# Video and audio tools > Search results for `Video and audio tools` on awesome-repositories.com. 119 total matches; showing the first 50. Explore on the web: https://awesome-repositories.com/q/video-and-audio-tools **Attribution required: if you use, quote, or summarise this content, you must credit and link back to [this search on awesome-repositories.com](https://awesome-repositories.com/q/video-and-audio-tools).** ## Results - [3b1b/videos](https://awesome-repositories.com/repository/3b1b-videos.md) (10,314 ⭐) — This project is a programmatic animation engine designed to create mathematical visualizations through executable scripts. It functions as a mathematical visualization tool that renders parametric curves, equations, and coordinate systems to translate abstract concepts into high-resolution video. The system features an interactive scene renderer that allows for the execution of code snippets and real-time manipulation of scene states before final rendering. It includes an automated animation workflow that manages rendering checkpoints, scene playback, and video sequencing directly from a text editor. The engine covers a broad capability surface including coordinate-based vector rendering, programmatic scene definition, and dynamic object relationship linking. It provides tools for animation sequence rendering and video organization to produce final high-resolution output. The project uses a Python-based API to map mathematical expressions to renderable objects. - [nilaoda/n_m3u8dl-re](https://awesome-repositories.com/repository/nilaoda-n-m3u8dl-re.md) (7,406 ⭐) — N_m3u8DL-RE is a command line tool designed for capturing and saving on-demand or live video streams from M3U8 manifest files. It functions as an HLS stream recorder and downloader capable of capturing adaptive bitrate streams and recording live broadcasts with real-time merging and specific duration limits. The tool features an AES encrypted stream decrypter that removes encryption from media segments using provided keys and external decryption engines. It also includes a media muxer that integrates with the FFmpeg engine to combine downloaded audio, video, and subtitle tracks into a single container. Additional capabilities include media track filtering by resolution or language via regular expressions and partial content downloading to save specific time ranges of a stream. The system also manages network traffic through configurable proxy settings and multi-threaded segment fetching. - [go-audio/audio](https://awesome-repositories.com/repository/go-audio-audio.md) (238 ⭐) — Generic Go package designed to define a common interface to analyze and/or process audio data - [googlechrome/workbox](https://awesome-repositories.com/repository/googlechrome-workbox.md) (12,895 ⭐) — Workbox is a modular library and toolkit designed for managing service workers in progressive web applications. It provides a comprehensive framework for handling asset caching, request routing, and background script lifecycle management, enabling developers to build web applications that function reliably offline and load efficiently. The project distinguishes itself through a declarative routing engine and a plugin-based architecture that allows for the injection of custom logic into the request and response processing pipeline. It supports advanced caching patterns, such as cache-first or network-first strategies, and includes specialized capabilities for media streaming, navigation preloading, and the synchronization of offline requests. Beyond core caching, the toolkit offers extensive utilities for monitoring and observability, including cache inspection, diagnostic logging, and network simulation. It also provides build-time integration tools to automate the generation of service worker files and the management of precache manifests, ensuring consistent application versioning and state coordination between the main application thread and background workers. - [avelino/awesome-go](https://awesome-repositories.com/repository/avelino-awesome-go.md) (175,576 ⭐) — This project serves as a comprehensive language ecosystem index, functioning as a centralized, community-curated directory for the Go programming language. It organizes a vast landscape of software components, libraries, and development tools into a structured, navigable hierarchy, enabling developers to efficiently discover resources tailored to specific functional domains. The repository distinguishes itself through a decentralized contribution model, where community-driven updates ensure the index remains current with the rapidly evolving software landscape. Beyond simple resource listing, it acts as a technical knowledge repository, aggregating professional literature, style guides, and best practices to support developer onboarding and professional growth across the entire software development lifecycle. The directory covers a broad capability surface, including essential utilities for distributed systems engineering, application security, data processing, and development productivity. It provides access to specialized tools for database management, web framework integration, testing, and build automation, alongside educational materials that help developers master language-specific architectural patterns. The project is maintained as a static resource aggregation, providing a holistic view of external links and documentation to orient developers within the Go ecosystem. - [seadve/kooha](https://awesome-repositories.com/repository/seadve-kooha.md) (3,262 ⭐) — Kooha is a screen recorder for Linux desktops that utilizes the Wayland protocol and XDG Portals for secure recording. It functions as a hardware-accelerated screen capture tool that offloads video compression to the GPU to reduce CPU load and power consumption. The application integrates the PipeWire framework to capture system and microphone audio streams and leverages FFmpeg for muxing video streams and exporting various codecs and containers. Its user interface is a native Linux application built with the GTK toolkit. The software covers screen recording and capture of entire displays, specific windows, or custom regions. It includes capabilities for multimedia content production and export, allowing users to configure recording settings such as frame rate and pointer visibility. - [pytorch/audio](https://awesome-repositories.com/repository/pytorch-audio.md) (2,886 ⭐) — Data manipulation and transformation for audio signal processing, powered by PyTorch - [audiojs/audio](https://awesome-repositories.com/repository/audiojs-audio.md) (0 ⭐) — Audio in JavaScript - [ffmpeg/ffmpeg](https://awesome-repositories.com/repository/ffmpeg-ffmpeg.md) (61,176 ⭐) — FFmpeg is a cross-platform multimedia framework designed for the recording, conversion, and streaming of audio and video content. It functions as a comprehensive toolkit that provides both a command-line utility for direct media manipulation and a collection of low-level libraries for integration into custom applications. At its core, the project utilizes a packet-based stream engine and a format-agnostic abstraction layer to handle diverse media standards, containers, and network protocols. The framework distinguishes itself through a modular, graph-based filter execution model that allows for complex, non-linear transformations of audio and video frames. It supports high-performance processing by offloading intensive encoding and decoding tasks to dedicated hardware and utilizing threaded parallel processing to maximize throughput across multiple processor cores. This architecture enables users to construct intricate pipelines for tasks ranging from simple format conversion to advanced real-time media filtering and analysis. Beyond core transcoding, the project covers a broad functional surface including live streaming, hardware device capture, and secure network transport. It provides extensive capabilities for metadata management, subtitle processing, and stream synchronization, alongside diagnostic tools for inspecting media integrity and performance. The system is highly extensible, allowing for the dynamic integration of external codecs and third-party libraries to support specialized media requirements. - [blakeblackshear/frigate](https://awesome-repositories.com/repository/blakeblackshear-frigate.md) (33,778 ⭐) — 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 tracking to maintain persistent identity and spatial coordinates for detected objects, enabling advanced behavioral analysis such as loitering detection and speed estimation. Users can further refine these capabilities through semantic search, which allows for text-to-image and image-to-image similarity queries across recorded footage. Beyond core detection, the platform provides comprehensive tools for spatial configuration, including declarative geometric masks and zone-based filtering to minimize false positives. It supports low-latency, peer-to-peer streaming for live viewing and integrates with smart home ecosystems to bridge camera feeds and event notifications. The system also includes specialized features for face recognition, license plate detection, and audio event analysis, all managed through a secure, token-authenticated API. The software is designed for containerized deployment, utilizing environment variables for configuration and standard protocols for certificate management and performance metric exposure. - [jianchang512/pyvideotrans](https://awesome-repositories.com/repository/jianchang512-pyvideotrans.md) (17,991 ⭐) — Pyvideotrans is an automated video localization platform designed to transcribe, translate, and dub media content for international distribution. It functions as an end-to-end workflow that combines speech recognition, text translation, and synthetic voice generation to process video files into localized versions. The system distinguishes itself by offering a choice between local model inference for privacy and integration with third-party cloud services via user-provided credentials. This architecture allows users to maintain control over their billing and data security while utilizing modular pipelines to orchestrate complex tasks like voice cloning and subtitle synchronization. The software supports large-scale operations through a command-line interface that manages batch task queuing and automated media processing. It utilizes multimedia frameworks to handle audio extraction and video remuxing, including options for lossless export to preserve visual quality. The toolset covers the entire localization lifecycle, from generating timestamped subtitles with speaker identification to producing synthetic voiceovers with adjustable speech parameters. - [humansignal/label-studio](https://awesome-repositories.com/repository/humansignal-label-studio.md) (27,619 ⭐) — Label Studio is a multi-modal data annotation platform designed to create and manage high-quality training datasets for machine learning. It functions as a self-hosted, containerized environment that supports secure, private deployments, including air-gapped configurations. The platform provides a centralized workspace for labeling diverse media types, such as images, text, audio, and time-series data, to support supervised and reinforcement learning workflows. The platform distinguishes itself through deep integration with machine learning backends, enabling active learning loops, automated pre-labeling, and real-time model-assisted annotation. It features a declarative interface configuration system that uses markup to define custom labeling tools, alongside plugin-based extensibility that allows for the injection of custom logic. To support enterprise-scale operations, it includes granular role-based access control, collaborative feedback tools, and automated task distribution management. The system covers a broad capability surface, including automated data ingestion from cloud storage, programmatic pipeline management via REST APIs, and comprehensive data export options. It also provides built-in observability tools to monitor annotator performance, inter-annotator agreement, and model quality. The application is packaged as a portable, container-ready microservice designed for deployment in scalable, cloud-native environments. - [video-react/video-react](https://awesome-repositories.com/repository/video-react-video-react.md) (2,724 ⭐) — A web video player built for the HTML5 world using React library. - [deepfakes/faceswap](https://awesome-repositories.com/repository/deepfakes-faceswap.md) (55,289 ⭐) — Faceswap is a comprehensive framework for automated media manipulation and neural face synthesis. It provides a modular pipeline that manages the entire lifecycle of facial feature extraction, deep learning model training, and image conversion. By coordinating complex computer vision workflows, the system enables users to map facial identities between source and destination datasets while maintaining structural alignment and lighting consistency across video frames. The project distinguishes itself through a highly extensible plugin-based architecture that handles hardware-accelerated processing and multi-stage image post-processing. It includes specialized tools for manual alignment verification, allowing users to refine detected facial data through a graphical interface to ensure high-quality results. The system also features robust batch-oriented data processing, which partitions media into standardized chunks to optimize memory usage and throughput during intensive neural network operations. Beyond its core synthesis capabilities, the framework covers a broad range of computer vision tasks including facial landmark detection, pose estimation, and mask generation. It integrates sophisticated model management utilities, such as automated loss calculation, gradient clipping, and snapshot recovery, to ensure stable training sessions. The system also provides extensive diagnostic tools for hardware performance monitoring and environment validation, ensuring compatibility across various compute accelerators. The software is managed through a centralized command-line and graphical toolkit that supports persistent configuration and session state management. It is designed to run on diverse hardware configurations by dynamically querying available compute resources and routing tensor operations to the optimal processor. - [expo/expo](https://awesome-repositories.com/repository/expo-expo.md) (50,111 ⭐) — Expo is a universal mobile framework designed to build native iOS and Android applications from a single codebase using web-standard technologies. It provides a comprehensive development environment that includes a unified runtime for testing, cloud-based infrastructure for compiling and signing native binaries, and automated tools for managing the entire mobile release lifecycle, including app store submission. The framework distinguishes itself through a plugin-based native configuration engine that programmatically modifies project files, allowing developers to integrate native modules without manual intervention. It also features a file-based routing system that maps directory structures directly to navigation paths, and an over-the-air update service that enables the deployment of JavaScript and asset changes directly to user devices, bypassing traditional app store review cycles. Beyond these core capabilities, the platform offers a wide range of integrated services for managing project metadata, environment variables, and persistent data storage. It includes a robust set of UI components and utilities for handling hardware-level features such as camera access, geolocation, audio and video playback, and push notifications. Developers can also leverage managed cloud services to orchestrate custom build profiles and automate CI/CD workflows. The project is managed via a command-line interface that facilitates project setup, native module integration, and the generation of custom development builds. Documentation and tooling are provided to support both standalone applications and the integration of Expo into existing native projects. - [ashbaldry/video](https://awesome-repositories.com/repository/ashbaldry-video.md) (0 ⭐) — {video} is a package that utilises the video.js library to play video on the modern web. - [bradlarson/gpuimage](https://awesome-repositories.com/repository/bradlarson-gpuimage.md) (20,299 ⭐) — GPUImage is a GPU-accelerated image processing framework for iOS designed to apply real-time filters and effects to images and video. It functions as a processing engine and fragment shader library that manages textures and shaders for efficient visual data manipulation. The framework utilizes a chainable filter architecture and a texture-based data pipeline to pass image data between processing stages without expensive memory transfers. It enables the creation of bespoke visual effects through the authoring of custom fragment shaders and provides mechanisms to synchronize texture data with external OpenGL ES graphics contexts. Capabilities cover a broad range of image and video processing, including color and tone adjustment, image source blending, and the generation of artistic visual styles. The system supports geometric transformations such as cropping and resizing, as well as real-time filtering of live camera feeds and the post-processing of movie files. - [aigc-audio/audiogpt](https://awesome-repositories.com/repository/aigc-audio-audiogpt.md) (10,174 ⭐) — AudioGPT is an LLM-driven audio framework and processing suite that uses large language models to orchestrate neural audio pipelines. It functions as a multimodal audio generator and processing system, integrating a collection of pretrained models to handle speech synthesis, sound generation, and audio manipulation. The system is distinguished by its ability to generate audio from diverse inputs, including text and images, and its capacity to produce synchronized talking head videos. It also operates as a neural speech translator, converting spoken language between different tongues while preserving meaning. The project covers a broad range of audio capabilities, including restoration, source separation, and automatic speech transcription. Additional functional areas include sound analysis for event detection, spatial audio conversion from mono to binaural formats, and speech style transfer. - [fishaudio/fish-speech](https://awesome-repositories.com/repository/fishaudio-fish-speech.md) (24,928 ⭐) — This project is a generative speech synthesis engine that converts text into high-fidelity human speech. It utilizes a two-stage autoregressive transformer architecture that separates semantic token prediction from acoustic detail reconstruction to balance linguistic accuracy with audio quality. The system is designed to support multilingual output and conversational AI development, enabling the generation of context-aware speech that maintains flow across multiple dialogue turns. The platform distinguishes itself through a production-ready inference server that employs continuous batching to maximize hardware utilization and reduce latency. It includes a comprehensive voice cloning toolkit that replicates unique vocal characteristics from short reference audio samples without requiring additional model training. Users can further customize output through low-rank adaptation fine-tuning, which allows for efficient style adjustments, and speaker-specific token embeddings that manage distinct voice characteristics during multi-speaker generation. Beyond core synthesis, the project provides a full suite of utilities for training and alignment, including reinforcement learning techniques to optimize for semantic accuracy and instruction adherence. It supports a variety of operational interfaces, including a command-line tool, a web-based dashboard, and an authenticated HTTP server for remote generation workloads. The system also includes data preparation and serialization tools to streamline the process of organizing and normalizing audio datasets for model training. - [breakthrough/pyscenedetect](https://awesome-repositories.com/repository/breakthrough-pyscenedetect.md) (4,556 ⭐) — PySceneDetect is a suite of tools for identifying cuts and transitions in video files using content, threshold, and histogram detection algorithms. It functions as a scene detector, frame extractor, statistics analyzer, metadata exporter, and video scene splitter. The project identifies scene boundaries and can divide video files into smaller clips using external processing tools. It allows for the extraction of representative image frames from detected changes and the export of scene lists into industry-standard formats such as EDL, FCP, HTML, OTIO, and CSV. The toolset includes capabilities for per-frame metric tracking and visual pattern analysis to determine optimal detection thresholds. It provides an interface to ingest video content from local files, hardware cameras, or data pipes. - [moonshotai/kimi-audio](https://awesome-repositories.com/repository/moonshotai-kimi-audio.md) (4,492 ⭐) — Kimi-Audio is a large language model audio foundation model designed to understand audio input and generate high-fidelity speech responses in real time. It functions as a unified system encompassing a text-to-speech synthesis engine and a speech-to-text transcription tool. The project enables real-time audio conversations through a multi-modal conversation loop and chunk-wise streaming detokenization to reduce playback latency. It provides controls over speech speed, accent, and emotional tone during conversational audio generation. The system covers audio intelligence capabilities, including audio content analysis, emotion recognition, scene classification, and captioning. It also includes an audio model fine-tuning toolkit for instruction-based adaptation and a benchmarking suite for evaluating performance via standardized metrics and side-by-side comparisons. - [bluesky-social/social-app](https://awesome-repositories.com/repository/bluesky-social-social-app.md) (18,063 ⭐) — This project provides a comprehensive implementation of the AT Protocol, serving as a framework for building decentralized social networking applications. It enables the creation of distributed data repositories where users maintain cryptographic ownership of their identity and content, allowing for portable accounts that can be migrated between independent servers without central authority intervention. The platform distinguishes itself by decoupling content hosting from discovery through modular algorithmic curation. Users can select third-party services to filter and organize their feeds, while content moderation is handled through a flexible labeling system that allows for both automated and community-driven content standards. By utilizing content-addressed storage and cryptographically signed records, the system ensures that data integrity can be independently verified across the network. Beyond core identity and storage, the project includes infrastructure for real-time network event streaming, media distribution, and global data aggregation. It supports complex social interactions through automated agents and provides tools for managing distributed repository state, including historical data backfilling and scalable traffic management. The repository contains the necessary tools and services to interact with the federated network, including standardized authentication flows and schema-based data interoperability. - [chainlit/chainlit](https://awesome-repositories.com/repository/chainlit-chainlit.md) (12,213 ⭐) — Chainlit is a Python framework designed for building and deploying interactive, stateful conversational AI interfaces. It provides a backend-driven platform that connects language models and agent frameworks to a web-based chat frontend, managing the complexities of session state, message history, and real-time communication. The framework distinguishes itself by offering a component-based UI builder that allows developers to inject interactive widgets, rich media, and data visualizations directly into the chat stream. It supports the visualization of complex agent workflows, enabling users to inspect intermediate reasoning steps and tool usage in real-time. Additionally, the platform includes built-in support for secure user authentication, persistent conversation history, and the ability to embed chat widgets into existing web applications with bidirectional communication. The system covers a broad range of capabilities, including document processing, vector database integration for context-aware retrieval, and comprehensive observability tools for debugging and monitoring model interactions. It also provides extensive configuration options for interface customization, localization, and access control, ensuring that applications can be tailored to specific organizational requirements. The project is distributed as a Python library and includes a command-line interface to facilitate project setup, configuration, and deployment. - [aschhoff/esp32-433mhz-receiver-and-tools](https://awesome-repositories.com/repository/aschhoff-esp32-433mhz-receiver-and-tools.md) (0 ⭐) — ESP32 433Mhz Receiver written in micropython and Tools for Windows - [chocobozzz/peertube](https://awesome-repositories.com/repository/chocobozzz-peertube.md) (14,520 ⭐) — PeerTube is a decentralized, open-source video hosting platform that enables users to operate independent, interoperable servers. By utilizing the ActivityPub protocol, it connects these servers into a global, federated network where users can follow channels, discover content, and interact across different instances. The platform is designed to function as a self-hosted video content management system, providing a community-driven alternative to centralized media services. What distinguishes PeerTube is its hybrid approach to content delivery and infrastructure management. It integrates peer-to-peer distribution via WebTorrent to reduce server bandwidth consumption, while simultaneously supporting remote object storage to decouple media assets from local disk capacity. To maintain performance under high load, the platform delegates resource-intensive tasks like video transcoding and transcription to external worker instances, ensuring the primary server remains responsive. The platform offers a comprehensive suite of tools for content management, including live streaming, automated moderation, and granular access controls. Its extensibility is supported by a hook-based plugin architecture, allowing administrators to inject custom logic, modify interface elements, or integrate third-party services. Additionally, the system provides a robust command-line interface and a standardized REST API, enabling programmatic control over administrative tasks, bulk content processing, and platform maintenance. The software is packaged for containerized deployment, simplifying infrastructure management and ensuring consistent execution across various hosting environments. - [peterl1n/robustvideomatting](https://awesome-repositories.com/repository/peterl1n-robustvideomatting.md) (9,244 ⭐) — RobustVideoMatting is a deep learning video matting tool and PyTorch library designed to remove backgrounds from videos and extract human subjects. It utilizes a temporal video segmentation model to ensure consistent matting and reduce flickering across video frames. The project includes a cross-platform model exporter that converts trained neural networks into various runtime formats. This allows for model deployment across multiple environments, including web and mobile applications. The framework provides capabilities for temporal video background removal and AI video post-production without the use of green screens. It supports video file conversion and the processing of image sequences to create transparent backgrounds for compositing. - [crowdcurio/audio-annotator](https://awesome-repositories.com/repository/crowdcurio-audio-annotator.md) (466 ⭐) — A JavaScript interface for annotating and labeling audio files. - [anomalyco/opentui](https://awesome-repositories.com/repository/anomalyco-opentui.md) (12,131 ⭐) — Opentui is a terminal user interface framework for building interactive command line applications. It provides a component-based system featuring a flexbox layout engine, a virtual node component tree, and a low-level 2D cell array renderer. The project is distinguished by a sophisticated keyboard binding engine that maps complex multi-stroke sequences and chords to named commands using prioritized, reactive layers. It also implements a plugin architecture that allows external modules to inject custom UI components into designated layout slots and extend input logic at runtime. Its capabilities cover rich text rendering—including syntax-highlighted code, markdown, and diff views—and advanced visual effects like alpha blending and RGBA matrix transformations. The framework includes a comprehensive input pipeline supporting the Kitty keyboard protocol, as well as a suite of interactive UI components such as multi-line text fields, selection menus, and value sliders. The system can be compiled into a standalone executable with embedded native binaries for distribution. - [eventual-inc/daft](https://awesome-repositories.com/repository/eventual-inc-daft.md) (5,225 ⭐) — Daft is a distributed dataframe library and multimodal data processor designed to handle large-scale structured and unstructured data. It functions as a vectorized execution engine that processes tables alongside images, audio, and video, utilizing a unified schema to manage diverse data types. The project distinguishes itself by combining distributed data engineering with large-scale AI inference. It provides an AI data pipeline for batch-optimizing model prompts and generating high-dimensional text embeddings, while utilizing zero-copy memory sharing to execute custom Python functions without processing overhead. Its capabilities extend across cloud data lakehouse connectivity, supporting open table formats like Iceberg, Delta Lake, and Hudi. The engine employs lazy-evaluated execution plans and sampling-based schema inference to manage datasets that exceed single-node memory, scaling workloads from local cores to distributed Kubernetes clusters. The system further includes a comprehensive suite for data transformation, covering columnar aggregation, window functions, and geospatial manipulation, as well as specialized tools for audio transcription and video frame extraction. - [elevenlabs/elevenlabs-python](https://awesome-repositories.com/repository/elevenlabs-elevenlabs-python.md) (2,873 ⭐) — This Python SDK provides a comprehensive toolkit for synthetic audio generation, voice cloning, and the development of conversational AI agents. It enables the creation of lifelike spoken audio from text, the replication of human voices through custom cloning, and the deployment of real-time voice agents capable of interacting with external large language models. The library distinguishes itself through deep integration of conversational AI capabilities, including the design of agent personas and the execution of real-time actions via APIs. It supports professional-grade audio production through a variety of specialized tools for multilingual dubbing, studio-quality music generation, and high-fidelity sound effects. The SDK covers a broad surface of speech and media processing, including real-time audio streaming via WebSockets, speech-to-text transcription with speaker diarization, and the synchronization of audio with visual elements. It also provides utilities for monitoring generation costs and managing agent security through response guardrails and access controls. - [ericlbuehler/mistral.rs](https://awesome-repositories.com/repository/ericlbuehler-mistral-rs.md) (6,597 ⭐) — mistral.rs is an inference engine for large language models that runs locally and exposes models behind OpenAI and Anthropic-compatible APIs. It serves as a multi-model serving platform, capable of loading several models in a single server process with per-request routing and on-demand loading and unloading. The engine supports multimodal inference, processing text alongside images, video, audio, and speech inputs, and includes a quantized model deployment runtime that reduces memory use and speeds up inference on consumer hardware. The project distinguishes itself through an agentic tool execution framework that runs server-side tools like code execution, shell commands, and web search in an automated loop during model generation, with session state persistence. It provides an in-process inference engine that can be embedded directly into Rust or Python applications without a separate server process, and includes an in-situ quantization engine that converts model weights to lower precision at load time with per-layer tuning. The system supports structured output constraints, forcing model output to conform to JSON Schema or grammar specifications during decoding, and offers automatic architecture detection that identifies model type, quantization format, and chat template from a Hugging Face model ID. The platform includes capabilities for managing LoRA adapters, composing models as mixture-of-experts configurations, and running distributed inference across multiple GPUs or nodes using tensor parallelism and ring transport. It provides a built-in web chat interface, supports speculative decoding with a smaller assistant model, and offers benchmarking, logging, and Prometheus metrics for monitoring. The project can be run from a configuration file, with options for customizing build processes, tuning hardware settings automatically, and managing model caches. - [blaizzy/mlx-audio](https://awesome-repositories.com/repository/blaizzy-mlx-audio.md) (5,994 ⭐) — mlx-audio is an audio processing toolkit built on Apple MLX that provides speech transcription, text-to-speech synthesis, voice cloning, and audio source separation using local models. It offers an OpenAI-compatible REST API and web interface for running audio generation and transcription tasks, enabling drop-in integration with existing tools that follow that endpoint structure. The toolkit supports text-prompted audio source separation, allowing specific sounds to be isolated from mixed recordings based on natural language descriptions. It also provides voice cloning from a short reference audio sample, speech enhancement through noise reduction, and voice activity detection with speaker diarization to distinguish between different speakers in recordings. Additional capabilities include speech-to-text transcription with word-level timestamp alignment, streaming audio generation that outputs results incrementally, and model weight quantization to reduce memory footprint and accelerate inference. The system manages multiple models through a unified interface and supports WebSocket audio transport for low-latency communication. - [android/ndk-samples](https://awesome-repositories.com/repository/android-ndk-samples.md) (10,513 ⭐) — The Android NDK samples provide a comprehensive collection of code examples demonstrating how to integrate C and C++ native code into Android applications. This repository serves as a practical guide for developers utilizing the Android Native Development Kit to implement performance-critical application components that require direct hardware access and low-level system interaction. The project highlights the use of the Java Native Interface to bridge managed code with native modules, enabling cross-language function calls and efficient data exchange. It demonstrates how to manage native activity lifecycles, configure build toolchains for multi-architecture compilation, and package native libraries to ensure compatibility across diverse mobile processor instruction sets. These samples cover a broad capability surface, including high-performance graphics rendering with Vulkan and OpenGL ES, low-latency audio processing, and on-device machine learning inference. The collection also illustrates advanced techniques for memory management, native code debugging, and performance optimization, such as hardware-assisted memory sanitization and CPU-specific instruction set targeting. - [arendst/tasmota](https://awesome-repositories.com/repository/arendst-tasmota.md) (24,502 ⭐) — 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 system, which uses JSON strings to assign physical pins and drivers to specific device functions without requiring firmware recompilation. It acts as a multi-protocol gateway, bridging disparate standards like Zigbee, Bluetooth, LoRaWan, and Modbus into a unified network. By utilizing a local message-broker-based control model, Tasmota synchronizes device states and executes custom automation logic directly on the hardware, ensuring consistent operation even when disconnected from external controllers. Beyond its core bridging and control capabilities, the firmware includes a comprehensive suite of tools for system observability, data logging, and media management. It supports complex automation through a built-in rule engine, persistent flash-based filesystem storage for scripts and assets, and extensive integration options for major smart home ecosystems. The project provides a web-based provisioning interface for initial setup and supports remote firmware management to simplify the maintenance of distributed hardware fleets. - [lengstrom/fast-style-transfer](https://awesome-repositories.com/repository/lengstrom-fast-style-transfer.md) (10,963 ⭐) — This project is a TensorFlow-based neural style transfer framework designed to apply the artistic textures and colors of a painting to images and videos. It utilizes a feed-forward image stylizer that transforms visual appearance in a single pass, avoiding the need for iterative optimization. The system includes a deep learning training pipeline that teaches convolutional neural networks to replicate specific styles using perceptual loss functions. It also features a video frame processor that decomposes video files into individual images for sequential stylization and reassembly. The software covers a broad range of capabilities including batch image processing, style transfer network training, and temporal frame processing for videos. It supports checkpoint-based model loading to restore trained network weights for immediate application and provides tools for style output verification. - [qwenlm/qwen-audio](https://awesome-repositories.com/repository/qwenlm-qwen-audio.md) (1,908 ⭐) — The official repo of Qwen-Audio (通义千问-Audio) chat & pretrained large audio language model proposed by Alibaba Cloud. - [google-gemini/cookbook](https://awesome-repositories.com/repository/google-gemini-cookbook.md) (17,418 ⭐) — The Gemini Cookbook is a comprehensive collection of implementation patterns, code samples, and development guides designed for building applications with Google Gemini models. It serves as a central resource for developers to integrate multimodal generative artificial intelligence into their software, providing the necessary frameworks to manage model interactions, stateful workflows, and structured data extraction. The repository distinguishes itself by offering specialized toolkits for autonomous agent orchestration, enabling the construction of agents that can execute code, browse the web, and perform multi-step tasks in sandboxed environments. It provides deep support for real-time conversational interfaces, including bidirectional streaming for audio, video, and text, as well as advanced capabilities for multimodal content generation and long-context data processing. Beyond core model integration, the project covers a broad capability surface including retrieval-augmented generation, batch processing for high-throughput workloads, and observability tools for monitoring token usage and debugging API interactions. It also provides guidance on security primitives, such as authentication and content safety, alongside operational strategies for cost optimization and infrastructure management. The documentation is structured as a series of Jupyter Notebooks, offering interactive examples that demonstrate how to implement these features within production-grade artificial intelligence systems. - [evandrolg/ts-audio](https://awesome-repositories.com/repository/evandrolg-ts-audio.md) (339 ⭐) — :musical_score: ts-audio is an agnostic library that makes it easy to work with AudioContext and create audio playlists in the browser - [mps-youtube/yewtube](https://awesome-repositories.com/repository/mps-youtube-yewtube.md) (8,743 ⭐) — Yewtube is a command line YouTube client, media player, and downloader. It provides a text-based interface for searching, streaming, and browsing video content and comments without requiring an API key. The project functions as a Tor network proxy client, routing network requests through the Tor network to anonymize browsing and streaming activity. It also operates as a media downloader, enabling the retrieval of videos and playlists for local storage in various resolutions and audio formats. The application covers broader capabilities including playlist management, online media streaming, and media conversion via external encoders. It includes a terminal-based user interface with customizable search results and integrates with system media controllers to synchronize playback state. - [chatwoot/chatwoot](https://awesome-repositories.com/repository/chatwoot-chatwoot.md) (31,959 ⭐) — Chatwoot is a self-hosted, omnichannel customer support platform designed to aggregate messages from diverse social and digital channels into a single, collaborative team inbox. It provides organizations with full data ownership and control over their support infrastructure, ensuring strict logical separation of customer data through multi-tenant architecture. By centralizing communication, the platform enables teams to manage, route, and resolve inquiries within a unified workspace that maintains complete interaction history for every contact. The platform distinguishes itself through an event-driven automation engine and a visual rule builder that allow teams to manage conversations and workflows without writing custom code. It incorporates intelligent features such as automated response drafting, conversation context recall, and a self-service knowledge base to improve agent efficiency. These capabilities are supported by granular role-based access controls and comprehensive performance analytics, which provide insights into agent productivity, inbox activity, and customer satisfaction trends. Beyond its core messaging and routing functions, the system offers a broad suite of operational tools including proactive engagement triggers, team workload balancing, and multilingual support. It supports flexible deployment strategies, including containerized and cloud-native orchestration, to accommodate various production environments. The platform is designed for extensibility, allowing for custom attribute management and integration with external systems via webhooks and API-based channels. - [ggerganov/kbd-audio](https://awesome-repositories.com/repository/ggerganov-kbd-audio.md) (0 ⭐) — kbd-audio - [yaofanguk/video-subtitle-extractor](https://awesome-repositories.com/repository/yaofanguk-video-subtitle-extractor.md) (8,432 ⭐) — This project is an optical character recognition tool designed to extract hardcoded subtitles from video frames and convert them into synchronized subtitle files. It functions as a text processor that transforms embedded visual text into a written format to improve video accessibility and translation. The system uses graphics processing units to increase the speed and accuracy of text recognition. It includes a subtitle cleaning tool that applies custom mapping configurations to filter out watermarks, channel logos, and duplicate lines from the extracted text. The tool supports batch processing for multiple video files that share identical resolutions and text region settings. It utilizes region-based extraction to isolate subtitles from background noise and synchronizes recognized text strings with specific video timestamps. - [hipstas/audio-labeler](https://awesome-repositories.com/repository/hipstas-audio-labeler.md) (53 ⭐) — An in-browser app for labeling audio clips at random, using Docker and Flask. - [elastic/elasticsearch](https://awesome-repositories.com/repository/elastic-elasticsearch.md) (77,012 ⭐) — Elasticsearch is a distributed search engine and document store designed for the high-performance indexing and retrieval of massive volumes of unstructured data. It functions as a centralized analytics platform, providing a schema-flexible architecture that organizes information into searchable indices while maintaining global cluster state through a distributed consensus mechanism. The platform distinguishes itself through its integrated approach to observability, security, and advanced analytics. It combines full-text, vector, and hybrid search capabilities with machine learning-driven insights, allowing users to perform complex statistical aggregations, geospatial analysis, and automated anomaly detection. Its storage architecture supports multi-tier data lifecycles, enabling efficient data placement across hot, warm, and cold nodes to balance performance with long-term retention requirements. Beyond core search and storage, the system provides comprehensive observability tools for centralized log analysis, application performance monitoring, and infrastructure health diagnostics. It includes built-in security operations for threat detection and endpoint protection, all managed through a unified RESTful API gateway. The system is accessible via standardized REST APIs for cluster management, data ingestion, and query execution. Extensive documentation is available to guide users through API references for search, indexing, security, and cluster administration. - [gyroflow/gyroflow](https://awesome-repositories.com/repository/gyroflow-gyroflow.md) (8,256 ⭐) — Gyroflow is a gyroscope video stabilization software and IMU telemetry processor designed to remove camera shake from video files. It functions as a hardware-accelerated video renderer and lens calibration tool, utilizing embedded or external gyroscope and accelerometer data to perform pixel-level stabilization. The system is distinguished by its ability to integrate with professional non-linear video editing software via plugins, allowing stabilization to be applied directly to timelines without transcoding original footage. It supports diverse telemetry ingestion from camera brands, flight controllers, and external sidecar files, and includes specialized tools for reversing electronic stabilization and correcting rolling shutter artifacts. Broad capabilities include lens distortion modeling, horizon locking, and adaptive crop and zoom management. The software provides a command-line interface for programmatic batch processing, directory monitoring, and telemetry conversion, alongside GPU-accelerated encoding for high-fidelity video export. The project provides utilities for digital lens calibration, sensor data visualization, and the generation of 3D camera motion for compositing environments. - [scikit-image/scikit-image](https://awesome-repositories.com/repository/scikit-image-scikit-image.md) (6,529 ⭐) — scikit-image is a Python image processing library and scientific image analysis toolkit. It provides a framework for digital image processing and computer vision, utilizing numerical arrays for pixel-level manipulations. The library enables the quantification of image properties and the detection of visual features, such as edges and blobs. It includes tools for image segmentation and the extraction of textures and patterns to characterize objects within visual data. Capabilities cover image manipulation through color space conversion, geometric transformations, and digital restoration. It also provides utilities for morphological operations, image registration, and the processing of video files. The project uses a plugin system for importing and exporting image files across various formats. - [gitroomhq/postiz-app](https://awesome-repositories.com/repository/gitroomhq-postiz-app.md) (32,271 ⭐) — Postiz is an open-source social media management platform designed to centralize the scheduling, publishing, and analysis of content across diverse social networks, community forums, and blogging platforms. It functions as a unified hub where users can coordinate, review, and distribute content through a shared team workspace, while leveraging integrated artificial intelligence to assist in drafting text and generating multimedia assets. The platform distinguishes itself through a modular architecture that utilizes a provider-specific adapter pattern to ensure consistent content distribution across various external services. It incorporates an AI-driven tool execution model that connects natural language models to internal functions, enabling automated content generation and media configuration. Furthermore, the system provides a programmatic API gateway that allows external applications to interact with its scheduling and management features via structured payloads. Beyond core scheduling, the platform includes comprehensive tools for performance tracking, media storage abstraction, and collaborative workflows. It supports complex content strategies through features like multi-part thread scheduling and automated campaign execution, while maintaining secure identity management through OAuth-based mediation and support for external identity providers. The application is designed for self-hosting and can be deployed into containerized environments using provided configuration charts. - [opentalker/video-retalking](https://awesome-repositories.com/repository/opentalker-video-retalking.md) (7,256 ⭐) — Video-retalking is an AI lip synchronization framework and talking head video editor designed to match the mouth movements of a subject in a video to a target audio track. It utilizes a deep learning pipeline to synchronize speech with video recordings. The system employs a two-stage generation process that separates coarse lip movement from high-resolution detail refinement. It incorporates identity-aware face refinement and expression template alignment to maintain photorealistic skin textures and ensure visual consistency across video frames. The toolset covers facial expression modification and regional face decomposition to independently control emotional states and speech synchronization. It also includes capabilities for synthetic face enhancement to improve the visual fidelity of generated human videos. - [audio-lab/render](https://awesome-repositories.com/repository/audio-lab-render.md) (44 ⭐) — :eyeglasses: Stream for rendering audio data - [awesome-selfhosted/awesome-selfhosted](https://awesome-repositories.com/repository/awesome-selfhosted-awesome-selfhosted.md) (299,516 ⭐) — This project is a community-curated directory of open-source software designed for deployment in private server environments and home labs. It serves as a comprehensive resource for discovering independent, self-hosted alternatives to mainstream cloud services, enabling users to maintain full data ownership and control over their digital infrastructure. The directory is structured through a hierarchical taxonomy that organizes a vast collection of applications into logical categories, ranging from media management and data analytics to private communication and team productivity tools. It distinguishes itself through a collaborative peer-review process, where community members validate the quality and relevance of each submission to ensure the directory remains accurate and reliable. The project covers a broad capability surface, including infrastructure automation, container-based service deployment, and declarative configuration management. These tools assist users in maintaining reproducible server environments and managing complex service dependencies across private hardware. The directory is maintained as a version-controlled repository, ensuring that all updates and community-driven changes are tracked and transparent.