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<!DOCTYPE html><html style="font-size: 41px;"><head><meta charset="utf-8"><meta http-equiv="x-ua-compatible" content="ie=edge"><meta name="viewport" content="width=device-width,initial-scale=1,shrink-to-fit=no"><title>Vearch</title><meta name="description" content=""><meta name="apple-mobile-web-app-capable" content="yes"><meta name="fragment" content="!"><meta name="apple-mobile-web-app-capable" content="yes"><meta name="msapplication-config" content="/static/icons/browserconfig.xml"><meta name="theme-color" content="#408c71"><link rel="manifest" href="/static/icons/manifest.json"><link rel="mask-icon" href="/static/icons/safari-pinned-tab.svg" color="#3fba84"><link rel="shortcut icon" href="/static/icons/favicon.ico"><link rel="canonical" href="https://snipcart.com"><style>body{background:#fcfdff}</style><script>window.prerenderReady = false</script><script type="text/javascript">var __rootrem;
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" alt=""></div> <p data-v-fd9e4c5e="">Vearch is the vector search infrastructure for deeping learning and AI applications. </p> <a data-v-fd9e4c5e="" href="https://vearch.readthedocs.io/en/latest/" target="_blank" class="get_started_btn"><img data-v-fd9e4c5e="" src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAWCAYAAADJqhx8AAAAAXNSR0IArs4c6QAAAOdJREFUOBFj+P//vzEQtwOxKQM5AKjxCRCDwB8gbgZiFpLMAelEAyeAfBWiDUHTDON+BjISiTIEpgMHvRooLojXIBwakYUfAzmOOA1BVomH/Q8o1wXEbBgG4dGETeocUFADxRBsqgiIfQXKZ8ANIaAYn/QmoKQwI0gF3DTSGWuYSNeDokOQEhdcBhoVxoDPkzjkQFE6EYjZwW7BoQiX8HOghDuKJ3CpxCIOCnVRFM0gDhaF6EKo8Y5uArpqND5myiPSANxpnwgDQLnPCV0dTj5Q8UskZxPO/+gmATU7APFSII5ElyOGDwB8C7D/LaUe1AAAAABJRU5ErkJggg==" alt="">
Get Started
</a> <a data-v-fd9e4c5e="" href="https://github.com/vearch/vearch" target="_blank" class="download_btn"><img data-v-fd9e4c5e="" src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAXCAYAAAAC9s/ZAAAAAXNSR0IArs4c6QAAAJ9JREFUOBFjYEAD////zwViXCAXTTkDE7oAqfxRAxhGAxGYaBiBSa4GSKcgJSBeIFsIiY/MfAfkfEYSmMMANABkyAxcaRePOEgPI9gwEAOIp+JRjC4FUgvRjOQckGsmoqvEwp+IrAeDDdTQi0UTTKgXQwM2AaDqTpgOJLoTm1qcYkCNrUiaW3EqxCcBNKAJhPGpGQZyoAT0nxJ/UFwmAgBYLA4zTyh9iAAAAABJRU5ErkJggg==" alt="">
Download
</a> <a data-v-fd9e4c5e="" href="mailto:[email protected]" target="_blank" class="mailing_list_btn"><img data-v-fd9e4c5e="" src="data:image/png;base64,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" alt="">
Mailing List
</a></div> <div data-v-fd9e4c5e="" class="info"><p data-v-fd9e4c5e="">Based on this project, the paper "Design and Implementation of a Real Time Visual Search System on JD E-commerce Platform" has be accepted and publised by International ACM Middleware Conference. <a data-v-fd9e4c5e="" href="https://arxiv.org/abs/1908.07389" target="_blank">https://arxiv.org/abs/1908.07389</a></p></div> <div data-v-fd9e4c5e="" class="content"><div data-v-fd9e4c5e="" class="con_flow"><p data-v-fd9e4c5e="">The Key features of vearch</p> <div data-v-fd9e4c5e="" class="line"></div> <div data-v-fd9e4c5e="" class="con_layer"><ul data-v-fd9e4c5e=""><li data-v-fd9e4c5e=""><img data-v-fd9e4c5e="" src="data:image/png;base64,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" alt=""> <span data-v-fd9e4c5e="">Large scale vector storage and retrieval</span> <p data-v-fd9e4c5e="">Vearch is a distributed vector storage and retrieval system which can be easily extend to billions scale.</p></li> <li data-v-fd9e4c5e=""><img data-v-fd9e4c5e="" src="data:image/png;base64,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" alt=""> <span data-v-fd9e4c5e="">High-performance real time index</span> <p data-v-fd9e4c5e="">Vearch implements a high-performance，lockless real time vector indexing subsystem that utilizes various optimization techniques to support millisecond vector update and retrieval.</p></li> <li data-v-fd9e4c5e=""><img data-v-fd9e4c5e="" src="data:image/png;base64,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" alt=""> <span data-v-fd9e4c5e="">Out of box</span> <p data-v-fd9e4c5e="">End to end one-click deployment. Through the module of plugin, a complete default visual search system can be deployed just with one click. Otherwise, you can easily customize your own image, video or text feature extraction algorithm plugin.</p></li> <li data-v-fd9e4c5e=""><img data-v-fd9e4c5e="" src="data:image/png;base64,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" alt=""> <span data-v-fd9e4c5e="">Scalar & numeric filter</span> <p data-v-fd9e4c5e="">Not only vector, vearch can also store scalar data, including numeric and string types. Besides storage, vearch can index numeric types, supporting equal or range filter, to reduce unnecessary computation.</p></li></ul></div></div> <div data-v-fd9e4c5e="" class="con_link"><p data-v-fd9e4c5e="">Application Scenarios</p> <div data-v-fd9e4c5e="" class="line"></div> <div data-v-fd9e4c5e="" class="con_image"><ul data-v-fd9e4c5e=""><li data-v-fd9e4c5e=""><div data-v-fd9e4c5e="" class="img_big"><img data-v-fd9e4c5e="" src="//storage.360buyimg.com/vearch/FR.png" alt=""></div> <span data-v-fd9e4c5e="">Face Recognition</span></li> <li data-v-fd9e4c5e=""><div data-v-fd9e4c5e="" class="img_big"><img data-v-fd9e4c5e="" src="//storage.360buyimg.com/vearch/CBIR.png" alt=""></div> <span data-v-fd9e4c5e="">CBIR</span> <div data-v-fd9e4c5e="" class="sub_title"> (Content-Based Image Retrieval) </div></li> <li data-v-fd9e4c5e=""><div data-v-fd9e4c5e="" class="img_big"><img data-v-fd9e4c5e="" src="//storage.360buyimg.com/vearch/VS.png" alt=""></div> <span data-v-fd9e4c5e="">Video Surveillance</span></li> <li data-v-fd9e4c5e=""><div data-v-fd9e4c5e="" class="img_big"><img data-v-fd9e4c5e="" src="//storage.360buyimg.com/vearch/TSR.png" alt=""></div> <span data-v-fd9e4c5e="">Text Semantic Retrieval</span></li> <li data-v-fd9e4c5e=""><div data-v-fd9e4c5e="" class="img_big"><img data-v-fd9e4c5e="" src="//storage.360buyimg.com/vearch/RS.png" alt=""></div> <span data-v-fd9e4c5e="">Recommendation System</span></li></ul></div></div> <div data-v-fd9e4c5e="" class="con_split"></div> <div data-v-fd9e4c5e="" class="con_show"><img data-v-fd9e4c5e="" src="//storage.360buyimg.com/vearch/dynamic.gif" alt="" class="con_gif"> <p data-v-fd9e4c5e="" class="con_desc">
This GIF provides a clear demonstration of the project vearch usage and its internal structure. The use of vearch is mainly divided into three steps. Firstly, create DB and Space, then import your data, and finally you can search on your own dataset.
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