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Release v3.9.0

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@github-actions github-actions released this 17 Aug 05:53
v3.9.0
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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 are ported over and have native support
    • Parsers have exposed runtime configuration changes via config messages
    • Python and C++ examples 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 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. The update function is accessible within the "danger zone" section
      • Using the provided flash_network_bootloader.py script. By default, the script flashes the user bootloader; use the -f flag to enable factory flashing
      • Using the CLI command depthai --flash <device_ip>. By default, the command flashes the user bootloader; use the -f flag to enable factory flashing
    • For more information, follow the tutorial 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 value for controlling the balance between cropping and retaining the full field of view
  • Depth colorization utility
    • Added dai::utility::colorizeDepthFrame in C++ and dai.utility.colorizeDepthFrame in Python
    • Supports ImgFrame, 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 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 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) 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 now selects supported resolutions from the connected camera features instead of assuming 1280 x 800
  • Added background_class and strides to NN Archive head metadata
  • Python bindings for NeuralNetwork, DetectionNetwork, and SpatialDetectionNetwork now use a common variant-based model argument
  • DetectionParser uses metadata-defined YOLO strides, and SegmentationParser uses the dedicated background-class field
  • Python message types now inherit common Buffer timestamp and sequence-number methods instead of declaring duplicate bindings
  • Examples:
    • Depth examples now use the unified Depth node where possible
    • The multi-device frame-sync example can encode synchronized streams as H.265
    • A Python example and a C++ example for printing bootloader versions have been added
  • Fixed MSVC builds that treated a DeviceNodeCRTP deprecation warning as an error
  • Updated the vcpkg baseline and explicitly use OpenCV 4 for macOS Homebrew builds
  • Embedded visualizer updated to 3.7.6:
    • Improved performance and stability

[RVC4] Luxonis OS compatibility

Integration tested with Luxonis OS 1.27.1, 1.30.1, and 1.33.0.

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