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class="globalBreadcrumb_breadcrumbList___dw0x globalBreadcrumb_horizonAlignLeft__pvF41"><li class="globalBreadcrumb_listItem__4n_9F"><a class="globalBreadcrumb_breadcrumbItem__3Axv8 globalBreadcrumb_homeItem__9PTnF globalBreadcrumb_darkTheme__R4ILy" href="/"><svg width="13" height="12" viewBox="0 0 13 12" fill="none" xmlns="http://www.w3.org/2000/svg" color="#fff"><g clip-path="url(#clip0_19069_588)"><path d="M11.4526 5.66339L6.71842 1.17877C6.42915 0.90476 5.97612 0.90476 5.68685 1.17877L0.952637 5.66339" stroke="#fff" stroke-width="0.9" stroke-linecap="round" stroke-linejoin="round"></path><path d="M2.05817 7.37201V10.5598C2.05817 10.974 2.39395 11.3097 2.80817 11.3097H9.57781C9.99202 11.3097 10.3278 10.974 10.3278 10.5597V7.37201" stroke="#fff" stroke-width="0.9" stroke-linecap="round" stroke-linejoin="round"></path><path d="M7.50721 11.3097V8.12201C7.50721 7.7078 7.17142 7.37201 6.75721 7.37201H5.62885C5.21463 7.37201 4.87885 7.70779 4.87885 8.12201V11.3097" stroke="#fff" stroke-width="0.9" stroke-linecap="round" stroke-linejoin="round"></path></g><defs><clipPath id="clip0_19069_588"><rect width="12" height="12" fill="white" transform="translate(0.202637)"></rect></clipPath></defs></svg></a><svg width="8" height="14" viewBox="0 0 8 14" fill="none" xmlns="http://www.w3.org/2000/svg" color="#fff"><path d="M7.39502 1.20099L0.608318 12.7991" stroke="#fff"></path></svg></li><li class="globalBreadcrumb_listItem__4n_9F"><a class="globalBreadcrumb_breadcrumbItem__3Axv8 globalBreadcrumb_darkTheme__R4ILy" href="/customers">Customers</a><svg width="8" height="14" viewBox="0 0 8 14" fill="none" xmlns="http://www.w3.org/2000/svg" color="#fff"><path d="M7.39502 1.20099L0.608318 12.7991" stroke="#fff"></path></svg></li><li class="globalBreadcrumb_listItem__4n_9F"><p class="globalBreadcrumb_currentItem__2QgJK globalBreadcrumb_darkTheme__R4ILy">Mozat</p></li></ul></div></h2><h1 class="globalPageHeader_title__wEJ6h globalPageHeader_longSentenceTitle__baBV5">Mozat Personalizes Fashion Discovery With Image Similarity Search Using Milvus</h1><p class="globalPageHeader_desc__zcPFG globalPageHeader_leftRightDesc__6SXEO"></p></div><div class="globalPageHeader_rightSection__3MIbW customerDetail_customRightPart__Utj0g"><img src="https://assets.zilliz.com/Group_4388_f72bdb1ba1.png" alt="Mozat"/></div></div></section><section class="customerDetail_highlighContainer__xlQJh"><ul class="page_container__IibMw customerDetail_highlighWrapper__15TxV"><li><p class="customerDetail_results__Wnijq">Handled tens of millions of </p><p class="customerDetail_desc__IeyIi">vector embeddings with fast scaling capability</p></li><li><p class="customerDetail_results__Wnijq">Achieved millisecond-level </p><p class="customerDetail_desc__IeyIi">query speed with optimal user experience</p></li><li><p class="customerDetail_results__Wnijq">Reshaped the future of fashion</p><p class="customerDetail_desc__IeyIi"> with a harmonious fusion of human creativity and machine intelligence</p></li></ul></section><section class="page_container__IibMw customerDetail_contentContainer__x6d7S"><div class="docContainer customerDetail_docContainer__DUpVO"><h2 id="About-Mozat" class="common-anchor-header">About Mozat<button data-href="#About-Mozat" class="anchor-icon" translate="no"> <svg aria-hidden="true" focusable="false" height="20" version="1.1" viewBox="0 0 16 16" width="16" > <path fill="#0092E4" fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z" ></path> </svg> </button></h2><p>Founded in 2003, <a href="http://www.mozat.com/home">Mozat</a> has been at the forefront of technology, spanning its business across Southeast Asia and Saudi Arabia. Specializing in social media, communication, and lifestyle applications, Mozat's crown jewel, an iPhone and Android application called <a href="https://stylepedia.com/">Stylepedia</a>, stood out as a testament to its creativity and dedication. This digital closet application offers users personalized style recommendations, integrates social media, and features an image search tool to discover similar fashion items. Mozat's Stylepedia reimagines fashion, fostering a sense of community and style exploration, where every outfit tells a story, and every user becomes a trendsetter.</p> <p> <span class="img-wrapper"> <img src="https://assets.zilliz.com/mozat_stylepedia_acc8d14177.png" alt="" class="doc-image" id="" /> <span></span> </span> </p> <h2 id="The-Challenge-Navigating-the-Vast-Realm-of-Fashion-Imagery" class="common-anchor-header">The Challenge: Navigating the Vast Realm of Fashion Imagery<button data-href="#The-Challenge-Navigating-the-Vast-Realm-of-Fashion-Imagery" class="anchor-icon" translate="no"> <svg aria-hidden="true" focusable="false" height="20" version="1.1" viewBox="0 0 16 16" width="16" > <path fill="#0092E4" fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z" ></path> </svg> </button></h2><p>Mozat envisioned Stylepedia as more than just a virtual closet but meant to be a place of hyper-personalized fashion suggestions tailored to individual tastes. However, this ambition came with its set of challenges. One of the major hurdles was the need to process a vast database of clothing images, growing exponentially every day. At the same time, the system had to deliver fast responses to users’ image queries for similar fashion style within milliseconds.</p> <p>Moreover, Mozat had to handle massive user-uploaded photos of varying resolutions, angles, and sizes. The challenge was clear: Mozat needed a technology that could efficiently store, recognize, comprehend, and compare these images, delivering lightning-fast and accurate results.</p> <h2 id="The-Solution-Adopting-Milvus-As-the-Neural-Network-of-Stylepedia" class="common-anchor-header">The Solution: Adopting Milvus As the Neural Network of Stylepedia<button data-href="#The-Solution-Adopting-Milvus-As-the-Neural-Network-of-Stylepedia" class="anchor-icon" translate="no"> <svg aria-hidden="true" focusable="false" height="20" version="1.1" viewBox="0 0 16 16" width="16" > <path fill="#0092E4" fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z" ></path> </svg> </button></h2><p>In their quest for a solution, the Mozat team found their answer in Milvus. It supports mainstream vector indexes and enables real-time searches on billions of vectors of datasets, making Milvus the ideal choice as the <a href="https://zilliz.com/glossary/neural-networks">neural network</a> for Stylepedia’s image search system.</p> <p>The image search system involves four modules:</p> <ul> <li><strong>Garment detection</strong> for detecting real-time objects and identifying clothing items and classifications.</li> <li><strong>Feature extraction</strong>: converting images into 512-dimensional vectors.</li> <li><strong>Vector similarity search:</strong> for large-scale similarity searches.</li> <li><strong>Post-processing:</strong> for refining results using color and critical label filtering, ensuring image quality alignment.</li> </ul> <p>Stylepedia utilizes Milvus in the vector similarity search module to support large-scale image similarity searches. Its workflow includes two parts. On the storage side, object detection and feature extraction models convert the entire fashion image library into 512-dimensional feature vectors. These vector data are then indexed and stored in Milvus. On the query side, machine learning models transform users’ query images into feature vectors. Milvus then performs ANN searches for the Top-K results most relevant to the query vectors and obtains their corresponding image IDs. Finally, after post-processing (filtering, sorting, etc.), Stylepedia returns a collection of similar images to the user.</p> <p> <span class="img-wrapper"> <img src="https://assets.zilliz.com/stylepedia_image_search_system_f6d73ba056.png" alt="" class="doc-image" id="" /> <span></span> </span> </p> <p>By leveraging Milvus, Stylepedia innovates three essential functions.</p> <ul> <li><strong>Searching for similar clothing items</strong>: Users can upload pictures of their clothes to find similar products in their digital closet.</li> <li><strong>Outfit suggestions</strong>: Users discover fashion photos containing specific items through similarity searches, aiding in new purchases or unique pairings.</li> <li><strong>Fashion photograph recommendations</strong>: The system analyzes browsing history and digital closet contents to provide tailored fashion photo recommendations.</li> </ul> <h2 id="The-Results-A-Fashion-Revolution" class="common-anchor-header">The Results: A Fashion Revolution<button data-href="#The-Results-A-Fashion-Revolution" class="anchor-icon" translate="no"> <svg aria-hidden="true" focusable="false" height="20" version="1.1" viewBox="0 0 16 16" width="16" > <path fill="#0092E4" fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z" ></path> </svg> </button></h2><p>Empowered by <a href="https://zilliz.com/what-is-milvus">Milvus</a>, Stylepedia emerged as a powerhouse of fashion intelligence. The increasing data volume was no longer a concern as Milvus handled billions of <a href="https://zilliz.com/glossary/vector-embeddings">vectors</a>, scaling out seamlessly. Stylepedia could now generate real-time responses to user queries, vastly improving user experience. Users could upload images of their clothes and quickly receive a curated selection of similar garments, making Stylepedia an artful fusion of technology and style expertise.</p> <p>With Milvus, Stylepedia becomes a fashion confidant, predicting trends, understanding individual tastes, and empowering users to embrace their style identity.</p> <h2 id="Conclusion-Shaping-Personal-Style-Journeys-with-Mozat-and-Milvus" class="common-anchor-header">Conclusion: Shaping Personal Style Journeys with Mozat and Milvus<button data-href="#Conclusion-Shaping-Personal-Style-Journeys-with-Mozat-and-Milvus" class="anchor-icon" translate="no"> <svg aria-hidden="true" focusable="false" height="20" version="1.1" viewBox="0 0 16 16" width="16" > <path fill="#0092E4" fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z" ></path> </svg> </button></h2><p>Mozat's collaboration with Milvus marked a new era in fashion discovery. Stylepedia ceased to be just an app; it became a harmonious fusion of human creativity and machine intelligence. By harnessing the power of Milvus, Mozat redefined how users interacted with fashion, paving the way for a future where technology is a partner in shaping personal style journeys.</p> </div><div class="globalArticleCTASection_sectionContainer__z7vw5 customerDetail_rightAnchorSection__qoRbt"><ul class="globalArticleCTASection_listWrapper__l52HF"><h3 class="globalArticleCTASection_anchorTitle__iGSh_">Content</h3><li><a class="globalArticleCTASection_anchorLink__JXvsH" href="/customers/mozat#About-Mozat">About Mozat</a></li><li><a class="globalArticleCTASection_anchorLink__JXvsH" href="/customers/mozat#The-Challenge-Navigating-the-Vast-Realm-of-Fashion-Imagery">The Challenge: Navigating the Vast Realm of Fashion Imagery</a></li><li><a class="globalArticleCTASection_anchorLink__JXvsH" href="/customers/mozat#The-Solution-Adopting-Milvus-As-the-Neural-Network-of-Stylepedia">The Solution: Adopting Milvus As the Neural Network of Stylepedia</a></li><li><a class="globalArticleCTASection_anchorLink__JXvsH" href="/customers/mozat#The-Results-A-Fashion-Revolution">The Results: A Fashion Revolution</a></li><li><a class="globalArticleCTASection_anchorLink__JXvsH" href="/customers/mozat#Conclusion-Shaping-Personal-Style-Journeys-with-Mozat-and-Milvus">Conclusion: Shaping Personal Style Journeys with Mozat and Milvus</a></li></ul><div class="customerDetail_usagesWrapper__VQc0i"><div><p class="usageSection_title__xPVsF">Use case</p><ul class=""><li><a class="usageSection_link__iVJ0S" href="https://zilliz.com/vector-database-use-cases/image-similarity-search">Image Similarity Search</a></li></ul></div><div><p class="usageSection_title__xPVsF">Industry</p><ul class=""><li><p class="usageSection_text__4cm5X">Fashion</p></li></ul></div></div><div class="share_shareSection__JdOu2"><h4 class="share_shareTitle__cRU4n">Share this article</h4><div class="share_mediasWrapper__IYc0b"><button aria-label="twitter" class="react-share__ShareButton 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src="/images/layout/iso-logo.png" alt="ISO"/></div></div></div></footer></div><script id="__NEXT_DATA__" type="application/json" crossorigin="">{"props":{"pageProps":{"data":{"id":41,"customer_name":"Mozat","title":"Mozat Personalizes Fashion Discovery With Image Similarity Search Using Milvus","meta_title":"Mozat Personalizes Fashion Discovery Using Milvus","meta_description":"Explore how Milvus empowers Mozat’s fashion app, Stylepedia, to be a powerhouse of fashion intelligence. ","cover_image_url":"https://assets.zilliz.com/Group_4388_f72bdb1ba1.png","share_image_url":null,"start_quote":null,"end_quote":null,"content":"\u003ch2 id=\"About-Mozat\" class=\"common-anchor-header\"\u003eAbout Mozat\u003cbutton data-href=\"#About-Mozat\" class=\"anchor-icon\" translate=\"no\"\u003e\n \u003csvg\n aria-hidden=\"true\"\n focusable=\"false\"\n height=\"20\"\n version=\"1.1\"\n viewBox=\"0 0 16 16\"\n width=\"16\"\n \u003e\n \u003cpath\n fill=\"#0092E4\"\n fill-rule=\"evenodd\"\n d=\"M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z\"\n \u003e\u003c/path\u003e\n \u003c/svg\u003e\n \u003c/button\u003e\u003c/h2\u003e\u003cp\u003eFounded in 2003, \u003ca href=\"http://www.mozat.com/home\"\u003eMozat\u003c/a\u003e has been at the forefront of technology, spanning its business across Southeast Asia and Saudi Arabia. Specializing in social media, communication, and lifestyle applications, Mozat's crown jewel, an iPhone and Android application called \u003ca href=\"https://stylepedia.com/\"\u003eStylepedia\u003c/a\u003e, stood out as a testament to its creativity and dedication. This digital closet application offers users personalized style recommendations, integrates social media, and features an image search tool to discover similar fashion items. Mozat's Stylepedia reimagines fashion, fostering a sense of community and style exploration, where every outfit tells a story, and every user becomes a trendsetter.\u003c/p\u003e\n\u003cp\u003e\n \u003cspan class=\"img-wrapper\"\u003e\n \u003cimg src=\"https://assets.zilliz.com/mozat_stylepedia_acc8d14177.png\" alt=\"\" class=\"doc-image\" id=\"\" /\u003e\n \u003cspan\u003e\u003c/span\u003e\n \u003c/span\u003e\n\u003c/p\u003e\n\u003ch2 id=\"The-Challenge-Navigating-the-Vast-Realm-of-Fashion-Imagery\" class=\"common-anchor-header\"\u003eThe Challenge: Navigating the Vast Realm of Fashion Imagery\u003cbutton data-href=\"#The-Challenge-Navigating-the-Vast-Realm-of-Fashion-Imagery\" class=\"anchor-icon\" translate=\"no\"\u003e\n \u003csvg\n aria-hidden=\"true\"\n focusable=\"false\"\n height=\"20\"\n version=\"1.1\"\n viewBox=\"0 0 16 16\"\n width=\"16\"\n \u003e\n \u003cpath\n fill=\"#0092E4\"\n fill-rule=\"evenodd\"\n d=\"M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z\"\n \u003e\u003c/path\u003e\n \u003c/svg\u003e\n \u003c/button\u003e\u003c/h2\u003e\u003cp\u003eMozat envisioned Stylepedia as more than just a virtual closet but meant to be a place of hyper-personalized fashion suggestions tailored to individual tastes. However, this ambition came with its set of challenges. One of the major hurdles was the need to process a vast database of clothing images, growing exponentially every day. At the same time, the system had to deliver fast responses to users’ image queries for similar fashion style within milliseconds.\u003c/p\u003e\n\u003cp\u003eMoreover, Mozat had to handle massive user-uploaded photos of varying resolutions, angles, and sizes. The challenge was clear: Mozat needed a technology that could efficiently store, recognize, comprehend, and compare these images, delivering lightning-fast and accurate results.\u003c/p\u003e\n\u003ch2 id=\"The-Solution-Adopting-Milvus-As-the-Neural-Network-of-Stylepedia\" class=\"common-anchor-header\"\u003eThe Solution: Adopting Milvus As the Neural Network of Stylepedia\u003cbutton data-href=\"#The-Solution-Adopting-Milvus-As-the-Neural-Network-of-Stylepedia\" class=\"anchor-icon\" translate=\"no\"\u003e\n \u003csvg\n aria-hidden=\"true\"\n focusable=\"false\"\n height=\"20\"\n version=\"1.1\"\n viewBox=\"0 0 16 16\"\n width=\"16\"\n \u003e\n \u003cpath\n fill=\"#0092E4\"\n fill-rule=\"evenodd\"\n d=\"M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z\"\n \u003e\u003c/path\u003e\n \u003c/svg\u003e\n \u003c/button\u003e\u003c/h2\u003e\u003cp\u003eIn their quest for a solution, the Mozat team found their answer in Milvus. It supports mainstream vector indexes and enables real-time searches on billions of vectors of datasets, making Milvus the ideal choice as the \u003ca href=\"https://zilliz.com/glossary/neural-networks\"\u003eneural network\u003c/a\u003e for Stylepedia’s image search system.\u003c/p\u003e\n\u003cp\u003eThe image search system involves four modules:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cstrong\u003eGarment detection\u003c/strong\u003e for detecting real-time objects and identifying clothing items and classifications.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eFeature extraction\u003c/strong\u003e: converting images into 512-dimensional vectors.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eVector similarity search:\u003c/strong\u003e for large-scale similarity searches.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003ePost-processing:\u003c/strong\u003e for refining results using color and critical label filtering, ensuring image quality alignment.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eStylepedia utilizes Milvus in the vector similarity search module to support large-scale image similarity searches. Its workflow includes two parts. On the storage side, object detection and feature extraction models convert the entire fashion image library into 512-dimensional feature vectors. These vector data are then indexed and stored in Milvus. On the query side, machine learning models transform users’ query images into feature vectors. Milvus then performs ANN searches for the Top-K results most relevant to the query vectors and obtains their corresponding image IDs. Finally, after post-processing (filtering, sorting, etc.), Stylepedia returns a collection of similar images to the user.\u003c/p\u003e\n\u003cp\u003e\n \u003cspan class=\"img-wrapper\"\u003e\n \u003cimg src=\"https://assets.zilliz.com/stylepedia_image_search_system_f6d73ba056.png\" alt=\"\" class=\"doc-image\" id=\"\" /\u003e\n \u003cspan\u003e\u003c/span\u003e\n \u003c/span\u003e\n\u003c/p\u003e\n\u003cp\u003eBy leveraging Milvus, Stylepedia innovates three essential functions.\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cstrong\u003eSearching for similar clothing items\u003c/strong\u003e: Users can upload pictures of their clothes to find similar products in their digital closet.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eOutfit suggestions\u003c/strong\u003e: Users discover fashion photos containing specific items through similarity searches, aiding in new purchases or unique pairings.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eFashion photograph recommendations\u003c/strong\u003e: The system analyzes browsing history and digital closet contents to provide tailored fashion photo recommendations.\u003c/li\u003e\n\u003c/ul\u003e\n\u003ch2 id=\"The-Results-A-Fashion-Revolution\" class=\"common-anchor-header\"\u003eThe Results: A Fashion Revolution\u003cbutton data-href=\"#The-Results-A-Fashion-Revolution\" class=\"anchor-icon\" translate=\"no\"\u003e\n \u003csvg\n aria-hidden=\"true\"\n focusable=\"false\"\n height=\"20\"\n version=\"1.1\"\n viewBox=\"0 0 16 16\"\n width=\"16\"\n \u003e\n \u003cpath\n fill=\"#0092E4\"\n fill-rule=\"evenodd\"\n d=\"M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z\"\n \u003e\u003c/path\u003e\n \u003c/svg\u003e\n \u003c/button\u003e\u003c/h2\u003e\u003cp\u003eEmpowered by \u003ca href=\"https://zilliz.com/what-is-milvus\"\u003eMilvus\u003c/a\u003e, Stylepedia emerged as a powerhouse of fashion intelligence. The increasing data volume was no longer a concern as Milvus handled billions of \u003ca href=\"https://zilliz.com/glossary/vector-embeddings\"\u003evectors\u003c/a\u003e, scaling out seamlessly. Stylepedia could now generate real-time responses to user queries, vastly improving user experience. Users could upload images of their clothes and quickly receive a curated selection of similar garments, making Stylepedia an artful fusion of technology and style expertise.\u003c/p\u003e\n\u003cp\u003eWith Milvus, Stylepedia becomes a fashion confidant, predicting trends, understanding individual tastes, and empowering users to embrace their style identity.\u003c/p\u003e\n\u003ch2 id=\"Conclusion-Shaping-Personal-Style-Journeys-with-Mozat-and-Milvus\" class=\"common-anchor-header\"\u003eConclusion: Shaping Personal Style Journeys with Mozat and Milvus\u003cbutton data-href=\"#Conclusion-Shaping-Personal-Style-Journeys-with-Mozat-and-Milvus\" class=\"anchor-icon\" translate=\"no\"\u003e\n \u003csvg\n aria-hidden=\"true\"\n focusable=\"false\"\n height=\"20\"\n version=\"1.1\"\n viewBox=\"0 0 16 16\"\n width=\"16\"\n \u003e\n \u003cpath\n fill=\"#0092E4\"\n fill-rule=\"evenodd\"\n d=\"M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z\"\n \u003e\u003c/path\u003e\n \u003c/svg\u003e\n \u003c/button\u003e\u003c/h2\u003e\u003cp\u003eMozat's collaboration with Milvus marked a new era in fashion discovery. Stylepedia ceased to be just an app; it became a harmonious fusion of human creativity and machine intelligence. 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