13 dépôts
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 est un client d'interface en ligne de commande pour Apache Kafka utilisé pour produire, consommer et déboguer des messages en utilisant le protocole filaire natif. Il fournit une suite d'outils pour interagir avec les clusters Kafka, y compris un débogueur de protocole pour inspecter les métadonnées du cluster et un gestionnaire de transactions pour gérer les lots de messages atomiques. Le projet dispose d'un décodeur de schéma Avro spécialisé qui convertit les messages encodés en binaire en JSON lisible par l'homme en s'intégrant avec des registres de schémas distants ou des fichiers locaux. De plus, il inclut un simulateur en mémoire qui permet de tester la logique du producteur et du consommateur en simulant un comportement de courtier éphémère sans nécessiter d'infrastructure externe. L'ensemble d'outils couvre un large éventail d'opérations de messagerie, y compris la prise en charge des groupes de consommateurs équilibrés, la recherche d'offset basée sur l'horodatage et le streaming de données transactionnelles à partir de l'entrée standard. Il fournit également des utilitaires pour la configuration de la sécurité des connexions et l'inspection des métadonnées du cluster.
Retrieves specific message offsets based on temporal values for targeted data recovery and analysis.
LyricsX est une application macOS qui rend les paroles de chansons synchronisées sur l'interface utilisateur du système pendant la lecture de musique. Il fonctionne comme un outil d'affichage de bureau, un agrégateur de paroles externe et un utilitaire de synchronisation. L'application récupère les paroles à partir de plusieurs sources de données distantes en utilisant les métadonnées de lecture actuelles et fournit un convertisseur de script pour traduire le texte entre les caractères chinois traditionnels et simplifiés. Elle inclut également un gestionnaire de fichiers de paroles pour importer et exporter des formats de paroles courants via des interactions de glisser-déposer. L'outil fournit des capacités de synchronisation temporelle pour faire correspondre les horodatages des paroles avec l'horloge de lecture audio. Les fonctionnalités supplémentaires incluent la capacité d'afficher les paroles sur le bureau ou la barre de menu et la gestion automatique du cycle de vie de l'application pour maintenir la synchronisation avec le lecteur de musique actif.
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 est un outil d'apprentissage contextuel du vocabulaire anglais et un lecteur multimédia interactif conçu pour l'étude des langues. Il extrait des mots de vidéos et de documents pour fournir des exemples concrets et des clips multimédias pour la mémorisation, fonctionnant comme un outil linguistique basé sur les sous-titres et un générateur de listes de mots basé sur les lemmes. Le système se différencie en liant les listes de vocabulaire à des horodatages vidéo et des sous-titres spécifiques pour un renforcement auditif et visuel. Il inclut un lecteur vidéo avec sous-titres bilingues et des exercices de transcription et d'orthographe au clavier pour construire une mémoire musculaire à travers des contextes de films et de séries télévisées. Le projet couvre l'extraction de vocabulaire à partir de documents, de sous-titres et de pistes vidéo, couplée à l'affinage des listes de mots par lemmatisation, filtrage de fréquence et exclusion basée sur le dictionnaire. Il gère également les sources d'apprentissage multimédia et diffuse des segments vidéo spécifiques associés aux mots cibles pour renforcer la mémoire.
Maps vocabulary terms to precise video playback offsets for immediate retrieval of audiovisual examples.
KafkaJS is a pure JavaScript client for Apache Kafka, providing the necessary tools to produce and consume messages from a Kafka cluster without requiring native dependencies or external addons. It functions as a comprehensive integration library for Node.js applications to engage in distributed message processing and real-time event streaming. The project is distinguished by its native implementation of the Kafka wire protocol, avoiding C++ dependencies. It features a security client supporting SSL, TLS, and SASL authentication, alongside transactional capabilities that allow for atomic mess
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.