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vitrivr's next-generation retrieval engine. It is capable of extracting and retrieving a wider range of multimedia objects such as audio, video, images or 3d models.

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vitrivr's next-generation retrieval engine.

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vitrivr-engine

vitrivr-engine is vitrivr's next generation retrieval engine with a flexible, modular architecture. Based on the experiences with its predecessor, Cineast, vitrivr engine's data model, ingestion pipeline and retrieval logic have been reworked from the ground. Essentially, vitrivr-engine enables the analysis (i.e. ingestion) and querying (i.e. retrieval ) of multimedia data.

Built With

Getting Started

See Getting Started

Usage

See Example

Project Structure

The project is set up as a multi-module Kotlin project:

Module Description Maven Dependency
vitrivr-engine-core The core library of the project, which provides basic interfaces & classes. Yes
vtirivr-engine-query Query / retrieval related extension to the core library with various retrievers and data manipulation operators. Yes
vitrivr-engine-index Indexing / ingestion related extension to the core library with various decoders and segmenters. Yes
vitrivr-engine-module-cottontaildb The database driver for the CottontailDB database, used for NNNS and other queries. Yes
vitrivr-engine-module-features Extension that contains specific indexing and retrieval implementations such as fulltext, colour, etc. Yes
vitrivr-engine-module-m3d Extension related to 3d model indexing and retrieval. Contains various feature modules and capability to process meshes. Yes
vitrivr-engine-module-fes Extension that can be used to harnes feature extraction provided by an external ML model server. Requires local generation of bindings: ./gradlew :vitrivr-engine-module-fes:generateFESClient Yes
vitrivr-engine-server A Javalin powered server providing an OpenApi documented REST API for both, ingestion and querying and a CLI, essentially the runtime of the project No

Contributing

We welcome contributors. Please fork the repo and open a pull-request with your work. A good starting point are the 'good first issue' issues.

Contributors

  • @ppanopticon
  • @lucaro
  • @sauterl
  • @net-csscience-raphel
  • @rahelarnold98
  • @faberf

Citation

See Citation

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vitrivr's next-generation retrieval engine. It is capable of extracting and retrieving a wider range of multimedia objects such as audio, video, images or 3d models.

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