plugin path

# Windows
# please download Dependency Walker ，open DLL .

If the plugin’s dependent library is not found, it will report an error "Open plugin failed" when loading.

Complete code sample, see get_with_plugin.cc .

Tip

Linux can also add a dependency library path to the system environment, so that the compiled program can run directly. (does not require export LD_LIBRARY_PATH in the terminal then run again).

Create a /etc/ld.so.conf.d/libmynteye.conf file and write the dependent library path.
Execute the sudo /sbin/ldconfig command in the terminal and refresh the cache.

Save Device Infomation And Parameters¶

The SDK provides a tool save_all_infos for save information and parameters.

Reference commands:

./samples/_output/bin/save_all_infos

# Windows
.\samples\_output\bin\save_all_infos.bat

Reference result on Linux:

$ ./samples/_output/bin/save_all_infos
I0512 21:40:08.687088  4092 utils.cc:26] Detecting MYNT EYE devices
I0512 21:40:09.366693  4092 utils.cc:33] MYNT EYE devices:
I0512 21:40:09.366734  4092 utils.cc:37]   index: 0, name: MYNT-EYE-S1000
I0512 21:40:09.366757  4092 utils.cc:43] Only one MYNT EYE device, select index: 0
I0512 21:40:09.367609  4092 save_all_infos.cc:38] Save all infos to "config/SN0610243700090720"

Result save into <workdir>/config by default. You can also add parameters to select other directory for save.

Saved contents:

<workdir>/
└─config/
   └─SN0610243700090720/
      ├─device.info
      ├─img.params
      └─imu.params

Save Single Image¶

Press “Space” “s” “S” to save image.

Reference commands:

api->Start(Source::VIDEO_STREAMING);

cv::namedWindow("frame");

std::int32_t count = 0;
std::cout << "Press 'Space' 's' 'S' to save image." << std::endl;
while (true) {
  api->WaitForStreams();

  auto &&left_data = api->GetStreamData(Stream::LEFT);
  auto &&right_data = api->GetStreamData(Stream::RIGHT);
  if (!left_data.frame.empty() && !right_data.frame.empty()) {
    cv::Mat img;
    cv::hconcat(left_data.frame, right_data.frame, img);
    cv::imshow("frame", img);
  }

  char key = static_cast<char>(cv::waitKey(1));
  if (key == 27 || key == 'q' || key == 'Q') {  // ESC/Q
    break;
  } else if (key == 32 || key == 's' || key == 'S') {
    if (!left_data.frame.empty() && !right_data.frame.empty()) {
      char l_name[20];
      char r_name[20];
      ++count;
      snprintf(l_name, sizeof(l_name), "left_%d.jpg", count);
      snprintf(r_name, sizeof(r_name), "right_%d.jpg", count);

      cv::imwrite(l_name, left_data.frame);
      cv::imwrite(r_name, right_data.frame);

      std::cout << "Saved " << l_name << " " << r_name << " to current directory" << std::endl;
    }
  }
}

api->Stop(Source::VIDEO_STREAMING);

The above code uses OpenCV to display the image. When the display window is selected, pressing ESC/Q will end the program.

Complete code examples, see save_single_image.cc .

Write Image Parameters¶

The SDK provides a tool write_img_params for writing image parameters.

For getting image parameters, please read get_img_params. This is used to calculate the deviation.

Reference commands:

./samples/_output/bin/write_img_params samples/config/img.params

# Windows
.\samples\_output\bin\write_img_params.bat samples\config\img.params

Warning

Please don’t override parameters, you can use save_all_infos to backup parameters.

And, samples/config/S1030/img.params.pinhole is the path of S1030 pihole parameters file. If you calibrated parameters yourself, you can edit it and run previous commands to write them into the devices.

Tip

The image calibration parameters of S21XX are in samples/config/S21XX The image calibration parameters of S1030 are in samples/config/S1030

Tip

You can also write into devices with SN*.conf provided by old SDK.

Write IMU Parameters¶

SDK provides the tool write_imu_params to write IMU parameters.

Information about how to get IMU parameters, please read get_imu_params .

Reference commands:

./samples/_output/bin/write_imu_params samples/config/imu.params

# Windows
.\samples\_output\bin\write_imu_params.bat samples\config\imu.params

The path of parameters folder can be found in samples/config/imu.params . If you calibrated the parameters yourself, you can edit the file and run above commands to write them into the device.

Warning

Please don’t override parameters, you can use save_all_infos to backup parameters.

SDK Control Samples¶

Set the frame rate of image & IMU frequency¶

Using the SetOptionValue() function in the API, you can set various control valuesfor the current device.

For mynteye s1030, to set the image frame rate and IMU frequency, set Option::FRAME_RATE and Option::IMU_FREQUENCY.

Attention

The effective fps of the image: 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60.
The effective frequency of IMU: 100, 200, 250, 333, 500.

For mynteye s21XX, the image frame rate should be selected when running the sample, and the frame rate and resolution are combined as follows:

index: 0, request: width: 1280, height: 400, format: Format::BGR888, fps: 10
index: 1, request: width: 1280, height: 400, format: Format::BGR888, fps: 20
index: 2, request: width: 1280, height: 400, format: Format::BGR888, fps: 30
index: 3, request: width: 1280, height: 400, format: Format::BGR888, fps: 60
index: 4, request: width: 2560, height: 800, format: Format::BGR888, fps: 10
index: 5, request: width: 2560, height: 800, format: Format::BGR888, fps: 20
index: 6, request: width: 2560, height: 800, format: Format::BGR888, fps: 30

Reference Code:

s1030：

auto &&api = API::Create(argc, argv);

// Attention: must set FRAME_RATE and IMU_FREQUENCY together, otherwise won't
// succeed.

// FRAME_RATE values: 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60
api->SetOptionValue(Option::FRAME_RATE, 25);
// IMU_FREQUENCY values: 100, 200, 250, 333, 500
api->SetOptionValue(Option::IMU_FREQUENCY, 500);

LOG(INFO) << "Set FRAME_RATE to " << api->GetOptionValue(Option::FRAME_RATE);
LOG(INFO) << "Set IMU_FREQUENCY to "
          << api->GetOptionValue(Option::IMU_FREQUENCY);

s21XX：

auto &&api = API::Create(argc, argv);
if (!api) return 1;

bool ok;
auto &&request = api->SelectStreamRequest(&ok);
if (!ok) return 1;
api->ConfigStreamRequest(request);

LOG(INFO) << "Please set frame rate by 'SelectStreamRequest()'";

Reference running results on Linux:

s1030：

$ ./samples/_output/bin/ctrl_framerate
I0513 14:05:57.218222 31813 utils.cc:26] Detecting MYNT EYE devices
I0513 14:05:57.899404 31813 utils.cc:33] MYNT EYE devices:
I0513 14:05:57.899430 31813 utils.cc:37]   index: 0, name: MYNT-EYE-S1000
I0513 14:05:57.899435 31813 utils.cc:43] Only one MYNT EYE device, select index: 0
I0513 14:05:58.076257 31813 framerate.cc:36] Set FRAME_RATE to 25
I0513 14:05:58.076836 31813 framerate.cc:37] Set IMU_FREQUENCY to 500
I0513 14:06:21.702361 31813 framerate.cc:82] Time beg: 2018-05-13 14:05:58.384967, end: 2018-05-13 14:06:21.666115, cost: 23281.1ms
I0513 14:06:21.702388 31813 framerate.cc:85] Img count: 573, fps: 24.6122
I0513 14:06:21.702404 31813 framerate.cc:87] Imu count: 11509, hz: 494.348

s21XX：

$ ./samples/_output/bin/ctrl_framerate
I/utils.cc:30 Detecting MYNT EYE devices
I/utils.cc:40 MYNT EYE devices:
I/utils.cc:43   index: 0, name: MYNT-EYE-S210A, sn: 07C41A190009071F
I/utils.cc:51 Only one MYNT EYE device, select index: 0
I/utils.cc:79 MYNT EYE devices:
I/utils.cc:82   index: 0, request: width: 1280, height: 400, format: Format::BGR888, fps: 10
I/utils.cc:82   index: 1, request: width: 1280, height: 400, format: Format::BGR888, fps: 20
I/utils.cc:82   index: 2, request: width: 1280, height: 400, format: Format::BGR888, fps: 30
I/utils.cc:82   index: 3, request: width: 1280, height: 400, format: Format::BGR888, fps: 60
I/utils.cc:82   index: 4, request: width: 2560, height: 800, format: Format::BGR888, fps: 10
I/utils.cc:82   index: 5, request: width: 2560, height: 800, format: Format::BGR888, fps: 20
I/utils.cc:82   index: 6, request: width: 2560, height: 800, format: Format::BGR888, fps: 30
I/utils.cc:93 There are 7 stream requests, select index:
2
I/framerate.cc:54 Please set frame rate by 'SelectStreamRequest()'
I/framerate.cc:99 Time beg: 2018-12-29 10:05:08.203095, end: 2018-12-29 10:08:20.074969, cost: 191872ms
I/framerate.cc:102 Img count: 5759, fps: 30.0148
I/framerate.cc:104 Imu count: 77163, hz: 402.159

After the sample program finishes running with ESC/Q, it will output the calculated value of the frame rate of image & IMU frequency.

Complete code samples，please see ctrl_framerate.cc .

Set the range of accelerometer & gyroscope¶

Using the SetOptionValue() function in the API, you can set various control values for the current device.

To set the range of accelerometer and gyroscope, set Option::ACCELEROMETER_RANGE and Option::GYROSCOPE_RANGE.

Attention

For mynteye s1030, the available settings are:

The effective range of accelerometer(unit:g): 4, 8, 16, 32.
Gyroscope Range Valid value (unit: DEG/S): 500, 1000, 2000, 4000.

For mynteye s21XX, the available settings are:

The effective range of accelerometer(unit:g): 6, 12, 24, 48.
The effective range of gyroscope(unit:deg/s): 250, 500, 1000, 2000, 4000.

Reference Code:

s1030：

auto &&api = API::Create(argc, argv);
if (!api)
  return 1;

// ACCELEROMETER_RANGE values: 4, 8, 16, 32
api->SetOptionValue(Option::ACCELEROMETER_RANGE, 8);
// GYROSCOPE_RANGE values: 500, 1000, 2000, 4000
api->SetOptionValue(Option::GYROSCOPE_RANGE, 1000);

LOG(INFO) << "Set ACCELEROMETER_RANGE to "
          << api->GetOptionValue(Option::ACCELEROMETER_RANGE);
LOG(INFO) << "Set GYROSCOPE_RANGE to "
          << api->GetOptionValue(Option::GYROSCOPE_RANGE);

s21XX：

auto &&api = API::Create(argc, argv);
if (!api) return 1;

bool ok;
auto &&request = api->SelectStreamRequest(&ok);
if (!ok) return 1;
api->ConfigStreamRequest(request);

// ACCELEROMETER_RANGE values: 6, 12, 24, 48
api->SetOptionValue(Option::ACCELEROMETER_RANGE, 6);
// GYROSCOPE_RANGE values: 250, 500, 1000, 2000, 4000
api->SetOptionValue(Option::GYROSCOPE_RANGE, 1000);

LOG(INFO) << "Set ACCELEROMETER_RANGE to "
          << api->GetOptionValue(Option::ACCELEROMETER_RANGE);
LOG(INFO) << "Set GYROSCOPE_RANGE to "
          << api->GetOptionValue(Option::GYROSCOPE_RANGE);

Reference running results on Linux:

s1030：

$ ./samples/_output/bin/ctrl_imu_range
I/utils.cc:28 Detecting MYNT EYE devices
I/utils.cc:38 MYNT EYE devices:
I/utils.cc:41   index: 0, name: MYNT-EYE-S1030, sn: 4B4C1F1100090712
I/utils.cc:49 Only one MYNT EYE device, select index: 0
I/imu_range.cc:34 Set ACCELEROMETER_RANGE to 8
I/imu_range.cc:36 Set GYROSCOPE_RANGE to 1000
I/imu_range.cc:81 Time beg: 2018-11-21 15:34:57.726428, end: 2018-11-21 15:35:12.190478, cost: 14464ms
I/imu_range.cc:84 Img count: 363, fps: 25.0967
I/imu_range.cc:86 Imu count: 2825, hz: 195.312

s21XX：

$ ./samples/_output/bin/ctrl_imu_range
I/utils.cc:30 Detecting MYNT EYE devices
I/utils.cc:40 MYNT EYE devices:
I/utils.cc:43   index: 0, name: MYNT-EYE-S210A, sn: 07C41A190009071F
I/utils.cc:51 Only one MYNT EYE device, select index: 0
I/utils.cc:79 MYNT EYE devices:
I/utils.cc:82   index: 0, request: width: 1280, height: 400, format: Format::BGR888, fps: 10
I/utils.cc:82   index: 1, request: width: 1280, height: 400, format: Format::BGR888, fps: 20
I/utils.cc:82   index: 2, request: width: 1280, height: 400, format: Format::BGR888, fps: 30
I/utils.cc:82   index: 3, request: width: 1280, height: 400, format: Format::BGR888, fps: 60
I/utils.cc:82   index: 4, request: width: 2560, height: 800, format: Format::BGR888, fps: 10
I/utils.cc:82   index: 5, request: width: 2560, height: 800, format: Format::BGR888, fps: 20
I/utils.cc:82   index: 6, request: width: 2560, height: 800, format: Format::BGR888, fps: 30
I/utils.cc:93 There are 7 stream requests, select index:
3
I/imu_range.cc:51 Set ACCELEROMETER_RANGE to 6
I/imu_range.cc:53 Set GYROSCOPE_RANGE to 1000
I/imu_range.cc:98 Time beg: 2018-12-29 10:03:10.706211, end: 2018-12-29 10:04:12.497427, cost: 61791.2ms
I/imu_range.cc:101 Img count: 3706, fps: 59.9762
I/imu_range.cc:103 Imu count: 24873, hz: 402.533

After the sample program finishes running with ESC/Q, the ranges of imu setting is complete. The ranges will be kept inside the hardware and not affected by power off.

Complete code samples，please see ctrl_imu_range.cc.

Enable auto exposure and its adjustment function¶

Using the SetOptionValue() function of the API, you can set various control values of the current open device.

To enable auto exposure, set Option::EXPOSURE_MODE to 0 .

For mynteye s1030, the settings available for adjustment during auto exposure are:

Option::MAX_GAIN Maximum gain.
Option::MAX_EXPOSURE_TIME Maximum exposure time.
Option::DESIRED_BRIGHTNESS Expected brightness.

For mynteye s21XX, the settings available for adjustment during auto exposure are:

Option::MAX_GAIN Maximum gain.
Option::MAX_EXPOSURE_TIME Maximum exposure time.
Option::DESIRED_BRIGHTNESS Expected brightness.
Option::MIN_EXPOSURE_TIME Minimum exposure time.

Reference Code:

s1030：

auto &&api = API::Create(argc, argv);

// auto-exposure: 0
api->SetOptionValue(Option::EXPOSURE_MODE, 0);

// max_gain: range [0,48], default 48
api->SetOptionValue(Option::MAX_GAIN, 48);
// max_exposure_time: range [0,240], default 240
api->SetOptionValue(Option::MAX_EXPOSURE_TIME, 240);
// desired_brightness: range [0,255], default 192
api->SetOptionValue(Option::DESIRED_BRIGHTNESS, 192);

LOG(INFO) << "Enable auto-exposure";
LOG(INFO) << "Set MAX_GAIN to " << api->GetOptionValue(Option::MAX_GAIN);
LOG(INFO) << "Set MAX_EXPOSURE_TIME to "
          << api->GetOptionValue(Option::MAX_EXPOSURE_TIME);
LOG(INFO) << "Set DESIRED_BRIGHTNESS to "
          << api->GetOptionValue(Option::DESIRED_BRIGHTNESS);

s21XX：

auto &&api = API::Create(argc, argv);

bool ok;
auto &&request = api->SelectStreamRequest(&ok);
if (!ok) return 1;
api->ConfigStreamRequest(request);

// auto-exposure: 0
api->SetOptionValue(Option::EXPOSURE_MODE, 0);

// max_gain: range [0,255], default 8
api->SetOptionValue(Option::MAX_GAIN, 8);
// max_exposure_time: range [0,1000], default 333
api->SetOptionValue(Option::MAX_EXPOSURE_TIME, 333);
// desired_brightness: range [1,255], default 122
api->SetOptionValue(Option::DESIRED_BRIGHTNESS, 122);
// min_exposure_time: range [0,1000], default 0
api->SetOptionValue(Option::MIN_EXPOSURE_TIME, 0);

LOG(INFO) << "Enable auto-exposure";
LOG(INFO) << "Set EXPOSURE_MODE to "
          << api->GetOptionValue(Option::EXPOSURE_MODE);
LOG(INFO) << "Set MAX_GAIN to " << api->GetOptionValue(Option::MAX_GAIN);
LOG(INFO) << "Set MAX_EXPOSURE_TIME to "
          << api->GetOptionValue(Option::MAX_EXPOSURE_TIME);
LOG(INFO) << "Set DESIRED_BRIGHTNESS to "
          << api->GetOptionValue(Option::DESIRED_BRIGHTNESS);
LOG(INFO) << "Set MIN_EXPOSURE_TIME to "
          << api->GetOptionValue(Option::MIN_EXPOSURE_TIME);

Reference running results on Linux:

s1030：

$ ./samples/_output/bin/ctrl_auto_exposure
I0513 14:07:57.963943 31845 utils.cc:26] Detecting MYNT EYE devices
I0513 14:07:58.457536 31845 utils.cc:33] MYNT EYE devices:
I0513 14:07:58.457563 31845 utils.cc:37]   index: 0, name: MYNT-EYE-S1000
I0513 14:07:58.457567 31845 utils.cc:43] Only one MYNT EYE device, select index: 0
I0513 14:07:58.474916 31845 auto_exposure.cc:37] Enable auto-exposure
I0513 14:07:58.491058 31845 auto_exposure.cc:38] Set MAX_GAIN to 48
I0513 14:07:58.505131 31845 auto_exposure.cc:39] Set MAX_EXPOSURE_TIME to 240
I0513 14:07:58.521375 31845 auto_exposure.cc:41] Set DESIRED_BRIGHTNESS to 192

s21XX：

$ ./samples/_output/bin/ctrl_auto_exposure
I/utils.cc:30 Detecting MYNT EYE devices
I/utils.cc:40 MYNT EYE devices:
I/utils.cc:43   index: 0, name: MYNT-EYE-S210A, sn: 07C41A190009071F
I/utils.cc:51 Only one MYNT EYE device, select index: 0
I/utils.cc:79 MYNT EYE devices:
I/utils.cc:82   index: 0, request: width: 1280, height: 400, format: Format::BGR888, fps: 10
I/utils.cc:82   index: 1, request: width: 1280, height: 400, format: Format::BGR888, fps: 20
I/utils.cc:82   index: 2, request: width: 1280, height: 400, format: Format::BGR888, fps: 30
I/utils.cc:82   index: 3, request: width: 1280, height: 400, format: Format::BGR888, fps: 60
I/utils.cc:82   index: 4, request: width: 2560, height: 800, format: Format::BGR888, fps: 10
I/utils.cc:82   index: 5, request: width: 2560, height: 800, format: Format::BGR888, fps: 20
I/utils.cc:82   index: 6, request: width: 2560, height: 800, format: Format::BGR888, fps: 30
I/utils.cc:93 There are 7 stream requests, select index:
3
I/auto_exposure.cc:72 Enable auto-exposure
I/auto_exposure.cc:73 Set EXPOSURE_MODE to 0
I/auto_exposure.cc:75 Set MAX_GAIN to 8
I/auto_exposure.cc:76 Set MAX_EXPOSURE_TIME to 333
I/auto_exposure.cc:78 Set DESIRED_BRIGHTNESS to 122
I/auto_exposure.cc:80 Set MIN_EXPOSURE_TIME to 0

The sample program displays an image with a real exposure time in the upper left corner, in milliseconds.

Complete code examples, see ctrl_auto_exposure.cc .

Enable manual exposure and its adjustment function¶

Using the SetOptionValue() function of the API, you can set various control values for the current open device.

To enabling manual exposure, set Option::EXPOSURE_MODE to 1.

For mynteye s1030, during manual exposure, the settings available for adjustment are:

Option::GAIN Gain.
Option::BRIGHTNESS Brightness (Exposure time).
Option::CONTRAST Contrast (Black level calibration).

For mynteye s21XX, during manual exposure, the settings available for adjustment are:

Option::BRIGHTNESS Brightness (Exposure time).

Reference Code:

s1030：

auto &&api = API::Create(argc, argv);

// manual-exposure: 1
api->SetOptionValue(Option::EXPOSURE_MODE, 1);

// gain: range [0,48], default 24
api->SetOptionValue(Option::GAIN, 24);
// brightness/exposure_time: range [0,240], default 120
api->SetOptionValue(Option::BRIGHTNESS, 120);
// contrast/black_level_calibration: range [0,254], default 116
api->SetOptionValue(Option::CONTRAST, 116);

LOG(INFO) << "Enable manual-exposure";
LOG(INFO) << "Set GAIN to " << api->GetOptionValue(Option::GAIN);
LOG(INFO) << "Set BRIGHTNESS to " << api->GetOptionValue(Option::BRIGHTNESS);
LOG(INFO) << "Set CONTRAST to " << api->GetOptionValue(Option::CONTRAST);

s21XX：

auto &&api = API::Create(argc, argv);

bool ok;
auto &&request = api->SelectStreamRequest(&ok);
if (!ok) return 1;
api->ConfigStreamRequest(request);

// manual-exposure: 1
api->SetOptionValue(Option::EXPOSURE_MODE, 1);

// brightness/exposure_time: range [1,255], default 70
api->SetOptionValue(Option::BRIGHTNESS, 70);

LOG(INFO) << "Enable manual-exposure";
LOG(INFO) << "Set EXPOSURE_MODE to "
          << api->GetOptionValue(Option::EXPOSURE_MODE);
LOG(INFO) << "Set BRIGHTNESS to "
          << api->GetOptionValue(Option::BRIGHTNESS);

Reference running results on Linux:

s1030：

$ ./samples/_output/bin/ctrl_manual_exposure
I0513 14:09:17.104431 31908 utils.cc:26] Detecting MYNT EYE devices
I0513 14:09:17.501519 31908 utils.cc:33] MYNT EYE devices:
I0513 14:09:17.501551 31908 utils.cc:37]   index: 0, name: MYNT-EYE-S1000
I0513 14:09:17.501562 31908 utils.cc:43] Only one MYNT EYE device, select index: 0
I0513 14:09:17.552918 31908 manual_exposure.cc:37] Enable manual-exposure
I0513 14:09:17.552953 31908 manual_exposure.cc:38] Set GAIN to 24
I0513 14:09:17.552958 31908 manual_exposure.cc:39] Set BRIGHTNESS to 120
I0513 14:09:17.552963 31908 manual_exposure.cc:40] Set CONTRAST to 116

s21XX：

$ ./samples/_output/bin/ctrl_manual_exposure
I/utils.cc:30 Detecting MYNT EYE devices
I/utils.cc:40 MYNT EYE devices:
I/utils.cc:43   index: 0, name: MYNT-EYE-S210A, sn: 07C41A190009071F
I/utils.cc:51 Only one MYNT EYE device, select index: 0
I/utils.cc:79 MYNT EYE devices:
I/utils.cc:82   index: 0, request: width: 1280, height: 400, format: Format::BGR888, fps: 10
I/utils.cc:82   index: 1, request: width: 1280, height: 400, format: Format::BGR888, fps: 20
I/utils.cc:82   index: 2, request: width: 1280, height: 400, format: Format::BGR888, fps: 30
I/utils.cc:82   index: 3, request: width: 1280, height: 400, format: Format::BGR888, fps: 60
I/utils.cc:82   index: 4, request: width: 2560, height: 800, format: Format::BGR888, fps: 10
I/utils.cc:82   index: 5, request: width: 2560, height: 800, format: Format::BGR888, fps: 20
I/utils.cc:82   index: 6, request: width: 2560, height: 800, format: Format::BGR888, fps: 30
I/utils.cc:93 There are 7 stream requests, select index:
3
I/manual_exposure.cc:62 Enable manual-exposure
I/manual_exposure.cc:63 Set EXPOSURE_MODE to 1
I/manual_exposure.cc:65 Set BRIGHTNESS to 70

The sample program displays an image with a real exposure time in the upper left corner, in milliseconds.

Complete code samples，see ctrl_manual_exposure.cc .

Enable IR and its adjustments function¶

Using the SetOptionValue() function of the API, you can set various control values for the current open device.

Enabling IR is setting Option::IR_CONTROL greater than 0. The greater the value, the greater the IR’s intensity.

Attention

mynteye s21XX doesn’t support this feature.

Reference Code:

auto &&api = API::Create(argc, argv);

// Detect infrared add-ons
LOG(INFO) << "Support infrared: " << std::boolalpha
          << api->Supports(AddOns::INFRARED);
LOG(INFO) << "Support infrared2: " << std::boolalpha
          << api->Supports(AddOns::INFRARED2);

// Get infrared intensity range
auto &&info = api->GetOptionInfo(Option::IR_CONTROL);
LOG(INFO) << Option::IR_CONTROL << ": {" << info << "}";

// Set infrared intensity value
api->SetOptionValue(Option::IR_CONTROL, 80);

Reference running results on Linux:

$ ./samples/_output/bin/ctrl_infrared
I0504 16:16:28.016624 25848 utils.cc:13] Detecting MYNT EYE devices
I0504 16:16:28.512462 25848 utils.cc:20] MYNT EYE devices:
I0504 16:16:28.512473 25848 utils.cc:24]   index: 0, name: MYNT-EYE-S1000
I0504 16:16:28.512477 25848 utils.cc:30] Only one MYNT EYE device, select index: 0
I0504 16:16:28.520848 25848 infrared.cc:13] Support infrared: true
I0504 16:16:28.520869 25848 infrared.cc:15] Support infrared2: true
I0504 16:16:28.520889 25848 infrared.cc:20] Option::IR_CONTROL: {min: 0, max: 160, def: 0}

At this point, if the image is displayed, you can see IR speckle on the image, as below:

Attention

The hardware will not record the IR value after being turned off and will reset to 0. In order to keep IR enabled, you must set the IR value after turning on the device.

Complete code samples，see ctrl_infrared.cc .

Low-pass Filter¶

Using the SetOptionValue() function in the API, you can set various control values for the current device.

To set the value of accelerometer low-pass filter and gyroscope low-pass filter, set Option::ACCELEROMETER_LOW_PASS_FILTER and Option::GYROSCOPE_LOW_PASS_FILTER.

Attention

s1030 doesn’t support this feature

Reference Code:

auto &&api = API::Create(argc, argv);
if (!api) return 1;

bool ok;
auto &&request = api->SelectStreamRequest(&ok);
if (!ok) return 1;
api->ConfigStreamRequest(request);

// ACCELEROMETER_RANGE values: 0, 1, 2
api->SetOptionValue(Option::ACCELEROMETER_LOW_PASS_FILTER, 2);
// GYROSCOPE_RANGE values: 23, 64
api->SetOptionValue(Option::GYROSCOPE_LOW_PASS_FILTER, 64);

LOG(INFO) << "Set ACCELEROMETER_LOW_PASS_FILTER to "
          << api->GetOptionValue(Option::ACCELEROMETER_LOW_PASS_FILTER);
LOG(INFO) << "Set GYROSCOPE_LOW_PASS_FILTER to "
          << api->GetOptionValue(Option::GYROSCOPE_LOW_PASS_FILTER);

Reference running results on Linux:

$ ./samples/_output/bin/ctrl_imu_low_pass_filter
I/utils.cc:30 Detecting MYNT EYE devices
I/utils.cc:40 MYNT EYE devices:
I/utils.cc:43   index: 0, name: MYNT-EYE-S210A, sn: 07C41A190009071F
I/utils.cc:51 Only one MYNT EYE device, select index: 0
I/utils.cc:79 MYNT EYE devices:
I/utils.cc:82   index: 0, request: width: 1280, height: 400, format: Format::BGR888, fps: 10
I/utils.cc:82   index: 1, request: width: 1280, height: 400, format: Format::BGR888, fps: 20
I/utils.cc:82   index: 2, request: width: 1280, height: 400, format: Format::BGR888, fps: 30
I/utils.cc:82   index: 3, request: width: 1280, height: 400, format: Format::BGR888, fps: 60
I/utils.cc:82   index: 4, request: width: 2560, height: 800, format: Format::BGR888, fps: 10
I/utils.cc:82   index: 5, request: width: 2560, height: 800, format: Format::BGR888, fps: 20
I/utils.cc:82   index: 6, request: width: 2560, height: 800, format: Format::BGR888, fps: 30
I/utils.cc:93 There are 7 stream requests, select index:
1
I/imu_low_pass_filter.cc:48 Set ACCELEROMETER_LOW_PASS_FILTER to 2
I/imu_low_pass_filter.cc:50 Set GYROSCOPE_LOW_PASS_FILTER to 64
I/imu_low_pass_filter.cc:96 Time beg: 2018-12-29 13:53:42.296299, end: 2018-12-29 14:06:33.295960, cost: 771000ms
I/imu_low_pass_filter.cc:99 Img count: 15412, fps: 19.9896
I/imu_low_pass_filter.cc:101 Imu count: 309891, hz: 401.934

After the sample program finishes running with ESC/Q, the low-pass filter of imu setting is complete. The ranges will be kept inside the hardware and not affected by power off.

Complete code samples，please see ctrl_imu_low_pass_filter.cc 。

Set IIC Address¶

Using the SetOptionValue() function in the API, you can set various control values for the current device.

To set the IIC address, set Option::IIC_ADDRESS_SETTING.

Attention

Only support S21XX

Reference Code:

s2XX：

auto &&api = API::Create(argc, argv);
if (!api) return 1;
bool ok;
auto &&request = api->SelectStreamRequest(&ok);
if (!ok) return 1;
api->ConfigStreamRequest(request);
Model model = api->GetModel();
if (model == Model::STANDARD210A || model == Model::STANDARD2) {
  api->SetOptionValue(Option::IIC_ADDRESS_SETTING, 0x31);
  LOG(INFO) << "Set iic address to " << std::hex << "0x"
            << api->GetOptionValue(Option::IIC_ADDRESS_SETTING);
}

Reference running results on Linux:

s21XX：

$ ./samples/_output/bin/ctrl_iic_adress
I/utils.cc:30 Detecting MYNT EYE devices
I/utils.cc:40 MYNT EYE devices:
I/utils.cc:43   index: 0, name: MYNT-EYE-S210A, sn: 07C41A190009071F
I/utils.cc:51 Only one MYNT EYE device, select index: 0
I/utils.cc:79 MYNT EYE devices:
I/utils.cc:82   index: 0, request: width: 1280, height: 400, format: Format::BGR888, fps: 10
I/utils.cc:82   index: 1, request: width: 1280, height: 400, format: Format::BGR888, fps: 20
I/utils.cc:82   index: 2, request: width: 1280, height: 400, format: Format::BGR888, fps: 30
I/utils.cc:82   index: 3, request: width: 1280, height: 400, format: Format::BGR888, fps: 60
I/utils.cc:82   index: 4, request: width: 2560, height: 800, format: Format::BGR888, fps: 10
I/utils.cc:82   index: 5, request: width: 2560, height: 800, format: Format::BGR888, fps: 20
I/utils.cc:82   index: 6, request: width: 2560, height: 800, format: Format::BGR888, fps: 30
I/utils.cc:93 There are 7 stream requests, select index:
3
I/imu_range.cc:51 Set iic address to 0x31

After the sample program finishes running with ESC/Q. Complete code samples，please see ctrl_iic_address.cc .

SDK Project Demos¶

How to use SDK with CMake¶

This tutorial will create a project with CMake to start using SDK.

You could find the project demo in <sdk>/samples/simple_demo/project_cmake directory .

Preparation¶

Windows: Install the win pack of SDK
Linux: build from source and make install

Create Project¶

Add CMakeLists.txt and mynteye_demo.cc files,

cmake_minimum_required(VERSION 3.0)

project(mynteyed_demo VERSION 1.0.0 LANGUAGES C CXX)

# flags

set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -Wall -O3")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wall -O3")

set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -std=c++11 -march=native")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11 -march=native")

## mynteye_demo

add_executable(mynteye_demo mynteye_demo.cc)
target_link_libraries(mynteye_demo mynteye ${OpenCV_LIBS})

Config Project¶

Add mynteye and OpenCV packages to CMakeLists.txt ,

# packages

if(MSVC)
  set(SDK_ROOT "$ENV{MYNTEYES_SDK_ROOT}")
  if(SDK_ROOT)
    message(STATUS "MYNTEYES_SDK_ROOT: ${SDK_ROOT}")
    list(APPEND CMAKE_PREFIX_PATH
      "${SDK_ROOT}/lib/cmake"
      "${SDK_ROOT}/3rdparty/opencv/build"
    )
  else()
    message(FATAL_ERROR "MYNTEYES_SDK_ROOT not found, please install SDK firstly")
  endif()
endif()

## mynteye

find_package(mynteye REQUIRED)
message(STATUS "Found mynteye: ${mynteye_VERSION}")

# When SDK build with OpenCV, we can add WITH_OPENCV macro to enable some
# features depending on OpenCV, such as ToMat().
if(mynteye_WITH_OPENCV)
  add_definitions(-DWITH_OPENCV)
endif()

## OpenCV

# Set where to find OpenCV
#set(OpenCV_DIR "/usr/share/OpenCV")

# When SDK build with OpenCV, we must find the same version here.
find_package(OpenCV REQUIRED)
message(STATUS "Found OpenCV: ${OpenCV_VERSION}")

Add include_directories and target_link_libraries to mynteye_demo target,

# targets

include_directories(
  ${OpenCV_INCLUDE_DIRS}
)

## mynteye_demo

add_executable(mynteye_demo mynteye_demo.cc)
target_link_libraries(mynteye_demo mynteye ${OpenCV_LIBS})

Start using SDK¶

Include the headers of SDK and start using its APIs, view the project demo.

Windows¶

Reference to “Install Build Tools” in install_windows_exe .

Then open x64 Native Tools Command Prompt for VS 2017 command shell to build and run.

mkdir _build
cd _build

cmake -G "Visual Studio 15 2017 Win64" ..

msbuild.exe ALL_BUILD.vcxproj /property:Configuration=Release

.\Release\mynteye_demo.exe

Linux¶

Open Terminal to build and run.

mkdir _build
cd _build/

cmake ..

make

./mynteye_demo

How to use SDK with Visual Studio 2017¶

This tutorial will create a project with Visual Studio 2017 to start using SDK.

You could find the project demo in <sdk>/samples/simple_demo/project_vs2017 directory.

Preparation¶

Windows: install the win pack of SDK

Create Project¶

Open Visual Studio 2017, then File > New > Project ,

Select “Windows Console Application”, set the project’s name and location, click “OK”,

Finally, you will see the new project like this,

Config Properties¶

Right click the project, and open its Properties window,

Change Configuration to All Configurations , then add the following paths to Additional Include Directories ,

$(MYNTEYES_SDK_ROOT)\include
$(MYNTEYES_SDK_ROOT)\3rdparty\opencv\build\include

Add the following definitions to Preprocessor Definitions ,

$(MYNTEYES_SDK_ROOT)\lib
$(MYNTEYES_SDK_ROOT)\3rdparty\opencv\build\x64\vc15\lib

Add the following paths to Additional Dependencies ，

mynteye.lib
opencv_world343.lib

If want to use debug mode, could change Configuration to Debug and add following debug libs:

mynteyed.lib
opencv_world343d.lib

Start using SDK¶

Include the headers of SDK and start using its APIs,

Select Release x64 or Debug x64 to run the project.

Change Log¶

2019-10-21(v2.5.0)¶

Change project directory structure.
Lifting dependency and improving code quality.
Support xy demo code in sample get_depth_with_region.
Fix some bugs.

2019-09-4(v2.4.2)¶

Part of the sample examples were sorted out, and useless tools and engineering code were removed.
Optimize disparity calculation.
Improving the logic of model display.
Fix some bugs.

2019-08-17(v2.4.1)¶

Optimize disparity calculation

2019-08-09(v2.4.0)¶

Optimize the synchronization of images and imu
Add 4.16+ kernel support on Ubuntu
Fix missinf frame_id issue in image information
Fix S1030 device not work issue in mynteye_multiple.launch
Add save single picture sample save_single_image

2019-07-03(v2.3.9)¶

Fix ros timestamp issue
Add calibration tool doc

2019-05-20(v2.3.8)¶

Improve VINS-Fusion supporting
Improve VINS-MONO supporting
Fix left/right rect image order error

2019-04-19(v2.3.7)¶

Improve VINS-Fusion supporting
Improve ORB-SLAM2 supporting

2019-04-15(v2.3.6)¶

Fix imu align bug of ros wrapper
Fix 14.04 complie error of ros wrapper
Support set iic address for s2100

2019-04-01(v2.3.5)¶

Improve camera info
Modify image algorithm parameters by yaml file
Add opening multi devices launch file in ROS
Add setting IIC address API of S210A
Add image/imu flag of external time source
Add LaserScan sample for S1030
Modify default orientation of point in ROS

2019-03-18(v2.3.4)¶

Add API to get auxiliary chip&ISP’s version (Depend on S2100/S210A 1.1 firmware & 1.0 subsidiary chip firmware)
Fix point fragment issue in image algorithm
Add 376*240 resolution support to S1030 (Depend on 2.4.0 firmware of S1030)
Add API to handle imu temperature drift (Depend on imu calibration)
Add version check feature
Fix depth image crash issue when use CUDA plugin
Documents update

FIRMWARE¶

Firmware Description¶

Firmware and SDK compatibility¶

S1030 Firmwares	SDK Version
MYNTEYE-S1030-2.7.0.img	2.5.0 (2.5.0 ~ latest)
MYNTEYE-S1030-2.5.0.img	2.4.0 (2.4.0 ~ 2.5.0)
MYNTEYE_S_2.4.0.img	2.3.4 (2.3.4 ~ 2.3.9)
MYNTEYE_S_2.3.0.img	2.3.0 (2.2.2-rc1 ~ 2.3.3)
MYNTEYE_S_2.2.2.img	2.3.0 (2.2.2-rc1 ~ 2.3.0)
MYNTEYE_S_2.0.0_rc.img	2.0.0-rc (2.0.0-rc ~ 2.0.0-rc2)
MYNTEYE_S_2.0.0_rc2.img	2.0.0-rc2 (2.0.0-rc ~ 2.0.0-rc2)
MYNTEYE_S_2.0.0_rc1.img	2.0.0-rc1
MYNTEYE_S_2.0.0_rc0.img	2.0.0-rc0 (2.0.0-rc1 ~ 2.0.0-alpha1)
MYNTEYE_S_2.0.0_alpha1.1.img	2.0.0-alpha1 (2.0.0-rc1 ~ 2.0.0-alpha1)
MYNTEYE_S_2.0.0_alpha1.img	2.0.0-alpha1 (2.0.0-rc1 ~ 2.0.0-alpha1)
MYNTEYE_S_2.0.0_alpha0.img	2.0.0-alpha0

S21X0 Firmwares	SDK Version
MYNTEYE-S21X0-2.1.0.img	2.5.0 (2.5.0 ~ latest)
MYNTEYE-S21X0-1.4.0.img	2.4.2(2.4.2 ~ 2.5.0)
MYNTEYE-S2100-1.3.2.img	2.4.0(2.4.0 ~ 2.4.1)
MYNTEYE_S2100_1.2.img	2.3.5(2.3.5 ~ 2.3.9)
MYNTEYE_S2100_1.1.img	2.3.4

Attention

Please CONFIRM your device model and use CORRECT firmware.

Firmwares indicates the firmware file name. It’s in MYNTEYE_BOX(Download Link) in the Firmwares directory.

SDK Version indicates the version of the SDK that the firmware is adapted to, and the range of available versions are indicated in parentheses.

Firmware Update¶

Update Main Chip Firmware¶

Please use the MYNT EYE TOOL to update main processing chip.

You can download the firmware and MYNT EYE TOOL installation package in the Firmwares folder of MYNTEYE_BOX(Download Link) . The file structure is as follows:

Firmwares/
├─Checksum.txt             # File checksum
├─MYNTEYE-S1030-2.7.0.img  # S1030 firmware
├─MYNTEYE-S21x0-2.1.0.img  # S21X0 firmware
├─...
└─mynt-eye-tool-setup.zip  # MYNT EYE TOOL zip

The firmware upgrade program currently only supports Windows, so you need to operate under Windows. Proceed as follows:

Download preparation¶

Download and unzip mynt-eye-tool-setup.zip
Find firmware, such as MYNTEYE-S1030-2.7.0.img
- Please refer to Firmware and SDK compatibility to select the firmware suitable for the SDK version

Install MYNT EYE TOOL¶

Double click on setup.msi and install the application.

Update Firmware¶

Plug in the MYNT® EYE camera into a USB3.0 port
Open MYNT EYE TOOL and select Options/FirmwareUpdate .

Click Update .

A warning dialog box will pop up, click yes .
- This operation will erase the firmware, for details see README.
  - Usually, the MYNT EYE TOOL automatically installs the driver during the upgrade process.
  - If the upgrade fails, refer to README.

In the open file selection box, select the firmware you want to upgrade and start upgrading.

Once the upgrade is complete, the status will changes to Succeeded.

Close the MYNT EYE TOOL，finish.

Attention

If you can’t find MYNT image device, WestBridge_driver, and Cypress USB BootLoader at the same time in the device manager, try another computer to perform the above operation. If you can not upgrade successfully, please contact us in time.

Manually update drivers¶

If the application indicates that you failed to update, you may fail to install the driver automatically. You can try to install the driver manually and then update it. The following is the manual installation of the driver.
Open device manager, locate WestBridge_driver device, and right click Update Driver,select [application directory]WestBridge_driver\\[corresponding system folders](If it is more than win7, choose wlh)\\[system bits] .

For example,if it is the win10 64 bit system computer,and the application is installed under the default path,you should select C:\Program Files (x86)\slightech\MYNT EYE TOOL 2.0\WestBridge_driver\wlh\x64.
After the installation driver is successful, you can find the Cypress USB BootLoader device in the device manager.

Then plug in the camera and open the application again to update.

Warning

During the first time you open the MYNT® EYE camera after a firmware update, please hold the camera steadily for 3 seconds, for a zero drift compensation process. You can also call the API RunOptionAction(Option::ZERO_DRIFT_CALIBRATION) for zero drift correction.

Update Auxiliary Chip Firmware¶

Update auxiliary chip (Only Support S21XX)¶

Plug in the MYNT® EYE camera into a USB3.0 port
Open MYNT EYE TOOL and select Options/BoardUpdate .

Click StmUpdate .

In the open file selection box, select the firmware MYNTEYE-S21X0-auxiliary-chip-1.4.2.bin and start upgrading.
Once the upgrade is complete, it will display update finished.

Change Log¶

2019-11-25¶

S1030 Main Chip Firmware: MYNTEYE-S1030-2.7.0.img

Fix some issues

S21X0 Main Chip Firmware: MYNTEYE-S21X0-2.1.0.img

Update protocol version
Fix and optimize some other issues

2019-09-09¶

S21X0 Main Chip Firmware: MYNTEYE-S21X0-1.4.0.img

Support 2110 device.

2019-08-09¶

S1030 Main Chip Firmware: MYNTEYE-S1030-2.5.0.img

Optimize the synchronization of image and imu
Not save the camera control parameters
Fix the overexplosion problem at low resolution
Fix USB 2.0 first open failure problem
Add automatic recovery function when updating wrong firmware

S2100 Main Chip Firmware: MYNTEYE-S2100-1.3.2.img

Optimize the synchronization of image and imu
Not save the camera control parameters
Optimize IMU low-pass filter default values
Optimize the exposure time calculation method, the maximum exposure time is limited to 66.5ms
Add automatic recovery function when updating wrong firmware
Fix and optimize some other issues

S2100 Auxiliary Chip Firmware: MYNTEYE-S2100-auxiliary-chip-1.4.2.bin

Time synchronization adds uart interface, io interruption judgement
Time synchronization i2c interface adds whoami, read timestamp and median filter open state interface
Fix and optimize some other issues

TOOLS SUPPORT¶

Calibration Tool Manual¶

Introduction¶

1.1 Support Platform¶

Currently the calibration tool only supports Ubuntu 16.04 LTS, but support the official, ROS multiple version of OpenCV dependencies.

Platform	Architecture	Different dependence
Ubuntu 16.04 LTS	x64(amd64)	libopencv-dev
Ubuntu 16.04 LTS	x64(amd64)	ros-kinetic-opencv3

1.2 Tools description¶

Deb/ppa installation package is available on Ubuntu. The architecture, dependencies, and versions will be distinguished from the name:

mynteye-s-calibrator-opencv-official-1.0.0_amd64.deb
mynteye-s-calibrator-opencv-ros-kinetic-1.0.0_amd64.deb

Dependency identifier	Dependency package	Detailed description
opencv-official	libopencv-dev	https://packages.ubuntu.com/xenial/libopencv-dev
opencv-ros-kinetic	ros-kinetic-opencv3	http://wiki.ros.org/opencv3

1.3 Deb Toolkit Get¶

Method of Obtaining	Get address
Baidu Cloud	https://pan.baidu.com/s/19rW0fPKUlQj6eldZpZFoAA Extraction code: a6ps
Google Drive	https://drive.google.com/open?id=1RsV2WEKAsfxbn-Z5nGjk5g3ml1UDEsDc

Installation¶

2.1 Installation Preparation¶

Ubuntu 16.04 LTS environment, x64 architecture
Deb package for the calibration tool, select OpenCV dependencies as needed (this step is not required for PPA installation)

2.2 Install ppa Package¶

$ sudo add-apt-repository ppa:slightech/mynt-eye-s-sdk
$ sudo apt-get update
$ sudo apt-get install mynteye-s-calibrator
$ sudo ln -sf /opt/myntai/mynteye-s-calibrator/mynteye-s-calibrator /usr/local/bin/ mynteye-s-calibrator

2.3 Install deb Package¶

Install the deb package with udo dpkg -i:

$ sudo dpkg -i mynteye-s-calibrator-opencv-official-1.0.0_amd64.deb
...
(Reading database ... 359020 files and directories currently installed.)
Preparing to unpack mynteye-s-calibrator-opencv-official-1.0.0_amd64.deb ...
Unpacking mynteye-s-calibrator (1.0.0) over (1.0.0) ...
Setting up mynteye-s-calibrator (1.0.0) ...

If you encounter an error that the dependency package is not installed, for example:

$ sudo dpkg -i mynteye-s-calibrator-opencv-official-1.0.0_amd64.deb
Selecting previously unselected package mynteye-s-calibrator.
(Reading database ... 358987 files and directories currently installed.)
Preparing to unpack mynteye-s-calibrator-opencv-official-1.0.0_amd64.deb ...
Unpacking mynteye-s-calibrator (1.0.0) ...
dpkg: dependency problems prevent configuration of mynteye-s-calibrator:
mynteye-s-calibrator depends on libatlas-base-dev; however:
Package libatlas-base-dev is not installed.
dpkg: error processing package mynteye-s-calibrator (--install):
dependency problems - leaving unconfigured
Errors were encountered while processing:
mynteye-s-calibrator

You can continue use sudo apt-get -f install to finished install

$ sudo apt-get -f install
Reading package lists... Done
Building dependency tree
Reading state information... Done
Correcting dependencies... Done
The following additional packages will be installed:
libatlas-base-dev
Suggested packages:
libblas-doc liblapack-doc
The following NEW packages will be installed:
libatlas-base-dev
0 upgraded, 1 newly installed, 0 to remove and 0 not upgraded.
1 not fully installed or removed.
Need to get 3,596 kB of archives.
After this operation, 30.8 MB of additional disk space will be used.
Do you want to continue? [Y/n]
Get:1 http://cn.archive.ubuntu.com/ubuntu xenial/universe amd64 libatlas-base-dev amd64 3.10.2-9 [3,596 kB]
Fetched 3,596 kB in 3s (1,013 kB/s)
Selecting previously unselected package libatlas-base-dev.
(Reading database ... 358993 files and directories currently installed.)
Preparing to unpack .../libatlas-base-dev_3.10.2-9_amd64.deb ...
Unpacking libatlas-base-dev (3.10.2-9) ...
Setting up libatlas-base-dev (3.10.2-9) ...
update-alternatives: using /usr/lib/atlas-base/atlas/libblas.so to provide /usr/lib/libblas.so (libblas.so) in auto mode
update-alternatives: using /usr/lib/atlas-base/atlas/liblapack.so to provide /usr/lib/liblapack.so (liblapack.so) in auto mode
Setting up mynteye-s-calibrator (1.0.0) ...

How To Use¶

3.1 Preparation For Use¶

MYNT EYE S Camera
Checkerboard
Evenly illuminated scene

3.2 Use Command¶

After installing the calibration tool, you can run the mynteye-s-calibrator command directly on the terminal to calibrate. -h can see its options:

$ mynteye-s-calibrator -h
Usage: mynteye-s-calibrator [options]
help: mynteye-s-calibrator -h
calibrate: mynteye-s-calibrator -x 11 -y 7 -s 0.036
Calibrate MYNT EYE S device.

Options:

-h, --help: show this help message and exit
-x WIDTH, --width=WIDTH: The chessboard width, default: 11
-y HEIGHT, --height=HEIGHT: The chessboard height, default: 7
-s METERS, --square=METERS: The chessboard square size in meters, default: 0.036
-n NUMBER, --number=NUMBER: The number of imagestools to use for calibration, default: 11
-p PATH, --path=PATH: The path to save the result, default: folder name using device’s SN

-x -y -s Used to set the width, height, and grid size of the calibration plate. Width and height refer to the number of black and white intersections in the horizontal and vertical directions of the checkerboard. Square size in meters.

3.3 Steps For Usage¶

First, connect the MYNT EYE S camera.
Then, run the mynteye-s-calibrator <calibration board parameter> command in the terminal.

Follow the prompts to select an index for the camera’s resolution, perform image calibration at this resolution
The S1030 camera only need calibrate 752*480 resolution. The S2100 camera need calibrate 2560*800 and 1280*400 resolutions.
As far as possible, let the calibration plate cover the left and right eye images of the camera,

and take care of the surroundings (maximum distortion). The calibration tool will automatically evaluate the qualified image for the calibration calculation and will indicate on the terminal how many have been selected.

Reference acquisition image, as follows:

Note: p_x, p_y, size, skew respectively indicate the scale of the calibration plate on the x-axis, y-axis, zoom, and tilt when the image is acquired. Make a point for reference.
Once the number of images acquired by the calibration needs is reached, the calibration calculation will be performed. The output is as follows:

1. The terminal will print out the left and right purpose calibration results.
1. The calibration results will be written into the files in <SN number> directory.
1. camera_left.yaml: Left eye parameter
2. camera_right.yaml: Right eye parameter
3. extrinsics.yaml: Binocular external parameter
4. img.params.equidistant: Camera parameters, which can be used for S SDK writing
5. stereo_reprojection_error.yaml: Reprojection error
Finally, you will also be asked if you want to write to the camera device. Enter or y to confirm

After writing to the device, you will be prompted with “Write to device done”.

3.4 Calibration result¶

Calibration result, It is desirable to have a reprojection error of 0.2 or less. If exceeds 1, it needs to be recalibrated.

Reprojection error, visible output after calibration completion “Final reprojection error: 0.201

Pixels”, or see the calibration result file “stereo_reprojection_error.yaml”.

OPEN SOURCE SUPPORT¶

How To Use In VINS-Mono ¶

If you wanna run VINS-Mono with MYNT EYE camera, please follow the steps:¶

Download MYNT-EYE-S-SDK and install mynt_eye_ros_wrapper.
Follow the normal procedure to install VINS-Mono.
Run mynt_eye_ros_wrapper and VINS-Mono.

Install ROS Kinetic conveniently (if already installed, please ignore)¶

cd ~
wget https://raw.githubusercontent.com/oroca/oroca-ros-pkg/master/ros_install.sh && \
chmod 755 ./ros_install.sh && bash ./ros_install.sh catkin_ws kinetic

Install Docker¶

sudo apt-get update
sudo apt-get install \
    apt-transport-https \
    ca-certificates \
    curl \
    gnupg-agent \
    software-properties-common
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
sudo add-apt-repository \
   "deb [arch=amd64] https://download.docker.com/linux/ubuntu \
   $(lsb_release -cs) \
   stable"
sudo apt-get update
sudo apt-get install docker-ce docker-ce-cli containerd.io

Then add your account to docker group by sudo usermod -aG docker $YOUR_USER_NAME . Relaunch the terminal or logout and re-login if you get Permission denied error.

To complie with docker,we recommend that you should use more than 16G RAM, or ensure that the RAM and virtual memory space is greater than 16G.

Install MYNT-EYE-VINS-Sample¶

git clone -b docker_feat https://github.com/slightech/MYNT-EYE-VINS-Sample.git
cd MYNT-EYE-VINS-Sample/docker
make build

Note that the docker building process may take a while depends on your network and machine. After VINS-Mono successfully started, open another terminal and play your bag file, then you should be able to see the result. If you need modify the code, simply run ./run.sh LAUNCH_FILE_NAME after your changes.

Run VINS-Mono with MYNT® EYE¶

Launch mynteye node

cd (local path of MYNT-EYE-S-SDK)
source ./wrappers/ros/devel/setup.bash
roslaunch mynt_eye_ros_wrapper vins_mono.launch

Open another terminal and run vins

cd path/to/MYNT-EYE-VINS-Sample/docker
./run.sh mynteye_s.launch
# ./run.sh mynteye_s2100.launch  # mono with s2100

How To Use In VINS-Fusion ¶

If you wanna run VINS-Fusion with MYNT EYE camera, please follow the steps:¶

Download MYNT-EYE-S-SDK and install mynt_eye_ros_wrapper.
Follow the normal procedure to install VINS-Fusion.
Run mynt_eye_ros_wrapper and VINS-Fusion.

Install ROS Kinetic conveniently (if already installed, please ignore)¶

cd ~
wget https://raw.githubusercontent.com/oroca/oroca-ros-pkg/master/ros_install.sh && \
chmod 755 ./ros_install.sh && bash ./ros_install.sh catkin_ws kinetic

Install Docker¶

sudo apt-get update
sudo apt-get install \
    apt-transport-https \
    ca-certificates \
    curl \
    gnupg-agent \
    software-properties-common
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
sudo add-apt-repository \
   "deb [arch=amd64] https://download.docker.com/linux/ubuntu \
   $(lsb_release -cs) \
   stable"
sudo apt-get update
sudo apt-get install docker-ce docker-ce-cli containerd.io

Then add your account to docker group by sudo usermod -aG docker $YOUR_USER_NAME . Relaunch the terminal or logout and re-login if you get Permission denied error.

To complie with docker,we recommend that you should use more than 16G RAM, or ensure that the RAM and virtual memory space is greater than 16G.

Install MYNT-EYE-VINS-FUSION-Samples¶

git clone https://github.com/slightech/MYNT-EYE-VINS-FUSION-Samples.git
cd MYNT-EYE-VINS-FUSION-Samples/docker
make build

Note that the docker building process may take a while depends on your network and machine. After VINS-Mono successfully started, open another terminal and play your bag file, then you should be able to see the result. If you need modify the code, simply run ./run.sh LAUNCH_FILE_NAME after your changes.

Run VINS-FUSION with MYNT® EYE¶

Launch mynteye node

cd (local path of MYNT-EYE-S-SDK)
source ./wrappers/ros/devel/setup.bash
roslaunch mynt_eye_ros_wrapper vins_fusion.launch

Open another terminal and run vins

cd path/to/MYNT-EYE-VINS-FUSION-Samples/docker
./run.sh mynteye-s/mynt_stereo_imu_config.yaml  # Stereo fusion
# ./run.sh mynteye-s2100/mynt_stereo_config.yaml # Stereo fusion with mynteye-s2100
# ./run.sh mynteye-s2100/mynt_stereo_imu_config.yaml # Stereo+imu fusion with mynteye-s2100

How To Use In ORB_SLAM2 ¶

If you wanna run ORB_SLAM2 with MYNT EYE camera, please follow the steps:¶

Download MYNT-EYE-S-SDK and follow steps to install.
Follow the normal procedure to install ORB_SLAM2.
Run examples by MYNT® EYE.

Prerequisites¶

sudo apt-get -y install libglew-dev cmake libgoogle-glog-dev
cd ~
git clone https://github.com/stevenlovegrove/Pangolin.git
cd Pangolin
mkdir build
cd build
cmake ..
cmake --build .
sudo make install

Building the nodes for mono and stereo (ROS)¶

Add the path including Examples/ROS/ORB_SLAM2 to the ROS_PACKAGE_PATH environment variable. Open .bashrc file and add at the end the following line.

export ROS_PACKAGE_PATH=${ROS_PACKAGE_PATH}:~/catkin_ws/src/MYNT-EYE-ORB-SLAM2-Sample

Execute build_ros.sh:

chmod +x build.sh
./build.sh
chmod +x build_ros.sh
./build_ros.sh

Stereo_ROS Example¶

Launch ORB_SLAM2 Stereo_ROS

Launch mynteye node

cd [path of mynteye-s-sdk]
make ros
source ./wrappers/ros/devel/setup.bash
roslaunch mynt_eye_ros_wrapper mynteye.launch

Open another terminal and run ORB_SLAM2

rosrun ORB_SLAM2 mynteye_s_stereo ./Vocabulary/ORBvoc.txt ./config/mynteye_s_stereo.yaml false /mynteye/left_rect/image_rect /mynteye/right_rect/image_rect

How To Use In OKVIS ¶

If you wanna run OKVIS with MYNT EYE camera, please follow the steps:¶

Download MYNT-EYE-S-SDK and install it.
Install dependencies and build MYNT-EYE-OKVIS-Sample follow the procedure of the original OKVIS.
Update camera parameters to <OKVIS>/config/config_mynteye.yaml.
Run OKVIS using MYNT® EYE.

Tip

OKVIS doesn’t support ARM right now

Install MYNTEYE OKVIS¶

First install dependencies based on the original OKVIS, and the follow:

sudo apt-get install libgoogle-glog-dev

git clone -b mynteye https://github.com/slightech/MYNT-EYE-OKVIS-Sample.git
cd MYNT-EYE-OKVIS-Sample/
mkdir build && cd build
cmake ..
make

Get camera calibration parameters¶

Through the GetIntrinsics() and GetExtrinsics() function of the MYNT-EYE-S-SDK API, you can get the camera calibration parameters of the currently open device, follow the steps:

cd MYNT-EYE-S-SDK
./samples/_output/bin/tutorials/get_img_params

After running the above type, pinhole’s distortion_parameters and projection_parameters is obtained , and then update to here .

Tip

You can get the camera model of device when get camera calibration parameters, if model is equidistant you need calibrate pinhole model by yourself or reference write_img_params to write a default pinhole config file to your device.

distortion_coefficients: [coeffs]   # only first four parameters of coeffs need to be filled
focal_length: [fx, fy]
principal_point: [cx, cy]
distortion_type: radialtangential

Run MYNTEYE OKVIS¶

Go to MYNT-EYE-OKVIS-Sample/build folder and Run the application okvis_app_mynteye_s :

cd MYNT-EYE-OKVIS-Sample/build
./okvis_app_mynteye_s ../config/config_mynteye_s.yaml

How To Use In VIORB ¶

If you wanna run VIORB with MYNT® EYE，please follow the steps:¶

Download MYNT-EYE-S-SDK and install mynt_eye_ros_wrapper.
Follow the normal procedure to install VIORB.
Update camera parameters to <VIO>/config/mynteye_s.yaml.
Run mynt_eye_ros_wrapper and VIORB.

Install MYNT-EYE-VIORB-Sample.¶

git clone -b mynteye https://github.com/slightech/MYNT-EYE-VIORB-Sample.git
cd MYNT-EYE-VIORB-Sample

ROS_PACKAGE_PATH environment variable. Open .bashrc file and add at the end the following line. Replace PATH by the folder where you cloned MYNT-EYE-VIORB-Sample:

export ROS_PACKAGE_PATH=${ROS_PACKAGE_PATH}:PATH/Examples/ROS/ORB_VIO

Execute:

cd MYNT-EYE-VIORB-Sample
./build.sh

Get image calibration parameters¶

Assume that the left eye of the mynteye camera is used with IMU. Through the GetIntrinsics() and GetExtrinsics() function of the MYNT-EYE-S-SDK API, you can get the image calibration parameters of the currently open device:

cd MYNT-EYE-S-SDK
./samples/_output/bin/tutorials/get_img_params

After running the above type, pinhole’s distortion_parameters and projection_parameters is obtained, and then update to <MYNT-EYE-VIORB-Sample>/config/mynteye.yaml.

Tip

You can get the camera model of device when get camera calibration parameters, if model is equidistant you need calibrate pinhole model by yourself or reference write_img_params to write a default pinhole config file to your device.

Run VIORB and mynt_eye_ros_wrapper¶

Launch mynteye node

roslaunch mynt_eye_ros_wrapper mynteye.launch

Open another terminal and run viorb

roslaunch ORB_VIO testmynteye_s.launch

Finally, pyplotscripts can be used to visualize some results.

How To Use In Maplab x¶

API DOCS¶

API¶

class API¶

The API class to communicate with MYNT® EYE device.

Public Types

using stream_callback_t = std::function<void(const api::StreamData &data)>¶: The api::StreamData callback.

using motion_callback_t = std::function<void(const api::MotionData &data)>¶: The api::MotionData callback.

using stream_switch_callback_t = std::function<void(const Stream &stream)>¶: The enable/disable switch callback.

Public Functions

Model GetModel() const¶: Get the model.

bool Supports(const Stream &stream) const¶: Supports the stream or not.

bool Supports(const Capabilities &capability) const¶: Supports the capability or not.

bool Supports(const Option &option) const¶: Supports the option or not.

bool Supports(const AddOns &addon) const¶: Supports the addon or not.

StreamRequest SelectStreamRequest(bool *ok) const¶: Log all stream requests and prompt user to select one.

const std::vector<StreamRequest> &GetStreamRequests(const Capabilities &capability) const¶: Get all stream requests of the capability.

void ConfigStreamRequest(const Capabilities &capability, const StreamRequest &request)¶: Config the stream request to the capability.

const StreamRequest &GetStreamRequest(const Capabilities &capability) const¶: Get the config stream requests of the capability.

const std::vector<StreamRequest> &GetStreamRequests() const¶: Get all stream requests of the key stream capability.

void ConfigStreamRequest(const StreamRequest &request)¶: Config the stream request to the key stream capability.

const StreamRequest &GetStreamRequest() const¶: Get the config stream requests of the key stream capability.

std::shared_ptr<DeviceInfo> GetInfo() const¶: Get the device info.

std::string GetInfo(const Info &info) const¶: Get the device info.

std::string GetSDKVersion() const¶: Get the sdk version.

IntrinsicsPinhole GetIntrinsics(const Stream &stream) const¶

Deprecated:: Get the intrinsics (pinhole) of stream.

template<typename T> T GetIntrinsics(const Stream &stream) const¶: Get the intrinsics of stream.

std::shared_ptr<IntrinsicsBase> GetIntrinsicsBase(const Stream &stream) const¶: Get the intrinsics base of stream.

Extrinsics GetExtrinsics(const Stream &from, const Stream &to) const¶: Get the extrinsics from one stream to another.

MotionIntrinsics GetMotionIntrinsics() const¶: Get the intrinsics of motion.

Extrinsics GetMotionExtrinsics(const Stream &from) const¶: Get the extrinsics from one stream to motion.

void LogOptionInfos() const¶: Log all option infos.

OptionInfo GetOptionInfo(const Option &option) const¶: Get the option info.

std::int32_t GetOptionValue(const Option &option) const¶: Get the option value.

void SetDisparityComputingMethodType(const DisparityComputingMethod &MethodType)¶: Set the disparity computing method.

void SetRectifyAlpha(const double &alpha)¶: Set the rectify bord cut alpha.

void setDuplicate(bool isEnable)¶: Set if the duplicate frames is enable.

void SetOptionValue(const Option &option, std::int32_t value)¶: Set the option value.

bool SetOptionValue(const Option &option, std::uint64_t value)¶: Set the option value.

bool RunOptionAction(const Option &option) const¶: Run the option action.

void SetStreamCallback(const Stream &stream, stream_callback_t callback)¶: Set the callback of stream.

void SetMotionCallback(motion_callback_t callback)¶: Set the callback of motion.

bool HasStreamCallback(const Stream &stream) const¶: Has the callback of stream.

bool HasMotionCallback() const¶: Has the callback of motion.

void Start(const Source &source)¶: Start capturing the source.

void Stop(const Source &source)¶: Stop capturing the source.

void WaitForStreams()¶: Wait the streams are ready.

void EnableStreamData(const Stream &stream)¶: Enable the data of stream.

Note

must enable the stream if it’s a synthetic one. This means the stream in not native, the device has the capability to provide this stream, but still support this stream.

void EnableStreamData(const Stream &stream, stream_switch_callback_t callback, bool try_tag = false)¶

Enable the data of stream.

callback function will call before the father processor enable. when try_tag is true, the function will do nothing except callback.

void DisableStreamData(const Stream &stream)¶: Disable the data of stream.

void DisableStreamData(const Stream &stream, stream_switch_callback_t callback, bool try_tag = false)¶

Disable the data of stream.

callback function will call before the children processor disable. when try_tag is true, the function will do nothing except callback.

api::StreamData GetStreamData(const Stream &stream)¶: Get the latest data of stream.

std::vector<api::StreamData> GetStreamDatas(const Stream &stream)¶: Get the datas of stream.

Note

default cache 4 datas at most.

void EnableMotionDatas(std::size_t max_size = std::numeric_limits<std::size_t>::max())¶: Enable cache motion datas.

std::vector<api::MotionData> GetMotionDatas()¶: Get the motion datas.

void EnableImuTimestampCorrespondence(bool is_enable)¶: enable motion datas timestamp correspondence in device.

void EnableTimestampCorrespondence(const Stream &stream, bool keep_accel_then_gyro = true)¶: Enable motion datas with timestamp correspondence of some stream in api.

void EnablePlugin(const std::string &path)¶: Enable the plugin.

void EnableProcessMode(const ProcessMode &mode)¶

Enable process mode, e.g.

imu assembly, temp_drift

void EnableProcessMode(const std::int32_t &mode)¶

Enable process mode, e.g.

imu assembly, temp_drift

std::shared_ptr<struct CameraROSMsgInfoPair> GetCameraROSMsgInfoPair()¶: Get ROS need camera info struct.

bool ConfigDisparityFromFile(const std::string &config_file)¶: Load disparity config from file.

Public Static Functions

static std::shared_ptr<API> Create(int argc, char *argv[])¶

Create the API instance.

Note

This will init glog with args and call device::select() to select a device.

Parameters

argc – the arg count.
argv – the arg values.

Returns

the API instance.

static std::shared_ptr<API> Create(int argc, char *argv[], const std::shared_ptr<Device> &device)¶

Create the API instance.

Note

This will init glog with args.

Parameters

argc – the arg count.
argv – the arg values.
device – the selected device.

Returns

the API instance.

static std::shared_ptr<API> Create(const std::shared_ptr<Device> &device)¶

Create the API instance.

Parameters: device – the selected device.
Returns: the API instance.

api::StreamData¶

struct StreamData¶

API stream data.

Public Members

std::shared_ptr<ImgData> img¶: ImgData.

cv::Mat frame¶: Frame.

std::shared_ptr<device::Frame> frame_raw¶: Raw frame.

std::uint16_t frame_id¶: Frame ID.

api::MotionData¶

struct MotionData¶

API motion data.

Public Members

std::shared_ptr<ImuData> imu¶: ImuData.

Device¶

class Device¶

The Device class to communicate with MYNT® EYE device.

Public Types

using stream_callback_t = device::StreamCallback¶: The device::StreamData callback.

using motion_callback_t = device::MotionCallback¶: The device::MotionData callback.

Public Functions

inline Model GetModel() const¶: Get the model.

bool Supports(const Stream &stream) const¶: Supports the stream or not.

bool Supports(const Capabilities &capability) const¶: Supports the capability or not.

bool Supports(const Option &option) const¶: Supports the option or not.

bool Supports(const AddOns &addon) const¶: Supports the addon or not.

const std::vector<StreamRequest> &GetStreamRequests(const Capabilities &capability) const¶: Get all stream requests of the capability.

void ConfigStreamRequest(const Capabilities &capability, const StreamRequest &request)¶: Config the stream request to the capability.

const StreamRequest &GetStreamRequest(const Capabilities &capability) const¶: Get the config stream requests of the capability.

const std::vector<StreamRequest> &GetStreamRequests() const¶: Get all stream requests of the key stream capability.

void ConfigStreamRequest(const StreamRequest &request)¶: Config the stream request to the key stream capability.

const StreamRequest &GetStreamRequest() const¶: Get the config stream requests of the key stream capability.

std::shared_ptr<DeviceInfo> GetInfo() const¶: Get the device info.

std::string GetInfo(const Info &info) const¶: Get the device info of a field.

std::shared_ptr<IntrinsicsBase> GetIntrinsics(const Stream &stream) const¶: Get the intrinsics of stream.

Extrinsics GetExtrinsics(const Stream &from, const Stream &to) const¶: Get the extrinsics from one stream to another.

MotionIntrinsics GetMotionIntrinsics() const¶: Get the intrinsics of motion.

Extrinsics GetMotionExtrinsics(const Stream &from) const¶: Get the extrinsics from one stream to motion.

std::shared_ptr<IntrinsicsBase> GetIntrinsics(const Stream &stream, bool *ok) const¶: Get the intrinsics of stream.

Extrinsics GetExtrinsics(const Stream &from, const Stream &to, bool *ok) const¶: Get the extrinsics from one stream to another.

MotionIntrinsics GetMotionIntrinsics(bool *ok) const¶: Get the intrinsics of motion.

Extrinsics GetMotionExtrinsics(const Stream &from, bool *ok) const¶: Get the extrinsics from one stream to motion.

void SetIntrinsics(const Stream &stream, const std::shared_ptr<IntrinsicsBase> &in)¶: Set the intrinsics of stream.

void SetExtrinsics(const Stream &from, const Stream &to, const Extrinsics &ex)¶: Set the extrinsics from one stream to another.

void SetMotionIntrinsics(const MotionIntrinsics &in)¶: Set the intrinsics of motion.

void SetMotionExtrinsics(const Stream &from, const Extrinsics &ex)¶: Set the extrinsics from one stream to motion.

void LogOptionInfos() const¶: Log all option infos.

OptionInfo GetOptionInfo(const Option &option) const¶: Get the option info.

std::int32_t GetOptionValue(const Option &option) const¶: Get the option value.

void SetOptionValue(const Option &option, std::int32_t value)¶: Set the option value.

bool SetOptionValue(const Option &option, std::uint64_t value)¶: Set the option value.

bool RunOptionAction(const Option &option) const¶: Run the option action.

void SetStreamCallback(const Stream &stream, stream_callback_t callback, bool async = false)¶: Set the callback of stream.

void SetMotionCallback(motion_callback_t callback, bool async = false)¶: Set the callback of motion.

bool HasStreamCallback(const Stream &stream) const¶: Has the callback of stream.

bool HasMotionCallback() const¶: Has the callback of motion.

virtual void Start(const Source &source)¶: Start capturing the source.

virtual void Stop(const Source &source)¶: Stop capturing the source.

void WaitForStreams()¶: Wait the streams are ready.

device::StreamData GetStreamData(const Stream &stream)¶: Get the latest data of stream.

device::StreamData GetLatestStreamData(const Stream &stream)¶

Deprecated:: Replaced by GetStreamData(const Stream &stream)

std::vector<device::StreamData> GetStreamDatas(const Stream &stream)¶: Get the datas of stream.

Note

default cache 4 datas at most.

void DisableMotionDatas()¶: Disable cache motion datas.

void EnableMotionDatas()¶: Enable cache motion datas.

void EnableImuCorrespondence(bool is_enable)¶: Enable motion datas timestamp correspondence.

void EnableMotionDatas(std::size_t max_size)¶: Enable cache motion datas.

std::vector<device::MotionData> GetMotionDatas()¶: Get the motion datas.

void EnableProcessMode(const ProcessMode &mode)¶

Enable process mode, e.g.

imu assembly, temp_drift

void EnableProcessMode(const std::int32_t &mode)¶

Enable process mode, e.g.

imu assembly, temp_drift

Public Static Functions

static std::shared_ptr<Device> Create(const std::string &name, std::shared_ptr<uvc::device> device)¶

Create the Device instance.

Parameters

name – the device name.
device – the device from uvc.

Returns

the Device instance.

device::Frame¶

class Frame¶

Frame with raw data.

Public Functions

inline Frame(const StreamRequest &request, const void *data)¶: Construct the frame with StreamRequest and raw data.

inline Frame(std::uint16_t width, std::uint16_t height, Format format, const void *data)¶: Construct the frame with stream info and raw data.

inline std::uint16_t width() const¶: Get the width.

inline std::uint16_t height() const¶: Get the height.

inline Format format() const¶: Get the format.

inline std::uint8_t *data()¶: Get the data.

inline const std::uint8_t *data() const¶: Get the const data.

inline std::size_t size() const¶: Get the size of data.

inline Frame clone() const¶: Clone a new frame.

device::StreamData¶

struct StreamData¶

Device stream data.

Public Members

std::shared_ptr<ImgData> img¶: ImgData.

std::shared_ptr<Frame> frame¶: Frame.

std::uint16_t frame_id¶: Frame ID.

device::MotionData¶

struct MotionData¶

Device motion data.

Public Members

std::shared_ptr<ImuData> imu¶: ImuData.

Enums¶

Model¶

enum mynteye::Model¶

Device model.

Values:

enumerator STANDARD¶: Standard.

enumerator STANDARD2¶: Standard 2.

enumerator STANDARD210A¶: Standard 210a.

enumerator STANDARD200B¶: Standard 200b.

Stream¶

enum mynteye::Stream¶

Streams define different type of data.

Values:

enumerator LEFT¶: Left stream.

enumerator RIGHT¶: Right stream.

enumerator LEFT_RECTIFIED¶: Left stream, rectified.

enumerator RIGHT_RECTIFIED¶: Right stream, rectified.

enumerator DISPARITY¶: Disparity stream.

enumerator DISPARITY_NORMALIZED¶: Disparity stream, normalized.

enumerator DEPTH¶: Depth stream.

enumerator POINTS¶: Point cloud stream.

Capabilities¶

enum mynteye::Capabilities¶

Capabilities define the full set of functionality that the device might provide.

Values:

enumerator STEREO¶: Provides stereo stream.

enumerator STEREO_COLOR¶: Provide stereo color stream.

enumerator COLOR¶: Provides color stream.

enumerator DEPTH¶: Provides depth stream.

enumerator POINTS¶: Provides point cloud stream.

enumerator FISHEYE¶: Provides fisheye stream.

enumerator INFRARED¶: Provides infrared stream.

enumerator INFRARED2¶: Provides second infrared stream.

enumerator IMU¶: Provides IMU (accelerometer, gyroscope) data.

Info¶

enum mynteye::Info¶

Camera info fields are read-only strings that can be queried from the device.

Values:

enumerator DEVICE_NAME¶: Device name.

enumerator SERIAL_NUMBER¶: Serial number.

enumerator FIRMWARE_VERSION¶: Firmware version.

enumerator HARDWARE_VERSION¶: Hardware version.

enumerator SPEC_VERSION¶: Spec version.

enumerator LENS_TYPE¶: Lens type.

enumerator IMU_TYPE¶: IMU type.

enumerator NOMINAL_BASELINE¶: Nominal baseline.

enumerator AUXILIARY_CHIP_VERSION¶: Auxiliary chip version.

enumerator ISP_VERSION¶: Isp version.

Option¶

enum mynteye::Option¶

Camera control options define general configuration controls.

Values:

enumerator GAIN¶

Image gain, valid if manual-exposure.

range: [0,48], default: 24

enumerator BRIGHTNESS¶

Image brightness, valid if manual-exposure.

range: [0,240], default: 120

enumerator CONTRAST¶

Image contrast, valid if manual-exposure.

range: [0,254], default: 116

enumerator FRAME_RATE¶

Image frame rate, must set IMU_FREQUENCY together.

values: {10,15,20,25,30,35,40,45,50,55,60}, default: 25

enumerator IMU_FREQUENCY¶

IMU frequency, must set FRAME_RATE together.

values: {100,200,250,333,500}, default: 200

enumerator EXPOSURE_MODE¶

Exposure mode.

0: enable auto-exposure

1: disable auto-exposure (manual-exposure)

enumerator MAX_GAIN¶

Max gain, valid if auto-exposure.

range of standard 1: [0,48], default: 48

range of standard 2: [0,255], default: 8

enumerator MAX_EXPOSURE_TIME¶

Max exposure time, valid if auto-exposure.

range of standard 1: [0,240], default: 240

range of standard 2: [0,655], default: 333

enumerator MIN_EXPOSURE_TIME¶

min exposure time, valid if auto-exposure

range: [0,655], default: 0

enumerator DESIRED_BRIGHTNESS¶

Desired brightness, valid if auto-exposure.

range of standard 1: [0,255], default: 192

range of standard 2: [1,255], default: 122

enumerator IR_CONTROL¶

IR control.

range: [0,160], default: 0

enumerator HDR_MODE¶

HDR mode.

0: normal

1: WDR

enumerator ACCELEROMETER_RANGE¶

The range of accelerometer.

value of standard 1: {4,8,16,32}, default: 8

value of standard 2: {6,12,24,48}, default: 12

enumerator GYROSCOPE_RANGE¶

The range of gyroscope.

value of standard 1: {500,1000,2000,4000}, default: 1000

value of standard 2: {250,500,1000,2000,4000}, default: 1000

enumerator ACCELEROMETER_LOW_PASS_FILTER¶

The parameter of accelerometer low pass filter.

values: {0,1,2}, default: 2

enumerator GYROSCOPE_LOW_PASS_FILTER¶

The parameter of gyroscope low pass filter.

values: {23,64}, default: 64

enumerator IIC_ADDRESS_SETTING¶

The setting of IIC address.

range: [0,127], default: 0

enumerator ZERO_DRIFT_CALIBRATION¶: Zero drift calibration.

enumerator ERASE_CHIP¶: Erase chip.

enumerator SYNC_TIMESTAMP¶: Sync timestamp.

Source¶

enum mynteye::Source¶

Source allows the user to choose which data to be captured.

Values:

enumerator VIDEO_STREAMING¶: Video streaming of stereo, color, depth, etc.

enumerator MOTION_TRACKING¶: Motion tracking of IMU (accelerometer, gyroscope)

enumerator ALL¶: Enable everything together.

AddOns¶

enum mynteye::AddOns¶

Add-Ons are peripheral modules of our hardware.

Values:

enumerator INFRARED¶: Infrared.

enumerator INFRARED2¶: Second infrared.

Format¶

enum mynteye::Format¶

Formats define how each stream can be encoded.

Values:

enumerator GREY¶: Greyscale, 8 bits per pixel.

enumerator YUYV¶: YUV 4:2:2, 16 bits per pixel.

enumerator BGR888¶: BGR 8:8:8, 24 bits per pixel.

enumerator RGB888¶: RGB 8:8:8, 24 bits per pixel.

CalibrationModel¶

enum mynteye::CalibrationModel¶

Camera calibration model.

Values:

enumerator PINHOLE¶: Pinhole.

enumerator KANNALA_BRANDT¶: Equidistant: KANNALA_BRANDT.

enumerator UNKNOW¶: Unknow.

DisparityComputingMethod¶

enum mynteye::DisparityComputingMethod¶

Camera disparity computing method type.

Values:

enumerator SGBM¶: bm

enumerator BM¶: sgbm

enumerator UNKNOW¶: unknow

Types¶

OptionInfo¶

struct OptionInfo¶

Option info.

Public Members

std::int32_t min¶: Minimum value.

std::int32_t max¶: Maximum value.

std::int32_t def¶: Default value.

Resolution¶

struct Resolution¶

Resolution.

Public Members

std::uint16_t width¶: Width.

std::uint16_t height¶: Height.

StreamRequest¶

struct StreamRequest¶

Stream request.

Public Members

std::uint16_t width¶: Stream width in pixels.

std::uint16_t height¶: Stream height in pixels.

Format format¶: Stream pixel format.

std::uint16_t fps¶: Stream frames per second.

Intrinsics¶

IntrinsicsPinhole¶

struct IntrinsicsPinhole : public mynteye::IntrinsicsBase¶

Stream intrinsics (Pinhole)

Public Members

double fx¶: The focal length of the image plane, as a multiple of pixel width.

double fy¶: The focal length of the image plane, as a multiple of pixel height.

double cx¶: The horizontal coordinate of the principal point of the image.

double cy¶: The vertical coordinate of the principal point of the image.

std::uint8_t model¶

Deprecated:: Replaced by calib_model_.

The distortion model of the image

double coeffs[5]¶: The distortion coefficients: k1,k2,p1,p2,k3.

IntrinsicsEquidistant¶

struct IntrinsicsEquidistant : public mynteye::IntrinsicsBase¶

Stream intrinsics (Equidistant: KANNALA_BRANDT)

Public Members

double coeffs[8]¶: The distortion coefficients: k2,k3,k4,k5,mu,mv,u0,v0.

ImuIntrinsics¶

struct ImuIntrinsics¶

IMU intrinsics: scale, drift and variances.

Public Members

double scale[3][3]¶

Scale matrix.

Scale X     cross axis  cross axis
cross axis  Scale Y     cross axis
cross axis  cross axis  Scale Z

double assembly[3][3]¶: Assembly error [3][3].

double drift[3]¶: Zero-drift: X, Y, Z.

double noise[3]¶: Noise density variances.

double bias[3]¶: Random walk variances.

double x[2]¶

Temperature drift.

0 - Constant value
1 - Slope

MotionIntrinsics¶

struct MotionIntrinsics¶

Motion intrinsics, including accelerometer and gyroscope.

Public Members

ImuIntrinsics accel¶: Accelerometer intrinsics.

ImuIntrinsics gyro¶: Gyroscope intrinsics.

Extrinsics¶

struct Extrinsics¶

Extrinsics, represent how the different datas are connected.

Public Functions

inline Extrinsics Inverse() const¶

Inverse this extrinsics.

Returns: the inversed extrinsics.

Public Members

double rotation[3][3]¶: Rotation matrix.

double translation[3]¶: Translation vector.

ImgData¶

struct ImgData¶

Image data.

Public Members

std::uint16_t frame_id¶: Image frame id.

std::uint64_t timestamp¶: Image timestamp in 1us.

std::uint16_t exposure_time¶: Image exposure time, virtual value in [1, 480].

bool is_ets = false¶: Is external time source.

ImuData¶

struct ImuData¶

IMU data.

Public Members

std::uint32_t frame_id¶: IMU frame id.

std::uint8_t flag¶

IMU accel or gyro flag.

0: accel and gyro are both valid

1: accel is valid

2: gyro is valid

bool is_ets = false¶: Is external time source.

std::uint64_t timestamp¶: IMU timestamp in 1us.

double accel[3]¶: IMU accelerometer data for 3-axis: X, Y, Z.

double gyro[3]¶: IMU gyroscope data for 3-axis: X, Y, Z.

double temperature¶: IMU temperature.

Utils¶

select¶

std::shared_ptr<Device> mynteye::device::select()¶

Detecting MYNT EYE devices and prompt user to select one.

Returns: the selected device, or nullptr if none.

select_request¶

MYNTEYE_NAMESPACE::StreamRequest mynteye::device::select_request(const std::shared_ptr<Device> &device, bool *ok)¶

List stream requests and prompt user to select one.

Returns: the selected request.

get_real_exposure_time¶

float mynteye::utils::get_real_exposure_time(std::int32_t frame_rate, std::uint16_t exposure_time)¶

Get real exposure time in ms from virtual value, according to its frame rate.

Parameters

frame_rate – the frame rate of the device.
exposure_time – the virtual exposure time.

Returns

the real exposure time in ms, or the virtual value if frame rate is invalid.

get_sdk_root_dir¶

std::string mynteye::utils::get_sdk_root_dir()¶: Get sdk root dir.

get_sdk_install_dir¶

std::string mynteye::utils::get_sdk_install_dir()¶: Get sdk install dir.

TECHNICAL SUPPORT¶

FAQ¶

If you have problems using MYNT EYE, please first check the following docs：

http://support.myntai.com/hc/

Contact Us¶

If you continue to encounter problems, please contact customer service.

http://support.myntai.com/hc/request/new/