Overview

Intel® RealSense™ SDK 2.0 is a cross-platform library for Intel® RealSense™ depth cameras (D400 & L500 series and the SR300).

:pushpin: For other Intel® RealSense™ devices (F200, R200, LR200 and ZR300), please refer to the latest legacy release.

The SDK allows depth and color streaming, and provides intrinsic and extrinsic calibration information. The library also offers synthetic streams (pointcloud, depth aligned to color and vise-versa), and a built-in support for record and playback of streaming sessions.

Developer kits containing the necessary hardware to use this library are available for purchase at store.intelrealsense.com. Information about the Intel® RealSense™ technology at www.intelrealsense.com

:open_file_folder: Don't have access to a RealSense camera? Check-out sample data

Update on Recent Changes to the RealSense Product Line

Intel has EOLed the LiDAR, Facial Authentication, and Tracking product lines. These products have been discontinued and will no longer be available for new orders.

Intel WILL continue to sell and support stereo products including the following: D410, D415, D430, , D401 ,D450 modules and D415, D435, D435i, D435f, D405, D455, D457 depth cameras. We will also continue the work to support and develop our LibRealSense open source SDK.

In the future, Intel and the RealSense team will focus our new development on advancing innovative technologies that better support our core businesses and IDM 2.0 strategy.

Building librealsense - Using vcpkg

You can download and install librealsense using the vcpkg dependency manager:

git clone https://github.com/Microsoft/vcpkg.git
cd vcpkg
./bootstrap-vcpkg.sh
./vcpkg integrate install
./vcpkg install realsense2

The librealsense port in vcpkg is kept up to date by Microsoft team members and community contributors. If the version is out of date, please create an issue or pull request on the vcpkg repository.

Download and Install

• Download - The latest releases including the Intel RealSense SDK, Viewer and Depth Quality tools are available at: latest releases. Please check the release notes for the supported platforms, new features and capabilities, known issues, how to upgrade the Firmware and more.

• Install - You can also install or build from source the SDK (on Linux \ Windows \ Mac OS \ Android \ Docker), connect your D400 depth camera and you are ready to start writing your first application.

Support & Issues: If you need product support (e.g. ask a question about / are having problems with the device), please check the FAQ & Troubleshooting section. If not covered there, please search our Closed GitHub Issues page, Community and Support sites. If you still cannot find an answer to your question, please open a new issue.

What’s included in the SDK:

Ready to Hack!

Our library offers a high level API for using Intel RealSense depth cameras (in addition to lower level ones). The following snippet shows how to start streaming frames and extracting the depth value of a pixel:

// Create a Pipeline - this serves as a top-level API for streaming and processing frames
rs2::pipeline p;

// Configure and start the pipeline
p.start();

while (true)
{
    // Block program until frames arrive
    rs2::frameset frames = p.wait_for_frames();

    // Try to get a frame of a depth image
    rs2::depth_frame depth = frames.get_depth_frame();

    // Get the depth frame's dimensions
    float width = depth.get_width();
    float height = depth.get_height();

    // Query the distance from the camera to the object in the center of the image
    float dist_to_center = depth.get_distance(width / 2, height / 2);

    // Print the distance
    std::cout << "The camera is facing an object " << dist_to_center << " meters away \r";
}

For more information on the library, please follow our examples, and read the documentation to learn more.

Contributing

In order to contribute to Intel RealSense SDK, please follow our contribution guidelines.

License

This project is licensed under the Apache License, Version 2.0. Copyright 2018 Intel Corporation

How to Contribute

This project welcomes third-party code via GitHub pull requests.

You are welcome to propose and discuss enhancements using project issues.

Branching Policy: The master branch is considered stable, at all times. The development branch is the one where all contributions must be merged before being promoted to master. If you plan to propose a patch, please commit into the development branch, or its own feature branch.

We recommend enabling travis-ci on your fork of librealsense to make sure the changes compile on all platforms and pass unit-tests.

In addition, please run pr_check.sh and api_check.sh under scripts directory. These scripts verify compliance with project's standards:

1. Every example / source file must refer to LICENSE
2. Every example / source file must include correct copyright notice
3. For indentation we are using spaces and not tabs
4. Line-endings must be Unix and not DOS style
5. Every API header file must be able to compile as the first included header (no implicit dependencies)

Most common issues can be automatically resolved by running ./pr_check.sh --fix

Please familirize yourself with the Apache License 2.0 before contributing.

Step-by-Step

1. Make sure you have git and cmake installed on your system. On Windows we recommend using Git Extensions for git bash.
2. Run git clone https://github.com/IntelRealSense/librealsense.git and cd librealsense
3. To align with latest status of the development branch, run:

git fetch origin
git checkout development
git reset --hard origin/development

1. git checkout -b name_of_your_contribution to create a dedicated branch
2. Make your changes to the local repository
3. Make sure your local git user is updated, or run git config --global user.email "email@example.com" and git config --global user.user "user" to set it up. This is the user & email that will appear in GitHub history.
4. git add -p to select the changes you wish to add
5. git commit -m "Description of the change"
6. Make sure you have a GitHub user and fork librealsense
7. git remote add fork https://github.com/username/librealsense.git with your GitHub username
8. git fetch fork
9. git push fork to push name_of_your_contribution branch to your fork
10. Go to your fork on GitHub at https://github.com/username/librealsense
11. Click the New pull request button
12. For base combo-box select development, since you want to submit a PR to that branch
13. For compare combo-box select name_of_your_contribution with your commit
14. Review your changes and click Create pull request
15. Wait for all automated checks to pass
16. The PR will be approved / rejected after review from the team and the community

To continue to new change, goto step 3. To return to your PR (in order to make more changes): 1. git stash 2. git checkout name_of_your_contribution 3. Repeat items 5-8 from the previous list 4. git push fork The pull request will be automatically updated

Comment about the Wrappers

It is very time consuming (and often impossible) for a single developer to test contributed functionality using all of the supported wrappers. There is no expectation of adding new functionality to all of the wrappers. One noteable exception is maintaining parity of public enumerations. Without strict maintanance it is easy for these lists to go out of sync and this can have serious runtime consequences.

For example, when adding new value to rs2_option enum, please also add it to: 1. The list of Matlab options under wrappers/matlab/option.m 2. The list of options for Unreal Engine integration 3. The list of options in the C# wrapper - wrappers/csharp/Intel.RealSense/Types/Enums/Option.cs 4. The list of Java options used for Android integration - wrappers/android/librealsense/src/main/java/com/intel/realsense/librealsense/Option.java 5. The list of options in the python wrapper

Once all are updated travis-ci will give clear indication that each of the wrappers is still passing compilation.