Rami Mouro 8a40ea5c87 fix(qualcomm): make install_cdi resolve QNN skels across BSP and Ubuntu/QAIRT layouts
The bundled CDI descriptors assume the Qualcomm Linux BSP filesystem layout
(/usr/lib/rfsa/adsp). On the equally-official Ubuntu image for RB3 Gen 2 /
Rubik Pi 3, the QAIRT apt packages board-select the Hexagon skels into
/usr/lib/dsp/cdsp and leave /usr/lib/rfsa/adsp as self-referential symlink
loops, so install_cdi silently dropped the skel mounts and NPU offload failed
silently at runtime (or a host-symlink workaround broke on reboot with an
ELOOP CDI mount error).

install_cdi.py now resolves each missing/broken mount from a fallback library
dir and rewrites it to the real file, injects ADSP_LIBRARY_PATH so the DSP
loader finds the skels, and warns loudly (with an optional --strict) when a
critical QNN/HTP library cannot be found instead of failing silently. Docs
updated to cover both images and a stronger verify step.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-30 10:48:44 -06:00
2026-06-04 17:07:12 -06:00
2026-03-20 07:24:34 -06:00
2026-05-20 08:36:49 -06:00
2026-05-01 11:25:26 -06:00
2026-01-01 09:56:09 -06:00

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Frigate NVR™ - Realtime Object Detection for IP Cameras

License: MIT

Translation status

[English] | 简体中文

A complete and local NVR designed for Home Assistant with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras.

Use of a GPU or AI accelerator is highly recommended. AI accelerators will outperform even the best CPUs with very little overhead. See Frigate's supported object detectors.

  • Tight integration with Home Assistant via a custom component
  • Designed to minimize resource use and maximize performance by only looking for objects when and where it is necessary
  • Leverages multiprocessing heavily with an emphasis on realtime over processing every frame
  • Uses a very low overhead motion detection to determine where to run object detection
  • Object detection with TensorFlow runs in separate processes for maximum FPS
  • Communicates over MQTT for easy integration into other systems
  • Records video with retention settings based on detected objects
  • 24/7 recording
  • Re-streaming via RTSP to reduce the number of connections to your camera
  • WebRTC & MSE support for low-latency live view

Documentation

View the documentation at https://docs.frigate.video

Donations

If you would like to make a donation to support development, please use Github Sponsors.

License

This project is licensed under the MIT License.

  • Code: The source code, configuration files, and documentation in this repository are available under the MIT License. You are free to use, modify, and distribute the code as long as you include the original copyright notice.
  • Trademarks: The "Frigate" name, the "Frigate NVR" brand, and the Frigate logo are trademarks of Frigate, Inc. and are not covered by the MIT License.

Please see our Trademark Policy for details on acceptable use of our brand assets.

Screenshots

Live dashboard

Live dashboard

Streamlined review workflow

Streamlined review workflow

Multi-camera scrubbing

Multi-camera scrubbing

Built-in mask and zone editor

Built-in mask and zone editor

Translations

We use Weblate to support language translations. Contributions are always welcome.

Translation status

Copyright © 2026 Frigate, Inc.

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