Frigate is a production-grade, full-stack Network Video Recorder (NVR) with real-time AI object detection. It ingests IP camera streams, performs motion detection, object detection (via TFLite/ONNX/OpenVINO/TensorRT on CPU/GPU/NPU), tracking, and recording. The backend is Python with FastAPI, Peewee ORM, and ZMQ-based inter-process communication. The frontend is a React/TypeScript single-page application with live views, timeline review, config editing, and GenAI enrichments (face recognition, license plates, semantic search, chat). It supports hardware acceleration across a wide range of devices (Coral, Intel iGPU, NVIDIA Jetson, Hailo, Rockchip NPU, etc.) and integrates deeply with Home Assistant. While primarily an application, it contains substantial data/research components including ML model runners, embedding pipelines, and post-processing logic for classification and transcription.
openHASP is an embedded firmware framework for home automation touch panels, built around LVGL for GUI rendering. It provides a configurable dashboard for controlling IoT devices via MQTT, with support for ESP32, STM32, and other microcontrollers. The system features hardware abstraction layers for displays and touch controllers, modular services (MQTT, HTTP, FTP, Telnet, WireGuard VPN), OTA updates, and a JSON-based configuration system. It integrates with home automation platforms like Home Assistant through auto-discovery and state topics, while offering local UI interaction via touchscreen. The architecture separates concerns into HAL, GUI, networking, storage, and services, enabling cross-platform deployment.
Awesome Home Assistant is a community-curated index (an awesome list) of third-party resources for the Home Assistant home automation platform. The repository contains a single massive README.md that serves as the canonical list, organized into sections for custom integrations, dashboard cards, themes, apps, DIY projects, community resources, and more. It is not a software application itself but a well-maintained documentation and curation project with a set of Python maintenance scripts and GitHub Actions workflows that validate entries, check for broken links, refresh star counts, and generate a static website via MkDocs. The repository is designed for contributors to propose additions via pull requests; automated checks enforce entry quality criteria (license, age, activity).