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.

Multiple devices in one pipeline

A single dai::Pipeline can drive several devices. Devices become part of the pipeline explicitly with addDevice(...) or implicitly when a node is created with an explicit device; the first device becomes the master (default device) used by nodes created without one.

pipeline = dai.Pipeline(False)                    # no implicit device
devA = pipeline.addDevice("10.0.0.10")            # promoted to master
devB = pipeline.addDevice("10.0.0.11")

camA = pipeline.create(dai.node.Camera).build(dai.CameraBoardSocket.CAM_A)          # master
camB = pipeline.create(dai.node.Camera, device=devB).build(dai.CameraBoardSocket.CAM_A)

sync = pipeline.create(dai.node.Sync)             # host Sync aligns both streams
sync.setRunOnHost(True)
camA.requestOutput((640, 400)).link(sync.inputs["a"])
camB.requestOutput((640, 400)).link(sync.inputs["b"])

Key behaviors:

• Device-to-device links. Linking an output on device A to an input on device B inserts a host relay automatically at build time.
• Partial operation. Losing one device leaves its streams idle while the rest of the pipeline keeps running; the lost device reconnects on its own. Observe this via pipeline.getDeviceState(device) and pipeline.setDeviceStateCallback(...). The pipeline stops itself only when the last device is gone or when a device that consumes another device’s streams is lost for good. Call pipeline.setStopOnDeviceLoss(True) to stop when any device that runs a node is lost for good (reconnection exhausted); with device.setMaxReconnectionAttempts(0) it stops as soon as the disconnect is detected.
• Time. getTimestamp() values are host-clock based and comparable across devices; per-device getTimestampDevice() values are not (a host Sync node rejects the DEVICE timestamp source across devices at build).
• Source devices. After build, a host node can ask input.getSourceDevice() / inputs.getSourceDevices() which device produces each of its inputs.
• Per-device configuration. Every pipeline-level device setter/getter has a (device, ...) overload; the form without a device targets the master.
• Holistic record/replay is not supported with more than one device yet.

See examples/{cpp,python}/.../MultiDevice/ for frame sync, a device-to-device relay and a multi-device host node.

Running on the device (standalone)

The pipeline process may itself run on an RVC4 and use the local device over shared memory, with further devices attached over the network:

```python local = pipeline.addDevice(dai.DeviceInfo.local()) # this RVC4, no search timeout remote = pipeline.addDevice(“10.0.0.11”) # a remote device over TCP

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