Open-source alternatives to Scrypted

Homebridge is a Node.js home automation server that acts as a bridge to expose non-native smart home devices to Apple HomeKit. It functions as a plugin-based framework that maps proprietary device APIs to standardized home automation services and protocols. The system utilizes a modular plugin architecture and a protocol emulation layer to make third-party hardware appear as native accessories. It further supports cross-platform compatibility by acting as a Matter device bridge, allowing Matter-standard hardware to connect to various home automation controllers. The software includes a web i

Moonfire-NVR is a self-hosted network video recorder designed to capture, archive, and manage video streams from IP cameras. It functions as a security surveillance platform that provides a web-based interface for monitoring live feeds, browsing historical recordings, and exporting specific video clips for review. The system distinguishes itself by recording H.264 and H.265 video streams directly to disk without re-encoding, which minimizes CPU usage and preserves original stream quality. It utilizes on-the-fly container remuxing to construct standard media files from stored segments, allowin

TeslaMate is a self-hosted system for recording and archiving telemetry from Tesla vehicles to a local database. It functions as a vehicle data logger and telemetry dashboard designed to maintain a complete history of driving and vehicle state data locally. The system includes a vehicle charging cost tracker to monitor the financial cost of charging sessions based on energy usage and electricity rates. It also features a geofencing location manager for defining custom geographic boundaries to automatically label visited locations and a home automation data broker that publishes real-time vehi

This project is a curated collection of deployment files and configurations for hosting a wide variety of open-source services on a home server. It primarily utilizes Docker and Docker Compose to automate the orchestration, lifecycle management, and deployment of containerized applications. The repository provides a comprehensive suite for self-hosted infrastructure, covering network management tools, media streaming, and home automation. It includes specialized configurations for securing internal services via reverse proxies, WireGuard VPN tunnels, and automated SSL/TLS certificate manageme

This project is a PyTorch implementation of the EfficientDet architecture designed for real-time object detection. It provides a neural network and inference engine capable of identifying and locating multiple objects within images or video streams. The implementation includes pretrained computer vision models with optimized weights, enabling immediate inference and fine-tuning without the need for training from scratch. The project covers the full pipeline for computer vision model optimization, including custom object detection training and model weight optimization. It incorporates struct

YOLOv9 is a real-time computer vision framework and deep learning model designed for image classification, object detection, and instance segmentation. It functions as both a vision model and a trainer, allowing for the optimization of neural network weights on custom datasets using single or multiple GPUs. The framework utilizes programmable gradient information to perform high-speed identification and location of multiple objects within images and video streams. It extends beyond bounding box detection to provide instance segmentation and panoptic segmentation, which labels every pixel in a

Huginn is an open-source automation platform that functions as an event-driven task automator and webhook integration engine. It enables the creation of agents that monitor web data and automate tasks across various web services, operating as a self-hosted web scraper and JavaScript workflow orchestrator. The system uses a directed graph of event flows to route and transform data between external APIs. It differentiates itself by allowing custom JavaScript execution within workflows to modify data payloads and by integrating human-in-the-loop automation to insert manual judgment or data entry

This application is a real-time computer vision system designed to identify and label objects within live video feeds, recorded files, and static images. It functions as a comprehensive framework that integrates pre-trained machine learning models with video processing pipelines to perform multi-object localization and visual data tracking. The system distinguishes itself through a multithreaded architecture that decouples frame acquisition from detection logic, ensuring the interface remains responsive during continuous analysis. It provides specialized scripts for training and optimizing cu

This project is a PyTorch implementation of the YOLOv4 object detection framework. It provides a system for training and deploying neural networks that identify and locate multiple objects within images and video streams. The framework includes tools for converting trained weights into universal formats and hardware-specific optimized engines, specifically supporting ONNX and TensorRT. It features a TensorRT inference optimizer to reduce latency and increase throughput, as well as a model architecture compatible with NVIDIA DeepStream streaming analytics pipelines. The system covers model tr

Frigate is a self-hosted network video recorder that functions as a private, local AI-powered vision engine. It manages video streams by performing real-time object detection, tracking, and classification directly on local hardware, ensuring that security monitoring and activity recording remain independent of cloud services. The system distinguishes itself through a modular, hardware-accelerated video pipeline that offloads intensive decoding and machine learning inference to dedicated GPUs, NPUs, or specialized accelerators like Coral TPUs and Hailo modules. It utilizes state-based object t

Darknet is a high-performance C-based inference engine and computer vision library designed for real-time object identification and localization. It serves as a neural network framework for training and deploying detection models using the YOLO architecture, providing a toolset for deep learning training and deployment. The project differentiates itself through a C and CUDA implementation that enables hardware acceleration for matrix multiplication and inference speed optimization. It provides a shared library interface for embedding detection capabilities into external applications and suppo

This project is a multi-room music server and library aggregator that centralizes local audio files and various streaming services into a single unified database. It functions as a media controller for DLNA and UPnP devices, enabling the management of music, podcasts, and audiobooks across networked speakers. The system is distinguished by its ability to synchronize audio playback across multiple speakers and brands simultaneously. It features a digital signal processor for loudness normalization and frequency correction, alongside an acoustic fingerprinting engine used for metadata enrichmen

RT-DETR is a real-time object detection model based on the detection transformer architecture. It is implemented as a computer vision model for both the PyTorch and PaddlePaddle deep learning platforms, designed to identify and locate multiple objects in images and video streams. The model eliminates the need for anchor generation and non-maximum suppression by utilizing a transformer-based approach. It focuses on high-performance detection, balancing precision and low latency for live environment deployment. The system employs a hybrid encoder and multi-scale feature fusion to extract globa

YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/

Beehive is a self-hosted integration platform and event automation engine. It functions as a plugin-based workflow orchestrator that links independent service plugins to automate data movement between external APIs and hardware. The system acts as an IoT hardware controller for managing network-enabled sockets, smart lighting, and serial port devices via TTY or COM. It also serves as an HTTP webhook gateway, receiving incoming requests to trigger internal workflows and external notifications. Capability areas include event-driven workflow automation with filter-based routing and template-bas

This project is a PyTorch implementation of the YOLOv3 object detection architecture. It functions as a real-time object detector and computer vision framework designed to identify and locate multiple objects within images using bounding boxes and class labels. The system allows for both the use of pretrained weights for immediate image analysis and the training of custom models using datasets with bounding box annotations. It provides a programmatic interface to integrate detection capabilities directly into other software applications. The framework includes tools for model evaluation to m

YOLOv7 is a PyTorch vision library and real-time inference engine designed for object detection, human pose estimation, and instance segmentation. It provides a framework for detecting and locating multiple objects within images or video streams using neural networks. The system includes tools for custom model training and fine-tuning, allowing pre-trained weights to be adapted to specialized datasets via transfer learning. It also supports model weight export and format conversion to facilitate deployment on production servers and embedded edge devices.

This project is a software integration designed to connect and control local Xiaomi smart home devices within a centralized home automation environment. It functions as a bridge that enables unified monitoring and management of various connected appliances across a local network, providing a standardized interface for IoT device orchestration. The integration secures communication channels by validating encrypted handshake sequences required to authorize commands between the controller and local hardware. It maintains state consistency by translating proprietary device attributes into standar

Tasmota is a universal firmware platform for ESP8266 and ESP32 microcontrollers, designed to provide local control and management of smart home hardware. It functions as an event-driven automation controller that replaces proprietary factory firmware, allowing users to manage relays, sensors, and lighting systems without relying on external cloud services. The system is built on a modular driver architecture that enables dynamic hardware configuration and peripheral support through a web-based management interface. The platform distinguishes itself through a template-driven hardware mapping s

YOLOv5 is a comprehensive computer vision framework designed for end-to-end deep learning, specializing in real-time object detection, image classification, and instance segmentation. It provides a unified toolkit that manages the entire lifecycle of a model, from initial dataset configuration and hyperparameter tuning to high-speed inference and deployment. The framework utilizes a modular neural architecture, allowing users to swap backbone and head components to tailor models for specific visual tasks. What distinguishes this project is its focus on production-ready deployment and model ef

Kestra is a declarative workflow orchestrator designed to manage complex task dependencies and automated processes through versioned configuration files. It functions as a distributed platform that decouples task scheduling from execution by offloading computational workloads to a fleet of worker nodes. The system uses a reactive, event-driven engine to initiate workflows automatically in response to external signals, webhooks, schedules, or file system changes. The platform distinguishes itself through a modular plugin architecture that allows for the integration of custom tasks and external

The platform is a distributed system designed for real-time data monitoring, continuous graph-based query processing, and reactive event automation. It functions as a middleware solution that tracks state changes in external databases and systems, evaluating these streams against graph patterns to identify significant events and state transitions without the need for manual polling. The platform distinguishes itself through its ability to synchronize state updates across distributed environments, including real-time updates to vector databases for AI applications. It utilizes a pluggable conn

pydoll is a Chrome DevTools Protocol automation library and headless browser controller used for web data extraction and parallel browser automation. It controls Chromium-based browsers via direct WebSocket connections, allowing it to manage isolated browser contexts and tabs while bypassing the overhead and detection associated with WebDriver. The project features an anti-bot evasion framework that mimics natural human behavior, including mouse movements generated via Bezier curves and variable typing patterns. It provides specialized stealth capabilities to bypass behavioral analysis and au

tracking.js is a browser computer vision library written in JavaScript for performing real-time image analysis and object tracking directly within a web browser. It functions as a real-time object tracker, a color tracking tool, and a face detection utility. The library enables the detection and monitoring of specific color ranges, human faces, and known visual patterns across consecutive video frames. It extracts visual features and descriptors from images to identify distinct landmarks for matching and tracking. The project covers broad computer vision capabilities, including the ability t

This is a PyTorch object detection framework that implements the Single Shot MultiBox Detector for identifying and localizing multiple objects within images and video. The project provides a neural network architecture designed for single-shot object detection, which predicts bounding boxes and class labels in one pass. The implementation includes a real-time object detector capable of processing live video streams to track and label objects across sequential frames. It also features a complete computer vision training pipeline for preparing image datasets and training model weights. The fra

Argo is a cloud native CI/CD platform and Kubernetes workflow engine. It functions as a container pipeline orchestrator and job scheduler, managing multi-step sequences of containers as jobs using directed acyclic graphs within a cluster. The system acts as a progressive delivery controller, reducing release risk through automated Canary and Blue-Green deployment strategies. It provides declarative GitOps synchronization to mirror the state of a git repository directly into the cluster environment for continuous delivery automation. The platform covers a broad range of capabilities including