# zed-sdk **Repository Path**: phenixcode/zed-sdk ## Basic Information - **Project Name**: zed-sdk - **Description**: No description available - **Primary Language**: Unknown - **License**: MIT - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2025-07-07 - **Last Updated**: 2025-11-28 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README
The ZED SDK is a cross-platform library designed to get the best out of the ZED cameras.
In this project, we provide tutorials and code samples to get started using the ZED SDK API.
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--- :tada: The **ZED SDK 5.1** is released! **ZED SDK 5.1** introduces a fully reworked **image capture** and **recording** pipeline delivering **stability**, **maximum performance**, and **reliability**. It adds **Jetson Thor support**, delivering up to **2.5× higher performance**. An **extra-close depth range** is now supported. **Streaming latency** is significantly reduced, ensuring smoother real-time operation. A redesigned **Virtual Stereo workflow for ZED X One** now achieves up to **60% lower CPU usage**. **OpenCV fisheye calibration** is now supported natively, and the new **ZED Studio** app unifies camera, stream, and SVO management. Improved **Positional Tracking** boosts **robustness**, introduces a **2D mode**, and refines **statuses**. Expanded support for **CUDA 13**, **JetPack 7**, **Python 3.14**, and **C++17/20** makes **ZED SDK 5.1** faster, more stable, and ready for the next generation of robotics and spatial AI. Please check the [Release Notes](https://www.stereolabs.com/developers/release/) of the latest version for more details. ## Overview Depth Sensing | Object Detection | Body Tracking | :------------: | :----------: | :-------------: | [](https://www.stereolabs.com/docs/depth-sensing) | [](https://www.stereolabs.com/docs/object-detection) | [](https://www.stereolabs.com/docs/body-tracking) | Positional Tracking | Global Localization | Spatial Mapping | :------------: | :----------: | :-------------: | [](https://www.stereolabs.com/docs/positional-tracking/) | [](/global%20localization) | [](https://www.stereolabs.com/docs/spatial-mapping) | Camera Control | Plane Detection | Multi Camera Fusion | :------------: | :----------: | :-------------: | [](https://www.stereolabs.com/docs/video/camera-controls/) | [](https://www.stereolabs.com/docs/spatial-mapping/plane-detection/) | [](/fusion) | ## Why ZED? - 🎯 End-to-end spatial perception platform for human-like sensing capabilities. - ⚡ Real-time performance: all algorithms of the ZED SDK are designed and optimized to run in real-time. - 📷 Reduce time-to-market with our comprehensive, ready-to-use hardware and software designed for multiple applications. - 📖 User-friendly and intuitive, with easy-to-use integrations and well-documented API for streamlined development. - 🛠️ Wide range of supported platforms, from desktop to embedded PCs. ## Getting started The ZED SDK contains all the libraries that power your camera along with tools that let you experiment with its features and settings. To get started: - [Get a ZED from the Stereolabs Store](https://store.stereolabs.com/) - [Download the ZED SDK](https://www.stereolabs.com/developers/release/#downloads) - [Install the ZED SDK](https://www.stereolabs.com/docs/installation/) on [Windows](https://www.stereolabs.com/docs/installation/windows/), [Linux](https://www.stereolabs.com/docs/installation/linux/) or [Jetson](https://www.stereolabs.com/docs/installation/jetson/) - [Start experimenting with the ZED SDK's tutorials](/tutorials) The [documentation](https://www.stereolabs.com/docs/) and [API reference](https://www.stereolabs.com/docs/api/) are great starting points to learn more about the ZED SDK and its many modules. ## Samples This repository contains ready-to-use and samples to start using the ZED SDK with only a few lines of code. They are organized by ZED SDK module: * [**Tutorials**](/tutorials) - A series of basic tutorials that demonstrate the use of each API module. * [**Camera Control**](/camera%20control) - This sample shows how to adjust the **ZED camera parameters**. * [**Camera Streaming**](/camera%20streaming) - This sample shows how to **stream** and receive on local network the ZED's video feed. * [**Depth Sensing**](/depth%20sensing) - This sample shows how to capture a **3D point cloud** and display with OpenGL. It also shows how to save depth data in different formats. * [**Positional Tracking**](/positional%20tracking) - This sample shows how to use **positional tracking** and display the result with *OpenGL*. * [**Global Localization**](/global%20localization) - This sample shows how to fuse the ZED SDK's **positional tracking with GNSS data** for global positioning. * [**Spatial Mapping**](/spatial%20mapping) - This sample shows how to capture **3D meshes** with the ZED and display it with *OpenGL*. Classic Mesh and Point Cloud fusion are available. * [**Object Detection**](/object%20detection) - This sample shows how to use the **Object Detection API** module with the ZED. * [**Body Tracking**](/body%20tracking) - This sample shows how to use the **Body Tracking API** with the ZED. * [**Recording**](/recording) - This sample shows how to **record** and **playback** video files in SVO format. SVO files let you use all the ZED SDK features without having a ZED connected. ## Supported platforms Here is the list of all supported operating systems for the latest version of the ZED SDK. Please find the [recommended specifications](https://www.stereolabs.com/docs/installation/specifications/) to make sure your configuration is compatible with the ZED SDK. | Ubuntu LTS | Windows | Jetson | | -------- | ------------------------- | ----------------- | | | | The ZED SDK requires the use of an **NVIDIA GPU** with a **Compute Capability > 5**. If you are not familiar with the corresponding versions between NVIDIA JetPack SDK and Jetson Linux, please take a look at our [blog post](https://www.stereolabs.com/blog/nvidia-jetson-l4t-and-jetpack-support/). ## Integrations The ZED SDK can be easily integrated into projects using the following programming languages: | C++ | Python | C# | C | | -------- | ------------------------- | ----------------- | -------- | | | | |