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NVR with realtime local object detection for IP cameras
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Classification Model UI Refactor (#20602) 
* Add cutoff for object classification

* Add selector for classifiction model type

* Improve model selection view

* Clean up design of classification card

* Tweaks

* Adjust button colors

* Improvements to gradients and making face library consistent

* Add basic classification model wizard

* Use relative coordinates

* Properly get resolution

* Clean up exports

* Cleanup

* Cleanup

* Update to use pre-defined component for image shadow

* Refactor image grouping

* Clean up mobile

* Clean up decision logic

* Remove max check on classification objects

* Increase default number of faces shown

* Cleanup

* Improve mobile layout

* Clenaup

* Update vocabulary

* Fix layout

* Fix page

* Cleanup

* Choose last item for unknown objects

* Move explore button

* Cleanup grid

* Cleanup classification

* Cleanup grid

* Cleanup

* Set transparency

* Set unknown

* Don't filter all configs

* Check length
2025-10-22 07:36:09 -06:00
.cspell Fixes (#18304) 2025-05-19 14:43:22 -06:00
.devcontainer Initial implementation of D-FINE model via ONNX (#16772) 2025-02-24 08:56:01 -07:00
.github [Init] Initial commit for Synaptics SL1680 NPU (#19680) 2025-09-26 07:07:12 -05:00
.vscode Fix vscode launch configuration (#13795) 2024-09-17 10:42:10 -05:00
config Improve the devcontainer experience (#3492) 2022-11-20 07:34:12 -06:00
docker Add support for Intel NPU (#20536) 2025-10-17 05:58:59 -05:00
docs Classification Model UI Refactor (#20602) 2025-10-22 07:36:09 -06:00
frigate Classification Model UI Refactor (#20602) 2025-10-22 07:36:09 -06:00
migrations Semantic Search Triggers (#18969) 2025-08-16 10:20:33 -05:00
notebooks Update YOLO_NAS_Pretrained_Export.ipynb (#19669) 2025-08-20 14:59:43 -05:00
web Classification Model UI Refactor (#20602) 2025-10-22 07:36:09 -06:00
.dockerignore Improve the devcontainer experience (#3492) 2022-11-20 07:34:12 -06:00
.gitignore Removed usage of PyYAML for config parsing. (#13883) 2024-09-22 10:56:57 -05:00
.pylintrc use fstr log style 2021-02-25 07:01:59 -06:00
audio-labelmap.txt Audio events (#6848) 2023-07-01 08:18:33 -05:00
benchmark_motion.py use a different method for blur and contrast to reduce CPU (#6940) 2023-06-30 07:27:31 -05:00
benchmark.py Fix go2rtc init (#18708) 2025-08-16 10:20:33 -05:00
CODEOWNERS Initial support for Hailo-8L (#12431) 2024-08-29 20:19:50 -06:00
cspell.json Work through most of the cspell warnings in python (#13794) 2024-09-17 10:41:46 -05:00
docker-compose.yml Devcontainer: update Mosquitto from 1.6 to 2.0 (#17415) 2025-03-27 10:33:49 -06:00
generate_config_translations.py Add script to generate english config translation file from config (#20301) 2025-10-01 07:39:43 -05:00
labelmap.txt Cleanup Detector labelmap (#4932) 2023-01-06 07:03:16 -06:00
LICENSE switch to MIT license 2020-07-26 12:07:47 -05:00
Makefile Fixes (#19984) 2025-09-09 06:17:56 -06:00
netlify.toml Docs improvements (#8641) 2023-11-18 08:04:43 -06:00
package-lock.json Implement support for notifications (#12523) 2024-08-29 20:19:50 -06:00
process_clip.py Improve async object detector support (#17712) 2025-04-15 08:55:38 -05:00
pyproject.toml Fix various typing issues (#18187) 2025-05-13 08:27:20 -06:00
README_CN.md Add Chinese community sponsors (#18945) 2025-07-04 14:32:48 -05:00
README.md Small Tweaks (#17652) 2025-04-11 08:21:01 -06:00

README.md

logo

Frigate - NVR With Realtime Object Detection for IP Cameras

Translation status 
English

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 such as a Google Coral or Hailo is highly recommended. AI accelerators will outperform even the best CPUs with very little overhead.

  • 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.

Screenshots

Live dashboard

Live dashboard

Streamlined review workflow

Streamlined review workflow

Multi-camera scrubbing

Multi-camera scrubbing

Built-in mask and zone editor

Multi-camera scrubbing

Translations

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

Translation status