Displaying 1 to 4 from 4 results

jina - Cloud-native neural search framework for ๐™–๐™ฃ๐™ฎ kind of data

  •    Python

Jina๐Ÿ”Š is a neural search framework that empowers anyone to build SOTA & scalable deep learning search applications in minutes. ๐ŸŒŒ All data types - Large-scale indexing and querying of any kind of unstructured data: video, image, long/short text, music, source code, PDF, etc.

Milvus - An open-source vector database for embedding similarity search and AI applications

  •    Go

Milvus is an open-source vector database built to power embedding similarity search and AI applications. Milvus makes unstructured data search more accessible, and provides a consistent user experience regardless of the deployment environment. Milvus 2.0 is a cloud-native vector database with storage and computation separated by design. All components in this refactored version of Milvus are stateless to enhance elasticity and flexibility.

VIAME - Video and Image Analytics for Marine Environments

  •    C++

VIAME is a computer vision application designed for do-it-yourself artificial intelligence including object detection, object tracking, image/video annotation, image/video search, image mosaicing, size measurement, rapid model generation, and tools for the evaluation of different algorithms. Originally targetting marine species analytics, it now contains many common algorithms and libraries, and is also useful as a generic computer vision toolkit. It contains a number of standalone tools for accomplishing the above, a pipeline framework which can connect C/C++, python, and matlab nodes together in a multi-threaded fashion, and, lastly, multiple algorithms resting on top of the pipeline infrastructure. Both a desktop and web version exist for deployments in different types of environments. For a full installation guide and description of the various flavors of VIAME, see the quick-start guide, above. The desktop version is provided as either a .msi, .zip or .tar file. Alternatively, docker files are available for both VIAME Desktop and Web (below). A sample instance of VIAME Web is also online, hosted at viame.kitware.com. For desktop installs, extract the binaries (or use the msi Windows installation wizard) and place them in a directory of your choosing, for example /opt/noaa/viame on Linux or C:\Program Files\VIAME on Windows. If using packages built with GPU support, make sure to have sufficient video drivers installed, version 451.82 or higher. The best way to install drivers depends on your operating system, see below. Lastly, run through some of the examples to validate the installation. The binaries are quite large, in terms of disk space, due to the inclusion of multiple default model files and programs, but if just building your desired features from source (e.g. for embedded apps) they are much smaller.

jinabox.js - A lightweight, customizable omnibox in Javascript, for use with a Jina backend.

  •    Javascript

jinabox.js is a lightweight, customizable set of components for querying and displaying results from Jina flows. You can use it for searching text, images, videos, audio or any kind of data with a Jina backend.









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