Readme

Important Notice

We are happy to announce that the RealSense GitHub repositories have been successfully migrated to the RealSenseAI organization. Please make sure to update your links to the new RealSenseAI organization for both cloning the repositories and accessing specific files within them.

https://github.com/IntelRealSense/librealsense --> https://github.com/realsenseai/librealsense

Note: A redirection from the previous name IntelRealSense is currently in place, but we cannot guarantee how long it will remain active. We recommend that all users update their references to point to the new GitHub location.

Branch Policy

We have updated our branch policy: From now on, we will also push beta releases to the master branch, so users can access up-to-date code and features. In the near future, beta binaries will also be pushed to public distribution servers (e.g., APT). The last validated official release can be found on our Releases page on GitHub.

Use Cases

Below are some of the many real-world applications powered by RealSense technology:

Why RealSense?

• High-resolution color and depth at close and long ranges
• Open source SDK with rich examples and wrappers (Python, ROS, C#, Unity and more...)
• Active developer community and defacto-standard 3D stereo camera for robotics
• Cross-platform support: Windows, Linux, macOS, Android, and Docker

Product Line

RealSense stereo depth products use stereo vision to calculate depth, providing high-quality performance in various lighting and environmental conditions.

Here are some examples of the supported models:

🛍️ Explore more stereo products

Getting Started

Start developing with RealSense in minutes using either method below.

1️. Precompiled SDK

This is the best option if you want to plug in your camera and get started right away.

1. Download the latest SDK bundle from the Releases page.
2. Connect your RealSense camera.
3. Run the included tools:
   • RealSense Viewer: View streams, tune settings, record and playback.
   • Depth Quality Tool: Measure accuracy and fill rate.

Setup Guides - precompiled SDK

<a href="./doc/distribution_linux.md"></a> <a href="./doc/distribution_windows.md"></a>

Note: For minor releases, we publish Debian packages as release artifacts that you can download and install directly.

2️. Build from Source

For a more custom installation, follow these steps to build the SDK from source.

1. Clone the repository and create a build directory:
   bashCopy

   git clone https://github.com/realsenseai/librealsense.git
   cd librealsense
   mkdir build && cd build
   

2. Run CMake to configure the build:
   bashCopy

   cmake ..
   

3. Build the project:
   bashCopy

   cmake --build .
   

Setup Guides - build from source

<a href="./doc/installation.md"></a> <a href="./doc/installation_jetson.md"></a> <a href="./doc/installation_windows.md"></a> <a href="./doc/installation_osx.md"></a>

Python Packages

Which should I use?

• Stable: pyrealsense2 — validated releases aligned with SDK tags (Recommended for most users).
• Beta: pyrealsense2-beta — fresher builds for early access and testing. Expect faster updates.

Install

pip install pyrealsense2 # Stable
pip install pyrealsense2-beta # Beta

Both packages import as pyrealsense2. Install only one at a time.

Ready to Hack!

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

C++

#include <librealsense2/rs.hpp>
#include <iostream>

int main() {
    rs2::pipeline p;                 // Top-level API for streaming & processing frames
    p.start();                       // Configure and start the pipeline

    while (true) {
        rs2::frameset frames = p.wait_for_frames();        // Block until frames arrive
        rs2::depth_frame depth = frames.get_depth_frame(); // Get depth frame
        if (!depth) continue;

        int w = depth.get_width(), h = depth.get_height();
        float dist = depth.get_distance(w/2, h/2);         // Distance to center pixel
        std::cout << "The camera is facing an object " << dist << " meters away\r";
    }
}

Python

import pyrealsense2 as rs

pipeline = rs.pipeline() # Create a pipeline
pipeline.start() # Start streaming

try:
    while True:
        frames = pipeline.wait_for_frames()
        depth_frame = frames.get_depth_frame()
        if not depth_frame:
            continue

        width, height = depth_frame.get_width(), depth_frame.get_height()
        dist = depth_frame.get_distance(width // 2, height // 2)
        print(f"The camera is facing an object {dist:.3f} meters away", end="\r")

finally:
    pipeline.stop() # Stop streaming

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

Supported Platforms

Operating Systems and Platforms

Programming Languages and Wrappers

For more platforms and wrappers look over here.

Full feature support varies by platform – refer to the release notes for details.

Community & Support

• 📚 Wiki & Docs
• 🐞 Report Issues- Found a bug or want to contribute? Read our contribution guidelines.

🔎 Looking for legacy devices (F200, R200, LR200, ZR300)? Visit the legacy release.