DepthAI Nodes

Overview

In DepthAI pipelines, Message objects are used to send information between Nodes. While DepthAI natively supports a variety of message and node types, some use cases—such as deploying custom AI models or executing specialized tasks—may require components beyond the built-in capabilities.To address these needs, we provide an open-source Python library called depthai-nodes. It offers custom elements fully compatible with DepthAI pipelines, differing only in that they execute on the host machine instead of on Luxonis device.The library consists of two primary modules: node and message, each serving distinct roles in pipeline composition. For more comprehensive documentation and examples, please refer to the library's GitHub repository.

Installation

The package is hosted on PyPI so it can be installed with pip:

Command Line

1pip install depthai-nodes

Modules

Node

The node module provides a collection of custom node objects that extend the functionality of standard DepthAI nodes. These nodes are grouped into parser, utility, and helper categories.

Parsers

Parser nodes are used to interpret the outputs of AI models. Their primary purpose is to encapsulate and abstract away postprocessing logic, allowing users to interact directly with clean, structured outputs. Thus, each parser node emits a DepthAI-compatible Message containing the parsed data.Below is an overview of the available parser nodes, along with their corresponding tasks and usage examples. We list only a small fraction of examples as many more are available on Luxonis Models. For detailed information on each individual parser, please refer to the Parser Node documentation.

Parser	Task	Usage Example
`YOLOExtendedParser`	Object Detection	YOLOv8 Instance Segmentation Nano, YOLOv8 Nano Pose Estimation
`YuNetParser`	Object Detection	YuNet
`SCRFDParser`	Object Detection	SCRFD Person detection
`MPPalmDetectionParser`	Object Detection	MediaPipe Palm Detection
`PPTextDetectionParser`	Object Detection	Paddle Text Detection
`ClassificationParser`	Classification	EfficientNet-Lite
`ClassificationSequenceParser`	Classification	Paddle Text Recognition
`SegmentationParser`	Segmentation	DeepLab-V3-Plus
`FastSAMParser`	Segmentation	FastSAM s
`KeypointParser`	Keypoints Detection	MediaPipe Hand Landmarker
`SuperAnimalParser`	Keypoints Detection	SuperAnimal Landmarker
`HRNetParser`	Keypoints Detection	Lite-HRNet
`XFeatMonoParser`	Feature Matching	XFeat
`XFeatStereoParser`	Feature Matching	XFeat
`LaneDetectionParser`	Other	Ultra Fast Lane Detection
`MLSDParser`	Other	M-LSD
`EmbeddingsParser`	Other	ArcFace
`RegressionParser`	Other	Head pose estimation
`MapOutputParser`	Other	Depth Anything V2
`ImageOutputParser`	Other	Zero-DCE

Utility & Helpers

This group includes nodes designed to assist with common tasks such as data processing, filtering, and pipeline management. It also contains abstract base nodes that serve as templates for building custom node implementations.Below is a brief overview of the available utility and helper nodes, along with their corresponding tasks and usage explanations. You can find more information about each individual node in the Utility & Helper Nodes documentation.

Parser	Task	Purpose
`BaseHostNode`	Abstract Class	Host node base class
`ApplyColormap`	Image Processing	Applies a colormap
`DepthMerger`	Image Processing	Merges depth and detections
`ImgFrameOverlay`	Image Processing	Overlays two images
`Tiling`	Image Processing	Divides frames into overlapping tiles
`TilesPatcher`	Image Processing	Patches detections from tiles back into the global frame
`ParsingNeuralNetwork`	Neural Network Processing	Creates a `NeuralNetwork` node and relevant parser(s) for the given model
`HostParsingNeuralNetwork`	Neural Network Processing	Host-side `ParsingNeuralNetwork` implementation
`ParserGenerator`	Neural Network Processing	Generates parsers from the given NN archive
`ImgDetectionsBridge`	Detection and Filtering	Transforms detections message
`ImgDetectionsFilter`	Detection and Filtering	Filters detections message
`GatherData`	Data Management	Gathers messages into one
`SnapsProducer`	Data Management	Creates and sends snaps (any message type)
`SnapsProducerFrameOnly`	Data Management	Creates and sends snaps (frame-only)

Message

The message module provides a set of custom message types that extend the standard DepthAI messages. These custom types make it easier to work with the outputs of various AI models and integrate them into visualization or processing pipelines.Here’s a quick overview of the available message types. You can find more information in the Message Type documentation.

Message Type	Stores
`Classifications`	Object class labels with probability scores
`Cluster`	A group of related points
`Clusters`	Multiple `Cluster` objects
`ImgDetectionExtended`	Bounding box with angle, label, keypoints, and confidence
`ImgDetectionsExtended`	Multiple `ImgDetectionExtended` objects; includes segmentation masks
`Keypoint`	A single keypoint with coordinates and probability
`Keypoints`	Multiple `Keypoint` objects
`Line`	Line coordinates with confidence
`Lines`	Multiple `Line` objects
`Map2D`	2D float array
`Prediction`	Single float value
`Predictions`	Multiple `Prediction` objects
`SegmentationMask`	2D integer array

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