13 repositorios
Retrieving a specific message offset based on a temporal value.
Distinct from Offset-Based Addressing: Focuses on translating timestamps to offsets, whereas Offset-Based Addressing is about navigating binary blobs.
Explore 13 awesome GitHub repositories matching data & databases · Timestamp-Based Offset Lookups. Refine with filters or upvote what's useful.
Sarama is an Apache Kafka Go client library that provides native support for the Kafka protocol. It includes a protocol client for managing offsets and timestamps, a producer implementation for sending messages, and a consumer group coordinator to balance workloads across multiple instances. The library enables high throughput data streaming through concurrent message production and maintains strict partition ordering during network retries. It supports secure communication with Kafka brokers using certificate-based encryption to protect data traffic. The project covers a broad range of dist
Allows retrieving specific message offsets for given timestamps to initiate reading from precise points in time.
WWDC is a native macOS video player and conference session manager designed for streaming and organizing developer conference videos. It functions as a video transcription browser and annotation tool, allowing users to track viewing progress and organize technical sessions into personalized learning paths. The application enables navigation through videos via searchable, multi-language text transcripts. Users can create searchable reference points by annotating specific video timestamps with custom notes and distribute content by sharing session links or extracting short video clips. The sys
Links searchable text indices to specific video time offsets for instant navigation during playback.
Silero VAD is a voice activity detection model and deep learning speech classifier designed to distinguish human speech from silence across diverse languages and noisy environments. It functions as a pre-trained neural network capable of identifying speech segments within both static audio recordings and real-time data streams. The project includes a language identification tool for classifying spoken languages and a framework for fine-tuning audio models. It provides utilities for optimizing detection thresholds using validation datasets and retraining the model with custom labeled audio to
Maps model output indices to temporal offsets to isolate specific voice segments from recordings.
Autocut is a text-based video editor and automatic speech recognition tool. It allows users to cut and merge video clips by modifying a text transcript instead of using a traditional timeline. The system operates as an FFmpeg video processor and subtitle manipulation utility. It converts spoken audio into text and compacts subtitle files into simplified formats, enabling the removal of unwanted video segments by deleting corresponding sentences from a transcription file. The project covers automated video transcription, non-linear video cutting, and subtitle file management. It supports hard
Generates precise video edit points by mapping text indices from a transcript to specific timecodes.
kcat es un cliente de interfaz de línea de comandos para Apache Kafka utilizado para producir, consumir y depurar mensajes utilizando el protocolo nativo. Proporciona un conjunto de herramientas para interactuar con clusters de Kafka, incluyendo un depurador de protocolos para inspeccionar metadatos del cluster y un gestor de transacciones para manejar lotes de mensajes atómicos. El proyecto cuenta con un decodificador de esquemas Avro especializado que convierte mensajes codificados en binario en JSON legible por humanos mediante la integración con registros de esquemas remotos o archivos locales. Además, incluye un simulador en memoria que permite probar la lógica del productor y consumidor simulando el comportamiento efímero del broker sin requerir infraestructura externa. El conjunto de herramientas cubre una amplia gama de operaciones de mensajería, incluyendo soporte para grupos de consumidores balanceados, búsqueda de offsets basada en marcas de tiempo y streaming de datos transaccionales desde la entrada estándar. También proporciona utilidades para la configuración de seguridad de la conexión y la inspección de metadatos del cluster.
Retrieves specific message offsets based on temporal values for targeted data recovery and analysis.
LyricsX es una aplicación de macOS que renderiza letras de canciones sincronizadas sobre la UI del sistema durante la reproducción de música. Funciona como una herramienta de visualización de escritorio, un agregador de letras externo y una utilidad de sincronización. La aplicación obtiene letras de múltiples fuentes de datos remotas utilizando metadatos de reproducción actuales y proporciona un convertidor de scripts para traducir texto entre caracteres chinos tradicionales y simplificados. También incluye un gestor de archivos de letras para importar y exportar formatos de letras comunes mediante interacciones de arrastrar y soltar. La herramienta proporciona capacidades para la sincronización de tiempo para hacer coincidir las marcas de tiempo de las letras con el reloj de reproducción de audio. Las características adicionales incluyen la capacidad de mostrar letras en el escritorio o en la barra de menús y la gestión automática del ciclo de vida de la aplicación para mantener la sincronización con el reproductor de música activo.
Adjusts the temporal offset of lyric lines to align precisely with the audio playback clock.
This project is an anime scene reverse image search engine that matches a screenshot to the exact anime episode and timestamp. It is designed as a self-hosted search service that can be deployed using Docker containers and pre-indexed databases, enabling private operation on local or custom infrastructure. At its core, the system extracts visual features from frames using a convolutional neural network trained on anime imagery. Query images provided via URL are processed through the same feature extraction pipeline, and an approximate nearest neighbor search matches the query against millions
Translates matched frame numbers to exact anime episode, offset, and scene metadata.
MuJing is a contextual English vocabulary learner and interactive media player designed for language study. It extracts words from videos and documents to provide real-world examples and media clips for memorization, functioning as a subtitle-based language tool and a lemma-based word list generator. The system differentiates itself by linking vocabulary lists to specific video timestamps and subtitles for auditory and visual reinforcement. It includes a video player with bilingual subtitles and keyboard-based transcription and spelling exercises to build muscle memory through movie and telev
Maps vocabulary terms to precise video playback offsets for immediate retrieval of audiovisual examples.
KafkaJS es un cliente de JavaScript puro para Apache Kafka, que proporciona las herramientas necesarias para producir y consumir mensajes de un clúster de Kafka sin requerir dependencias nativas o addons externos. Funciona como una biblioteca de integración integral para aplicaciones Node.js para participar en el procesamiento de mensajes distribuidos y streaming de eventos en tiempo real. El proyecto se distingue por su implementación nativa del protocolo de red de Kafka, evitando dependencias de C++. Cuenta con un cliente de seguridad que soporta autenticación SSL, TLS y SASL, junto con capacidades transaccionales que permiten el envío atómico de mensajes y compromisos de offset vinculados para asegurar un procesamiento exactamente una vez. La biblioteca cubre una amplia gama de áreas operativas, incluyendo administración completa de clústeres para gestionar temas y grupos de consumidores, estrategias avanzadas de enrutamiento y asignación de particiones, y telemetría integral mediante monitoreo basado en eventos. También implementa patrones de fiabilidad de red como reintentos con retroceso exponencial (exponential backoff) y obtención de datos consciente del rack para optimizar la latencia.
Fetches the earliest or most recent offsets for a topic based on a specific timestamp.
DashPlayer is a language learning video player designed for vocabulary and grammar study. It integrates an AI subtitle generator to create machine-translated captions and grammatical sentence analysis for video content. The project features a bilingual subtitle renderer that displays dual-language captions with toggleable visibility. It includes a remote media downloader to fetch online video content via URL and a utility to split long files into smaller segments for more manageable study sessions. The playback system supports sentence-based navigation, allowing users to jump between subtitl
Enables jumping between subtitle lines and repeating phrases using keyboard and Bluetooth inputs.
LLPlayer is a language learning media player and AI subtitle generator that integrates large language models for real-time audio transcription and translation. It functions as an LLM-integrated video player and SRT transcription tool, utilizing local or remote AI models to generate text subtitles from audio and video streams. The project distinguishes itself through a contextual translation workflow that sends preceding subtitle lines to language models to maintain conversational flow and sentence structure. It also includes an optical character recognition system to convert bitmap-based subt
Maps searchable subtitle text to specific playback timestamps for rapid video navigation.
Auto-subs is an AI transcription and automatic captioning tool that converts spoken audio from video files into synchronized subtitles. It functions as a subtitle generator and a transcription bridge, enabling the conversion of speech to text with automatic speaker identification and multi-language translation support. The software prioritizes data privacy by utilizing on-device AI inference to process audio and video files locally on the user's hardware. It distinguishes itself by offering deep integration with professional video editing workflows, allowing users to export timing and transcr
Binds specific words or phrases to precise time offsets to keep captions synchronized during edits.
danmu_api is a bullet chat API gateway that aggregates video comments from multiple platforms and serves them through a standardized interface for use in media players. It includes a metadata matching service to identify video content across platforms using keywords or file names. The system uses an adapter-based normalization process to translate diverse platform response formats into a single schema and utilizes a Redis-backed cache to store search results and comment streams. It features a processing engine that cleans comment streams using keyword and regular expression filters. The proj
Adjusts comment delivery timing using linear scaling and manual offsets to align text with video playback.