13 repository-uri
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 este un client de linie de comandă pentru Apache Kafka utilizat pentru a produce, consuma și depana mesaje folosind protocolul nativ. Oferă o suită de instrumente pentru interacțiunea cu clusterele Kafka, inclusiv un depanator de protocol pentru inspectarea metadatelor clusterului și un manager de tranzacții pentru gestionarea batch-urilor atomice de mesaje. Proiectul dispune de un decodor de schemă Avro specializat care convertește mesajele codificate binar în JSON lizibil pentru oameni prin integrarea cu registre de scheme la distanță sau fișiere locale. În plus, include un simulator în memorie care permite testarea logicii de producător și consumator prin simularea comportamentului brokerului efemer fără a necesita infrastructură externă. Setul de instrumente acoperă o gamă largă de operațiuni de mesagerie, inclusiv suport pentru grupuri de consumatori echilibrate, căutarea offset-ului bazată pe timestamp și streaming de date tranzacționale din input standard. De asemenea, oferă utilitare pentru configurarea securității conexiunii și inspectarea metadatelor clusterului.
Retrieves specific message offsets based on temporal values for targeted data recovery and analysis.
LyricsX este o aplicație macOS care redă versurile melodiilor sincronizate peste UI-ul sistemului în timpul redării muzicii. Acesta funcționează ca un instrument de afișare pe desktop, un agregator extern de versuri și un utilitar de sincronizare. Aplicația preia versurile din mai multe surse de date externe folosind metadatele de redare curente și oferă un convertor de script pentru a traduce textul între caracterele chinezești tradiționale și simplificate. Include, de asemenea, un manager de fișiere de versuri pentru importarea și exportarea formatelor comune de versuri prin interacțiuni drag-and-drop. Instrumentul oferă capabilități pentru sincronizarea temporizării pentru a potrivi timestamp-urile versurilor cu ceasul de redare audio. Caracteristicile suplimentare includ capacitatea de a afișa versurile pe desktop sau în bara de meniu și gestionarea automată a ciclului de viață al aplicației pentru a menține sincronizarea cu playerul muzical activ.
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 este un instrument de învățare a vocabularului englez contextual și un player media interactiv conceput pentru studiul limbilor străine. Extrage cuvinte din videoclipuri și documente pentru a oferi exemple din lumea reală și clipuri media pentru memorare, funcționând ca un instrument lingvistic bazat pe subtitrări și un generator de liste de cuvinte bazat pe leme. Sistemul se diferențiază prin legarea listelor de vocabular de timestamp-uri specifice din videoclipuri și subtitrări pentru consolidare auditivă și vizuală. Include un player video cu subtitrări bilingve și exerciții de transcriere și ortografie bazate pe tastatură pentru a construi memoria musculară prin contexte din filme și televiziune. Proiectul acoperă extragerea vocabularului din documente, subtitrări și piste video, combinată cu rafinarea listelor de cuvinte prin lematizare, filtrarea frecvenței și excluderea bazată pe dicționar. De asemenea, gestionează sursele de învățare multimedia și transmite segmente video specifice asociate cu cuvintele țintă pentru a consolida memoria.
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.