DepthAI Library

DepthAI library for interfacing with Luxonis DepthAI hardware. It’s written in C++ and offers Python bindings out of the box.

Important — You’re viewing the v3.x.y branch.

• For production projects that still rely on v2, check out the v2_stable branch.
• Need to migrate? Follow the step-by-step v2 → v3 Porting Guide.

Documentation

Documentation is available over at Luxonis DepthAI API

Examples

Examples for both C++ and Python are available in the examples folder. To see how to build and run them see README.md for more information. To build the examples in C++ configure with the following option added:

cmake -S. -Bbuild -D'DEPTHAI_BUILD_EXAMPLES=ON'
cmake --build build

Beta features

The beta namespace is a staging area for experimental DepthAI features. It allows new features to be developed and iterated on quickly before they are promoted to the main depthai namespace.

Beta features are well-developed, but minor API and behavioral changes may occur between DepthAI releases without notice.

In C++, beta nodes are available under dai::beta::node:

auto node = pipeline.create<dai::beta::node::ImgDetectionsFilter>();

In Python, they are available under dai.beta.node:

node = pipeline.create(dai.beta.node.ImgDetectionsFilter)

On-device execution of Beta nodes is supported only on RVC4. If running Beta nodes on RVC2, DepthAI automatically configures beta nodes to run on the host.

Dependencies

• CMake >= 3.20
• C/C++17 compiler
• [Linux] libudev >= 1.0.0
• [optional] OpenCV 4 (required if building examples and for record and replay)
• [optional] PCL (required for point cloud example)

To install libudev on Debian based systems (Ubuntu, etc.): sudo apt install libudev-dev

To install OpenCV: MacOS: brew install opencv Linux: sudo apt install libopencv-dev Windows: choco install opencv

To install PCL: MacOS: brew install pcl Linux: sudo apt install libpcl-dev

Using Python bindings

Installing the latest pre-released version of the library can be done with:

python3 -m pip install --extra-index-url https://artifacts.luxonis.com/artifactory/luxonis-python-release-local/ --pre -U depthai

or by running:

python3 examples/python/install_requirements.py on the branch you want to install

For more specific information about Python bindings, see Python README.

Building

Make sure submodules are updated

git submodule update --init --recursive

Then configure and build

cmake -S . -B build
cmake --build build --parallel [num CPU cores]

On Windows it’s often required to specify the location of the OpenCV installation. In case you used chocolatey to install OpenCV, you can use the following command:

cmake -S . -B build -DOpenCV_DIR=C:/tools/opencv/build -DCMAKE_BUILD_TYPE=Release
cmake --build build --config Release --parallel [num CPU cores]

ℹ️ To speed up build times, use cmake --build build --parallel [num CPU cores].

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Changelog for package depthai

3.9.0 (2026-08-17)

## Features

• Beta features namespace
  • Staging area for experimental DepthAI nodes and features
  • Enables faster support for features whose public API may change without prior notice
  • All nodes run natively on RVC4 and on the host for RVC2
  • All parsers and unique messages from [depthai_nodes]{.title-ref} are ported over and have native support
  • Parsers have exposed runtime configuration changes via config messages
  • [Python](https://github.com/luxonis/depthai-core/tree/main/examples/python/Beta) and [C++ examples](https://github.com/luxonis/depthai-core/tree/main/examples/cpp/Beta) are available
• [_RVC2_] PoE Bootloader update
  • Embedded Bootloader version updated to v0.0.29
  • Greatly improves RVC2 PoE device discoverability by fixing stale connection information that could result in [X_LINK_DEVICE_NOT_FOUND]{.title-ref} errors
  • The bootloader is backward- and forward-compatible and independent of the DepthAI version
  • Updating the recoverable _user bootloader is recommended for devices with frequent discovery failures. For full integration, we recommend flashing the _factory bootloader.
  • The following three flashing paths are available:
    • For a GUI experience, use [device_manager.py](https://github.com/luxonis/depthai-core/blob/main/utilities/device_manager.py). The update function is accessible within the "danger zone" section
    • Using the provided [flash_network_bootloader.py](https://github.com/luxonis/depthai-core/blob/main/utilities/flash_network_bootloader.py) script. By default, the script flashes the _user bootloader; use the [-f]{.title-ref} flag to enable factory flashing
    • Using the CLI command [depthai --flash <device_ip>]{.title-ref}. By default, the command flashes the _user bootloader; use the [-f]{.title-ref} flag to enable factory flashing
  • For more information, follow the [tutorial](https://docs.luxonis.com/software-v3/depthai/depthai-components/bootloader) in our docs
• [_RVC4_] Alpha parameter for image undistortion
  • StereoDepth node now properly handles alpha scaling of undistortion on RVC4
  • Camera output requests now accept an optional [alphaScaling]{.title-ref} value for controlling the balance between cropping and retaining the full field of view
• Depth colorization utility
  • Added [dai::utility::colorizeDepthFrame]{.title-ref} in C++ and [dai.utility.colorizeDepthFrame]{.title-ref} in Python
  • Supports [ImgFrame]{.title-ref}, OpenCV matrices, configurable depth ranges and color maps, and logarithmic or linear scaling
  • Can automatically derive visualization bounds from valid depth pixels and render invalid pixels as black
• [*RVC4*] VideoEncoder improvements
  • Improved latency for 4000 x 3000 H.264, H.265, and MJPEG encoding
  • Fixed an issue where [setKeyframeFrequency]{.title-ref} had no effect on RVC4

## Bug fixes

• [*RVC4*] 480 FPS mode
  • Fixed a regression from 3.7.1 where the ImageManip pool size was too small to properly support 480 FPS HFR mode
  • ImageManip can now grow its output pool when it is running low on frames
  • Added [setMaxPoolSize]{.title-ref} to cap the maximum output-pool size
• [_RVC2] Added a total power limit for DOT and FLOOD projectors to avoid power resets on the RVC2 ToF 63D sensor
• [RVC2] SpatialLocationCalculator now remaps regions of interest correctly when the depth input is not aligned
• Fixed YOLOv6 and YOLOv6-R1 decoding, including stride-based box reconstruction and confidence handling
• Rectification now uses the transformations carried by its input frames and reinitializes when those transformations change
• Fixed ImageManip four-point transform did not account for normalized coordinates
• Fixed colorization flicker and inconsistent frame rates in the ToF examples
• ReplayVideo now reports a runtime error when FFmpeg cannot open a video instead of relying on an assertion

## Misc

• Added a [getConnectedCameras(CameraSensorType)]{.title-ref} overload for filtering connected cameras by sensor type
• Reworked stereo-pair discovery to consider only connected and calibrated cameras with compatible sensors, valid extrinsics, and suitable orientation
  • Stereo pairs are now ordered by descending baseline length
• [cam_test.py]{.title-ref} now selects supported resolutions from the connected camera features instead of assuming 1280 x 800

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