The newest addition to our portfolio of solutions is the Comics Identification (/v2/comics_id). This service is designed to identify comics from images. While it’s still in the early stages, we are actively refining and enhancing its capabilities.

The API detects the largest comic book in an image, and provides key information such as the title, issue number, release date, publisher, origin date, and creator’s name, making it ideal for identifying comic books, magazines, as well as manga.

This tool is perfect for organizing and cataloging large comic collections, offering accurate identification and automation of metadata extraction. Whether you’re managing a digital archive or cataloging physical collections, the Comics Identification API streamlines the process by quickly delivering essential details. We’re committed to continuously improving this service to meet the evolving needs of comic identification.

Star Wars Unlimited, Digimon, Dragon Ball, and More Can Now Be Recognized by Our System

Our trading card identification system has already been widely used to accurately recognize and provide detailed information on cards from games like Pokémon, Yu-Gi-Oh!, Magic: The Gathering, One Piece, Flesh and Blood, MetaZoo, and Lorcana.

Recently, we’ve expanded the system to include cards from Garbage Pail Kids, Star Wars Unlimited, Digimon, Dragon Ball Super, Weiss Schwarz, and Union Arena. And we’re continually adding new games based on demand. For the full and up-to-date list of recognized games, check out our API documentation.

Detect and Identify Both Trading Cards and Their Slab Labels

The new endpoint slab_grade processes your list of image records to detect and identify cards and slab labels. It utilizes advanced image recognition to return detailed results, including the location of detected items and analyzed features.

The Slab Label object provides essential information, such as the company or category (e.g., BECKETT, CGC, PSA, SGC, MANA, ACE, TAG, Other), the card’s grade, and the side of the slab. This endpoint enhances our capability to categorize and assess trading cards with greater precision. In our App, you will find it under Collectibles Recognition: Slab Reading & Identification.

Automatic Recognition of Collectibles

Ximilar built an AI system for the detection, recognition and grading of collectibles. Check it out!

Read more

New Endpoint for Card Centering Analysis With Interactive Demo

Given a single image record, the centering endpoint returns the position of a card and performs centering analysis. You can also get a visualization of grading through the _clean_url_card and _exact_url_card fields.

The _tags field indicates if the card is autographed, its side, and type. Centering information is included in the card field of the record.

Learn How to Scan and Identify Trading Card Games in Bulk With Ximilar

Our new guide How To Scan And Identify Your Trading Cards With Ximilar AI explains how to use AI to streamline card processing with card scanners. It covers everything from setting up your scanner and running a Python script to analyzing results and integrating them into your website.

Let Us Know What You Think!

And that’s a wrap on our latest updates to the platform! We hope these new features might help your shop, website, or app grow traffic and gain an edge over the competition.

If you have any questions, feedback, or ideas on how you’d like to see the services evolve, we’d love to hear from you. We’re always open to suggestions because your input shapes the future of our platform. Your voice matters!

The post New AI Solutions for Card & Comic Book Collectors appeared first on Ximilar: Visual AI for Business.

Our AI-powered Product Description revolutionizes the way you manage your fashion apparel catalogs by fully automating the creation of product titles and descriptions. Instead of spending hours manually tagging and writing descriptions, our AI-driven generator swiftly produces optimized texts, saving you valuable time and effort.

With the ability to customize style, tonality, format, length, and preferred product tags, you can ensure that each description aligns perfectly with your brand’s voice and SEO needs. This service is designed to streamline your workflow, providing accurate, engaging, and search-friendly descriptions for your entire fashion inventory.

Enhanced Taxonomy for Accessories Product Tagging

We’ve upgraded our taxonomy for accessories tagging. For sunglasses and glasses, you can now get tags for frame types (Frameless, Fully Framed, Half-Framed), materials (Combined, Metal, Plastic & Acetate), and shapes (Aviator, Cat-eye, Geometric, Oval, Rectangle, Vizor/Sport, Wayfarer, Round, Square). Try how it works on your images in our public demo.

Automate Detection & Tagging of Home Decor Images With AI

Our new Home Decor Tagging service streamlines the process of categorizing and managing your home decor product images. It uses advanced recognition technology to automatically assign categories, sub-categories, and tags to each image, making your product catalog more organized. You can customize the tags and choose translations to fit your needs.

The service also offers flexibility with custom profiles, allowing you to rename tags or add new ones based on your requirements. For pricing details and to see the service in action, check our API documentation or contact our support team for help with custom tagging and translations.

Visual Search for Home Decor: Find Products With Real-Life Photos

With our new Home Decor Search service, customers can use real-life photos to find visually similar items from your furniture and home decor catalogue.

Our tool integrates four key functionalities: home decor detection, product tagging, colour extraction, and visual search. It allows users to upload a photo, which the system analyzes to detect home decor items and match them with similar products from your inventory.

To use Home Decor Search, you first sync your database with Ximilar’s cloud collection. This involves processing product images to detect and tag items, and discarding the images immediately after. Once your data is synced, you can perform visual searches by submitting photos and retrieving similar products based on visual and tag similarity.

The API allows for customized searches, such as specifying exact objects of interest or integrating custom profiles to modify tag outputs. For a streamlined experience, Ximilar offers options for automatic synchronization and data mapping, ensuring your product catalog remains up-to-date and accurate.

The post New Solutions & Innovations in Fashion and Home Decor AI appeared first on Ximilar: Visual AI for Business.

AI’s Impact on Fashion: Turning the Industry on Its Head

The latest buzz in the fashion e-commerce realm revolves around visual AI. From AI-powered fashion design to AI-generated fashion models, and all the new AI tools, which rapidly change our shopping experience by quietly fueling the product discovery engines in the background, often unnoticed.

Key AI-Powered Technologies in Fashion E-Commerce

So what are the main AI technologies shaking up fashion e-commerce lately? And why is it important to keep up with them?

Recognition, Detection & Data Enrichment in Fashion

In the world of fashion e-commerce, time is money. Machine learning techniques now allow fashion e-shops to upload large unstructured collections of images and extract all the necessary information from them within milliseconds. The results of fashion image recognition (tags/keywords) serve various purposes like product sorting, filtering, searching, and also text generation.

These tools are indispensable for today’s fashion shops and marketplaces, particularly those with extensive stock inventories and large volumes of data. In the past few years, automated fashion tagging has made time-consuming manual product tagging practically obsolete.

Generative AI Systems for Fashion

The fashion world has embraced generative artificial intelligence almost immediately. Utilizing advanced AI algorithms and deep learning, AI can analyze images to extract visual attributes such as styles, colours, and textures, which are then used to generate visually stunning designs and written content. This offers endless possibilities for creating personalized shopping experiences for consumers.

Our AI also enables you to automate the writing of all product titles and product descriptions via API, directly utilizing the product attributes extracted with deep tagging and letting you select the tone, length, and other rules to get SEO-friendly texts quickly. We’ll delve deeper into this later on.

Fashion Discovery Engines and Recommendation Systems

Fashion search engines and personalized recommendations are game-changers in online shopping. They are powered by our speciality: visual search. This technology analyzes images in depth to capture their essence and search vast product catalogs for identical or similar products. Three of its endless uses are indispensable for fashion e-commerce: similar items recommendations, reverse image search and image matching.

Visual search enables shoppers to effortlessly explore new styles, find matching pieces, and stay updated on trends. It allows you to have your own visual search engine, that rapidly scans image databases with millions of images to provide relevant and accurate search results within milliseconds. This not only saves you time but also ensures that every purchase feels personalized.

Shopping Assistants in Fashion E-Commerce and Retail

The AI-driven assistants guide shoppers towards personalized outfit choices suited for any occasion. Augmented Reality (AR) technology allows shoppers to virtually try on garments before making a purchase, ensuring their satisfaction with every selection. Personalized styling advice and virtual try-ons powered by artificial intelligence are among the hottest trends developed for fashion retailers and fashion apps right now.

Both fashion tags for occasions extracted with our automated product tagging, as well as similar item recommendations, are valuable in systems that assist customers in dressing appropriately for specific events.

My Fashion Website Needs AI Automation, What Should I Do?

Consider the Needs of Your Shoppers

To provide the best customer experience possible, always take into account your shoppers’ demographics, geographical location, language preferences, and individual styles.

However, predicting style is not an easy task. But by utilizing AI, you can analyze various factors such as user preferences, personal style, favoured fashion brands, liked items, items in their shopping baskets, and past purchases. Think about how to help them discover items aligned with their preferences and receive only relevant suggestions that inspire rather than overwhelm them.

There are endless ways to improve a fashion e-shop. Always keep in mind not to overwhelm the visitors, and streamline your offer to the most relevant items.

While certain customer preferences can be manually set up by users when logging into an app or visiting an e-commerce site, such as preferred sizes, materials, or price range, others can be predicted. For example, design preferences can be inferred based on similarities with items visitors have browsed, liked, saved, or purchased.

Three Simple Steps to Elevate Your Fashion Website With AI

Whether you run a fashion or accessories e-shop, or a vintage fashion marketplace, using these essential AI-driven features could boost your traffic, improve customer engagement, and get you ahead of the competition.

Automate Product Tagging & Text Generation

The image tagging process is fueled by specialised object detection and image recognition models, ensuring consistent and accurate tagging, without the need for any additional information. Our AI can analyze product images, identify all fashion items, and then categorize and assign relevant tags to each item individually.

In essence, you input an unstructured collection of fashion images and receive structured metadata, which you can immediately use for searching, sorting, filtering, and product discovery on your fashion website.

The keywords extracted by AI can serve right away to generate captivating product titles and descriptions using a language model. With Ximilar, you can pre-set the tone and length, and even set basic rules for AI-generated texts tailored for your website. This automates the entire product listing process on your website through a single API integration.

Streamline and Automate Collection Management With AI

Visual AI is great for inventory management and product gallery assembling. It can recognize and match products irrespective of lighting, format, or resolution. This enables consistent image selection for product listings and galleries.

You can synchronise your entire fashion apparel inventory via API to ensure continual processing by up-to-date visual AI. You can either set the frequency of synchronization (e.g., the first day of each month) or schedule the synchronization run every time you add a new addition to the collection.

For example, you can showcase all clothing items on models in product listings or display all accessories as standalone photos in the shopping cart. Additionally, you can automate tasks like removing duplicates and sorting user-generated visual content, saving a lot of valuable time. Moreover, AI can be used to quickly spot inappropriate and harmful content.

Provide Relevant Suggestions & Reverse Image Search

During your collection synchronisation, visual search processes each image and each product in it individually. It precisely analyzes various visual features, such as colours, patterns, edges and other structures. Apart from the inventory curation, this will enable you to:

1. Have your custom fashion recommendation system. You can provide relevant suggestions from your inventory anywhere across the customer journey from the start page to the kart.
2. Improve your website or app with a reverse image search tool. Your visitors can search with smartphone photos, product images, pictures from Pinterest, Instagram, screenshots, or even video content.

Since fashion detection, image tagging and visual search are the holy trinity of fashion discovery systems, we’ve integrated them into a single service called Fashion Search. Check out my article Everything You Need to Know About Fashion Search to learn more.

Visual search can match images, independent of their origin (e.g., professional images vs. user-generated content), quality and format. We can customize it to fit your collection, even for vintage pieces, or niche fashion brands. For a firsthand experience of how basic fashion visual search operates, check out our free demo.

How Does the Automated Fashion Tagging Work?

Let’s take a closer look at the basic AI-driven tool for the fashion industry: automated fashion tagging. Our product tagging is powered by a complex hierarchy of computer vision models, that work together to detect and recognize all fashion products in an image. Then, each product gets one category (e.g., Clothing), one or more subcategories (e.g., Evening dresses or Cocktail dresses), and a varied set of product tags.

To name a few, fashion tags describe the garment’s type, cut, fit, colours, material, or patterns. For shoes, there are features such as heels, toes, materials, and soles. Other categories are for instance jewellery, watches, and accessories.

The fashion taxonomy encompasses hundreds of product tags for all typical categories of fashion apparel and accessories. Nevertheless, we continually update the system to keep up with emerging trends in the fashion industry. Custom product tags, personal additions, taxonomy mapping, and languages other than the default English are also welcomed and supported. The service is available online – via API.

How Do I Use the Automated Fashion Tagging API?

You can seamlessly integrate automated fashion tagging into basically any website, store, system, or application via REST API. I’d suggest taking these steps first:

First, log into Ximilar App – After you register into Ximilar App, you will get the unique API authentication token that will serve for your private connection. The App has many useful functions, which are summarised here. In the past, I wrote this short overview that could be helpful when navigating the App for the first time.

If you’d like to try creating and training your own additional machine learning models without coding, you can also use Ximilar App to approach our computer vision platform.

Secondly, select your plan – Use the API credit consumption calculator to estimate your credit consumption and optimise your monthly supply. This ensures your credit consumption aligns with the actual traffic on your website or app, maximizing efficiency.

And finally, connect to API – The connection process is described step by step in our API documentation. For a quick start, I suggest checking out First Steps, Authentication & Image Data. Automated Fashion Tagging has dedicated documentation as well. However, don’t hesitate to reach out anytime for guidance.

Do You Need Help With the Setup?

Our computer vision specialists are ready to assist you with even the most challenging tasks. We also welcome all suggestions and custom inquiries to ensure our solutions meet your unique needs. And if you require a custom solution, our team of developers is happy to help.

We also offer personalized demos on your data before the deployment, and can even provide dedicated server options or set up offline solutions. Reach out to us via live chat for immediate assistance and our team will guide you through the entire process. Alternatively, you can contact us via our contact page, and we will get back to you promptly.

The post How Fashion Tagging Works and Changes E-Commerce? appeared first on Ximilar: Visual AI for Business.

Huge App Updates

The Ximilar App is the winner in terms of updates. So far, there was just the straightforward Image Recognition service available since we acquired Vize in 2018. From now on you can manage also Fashion Tagging, Generic Image Tagging & Image Similarity — the fastest similarity engine on the market. All these services were only available upon request via API. And now anybody — yes, you too! — can use these services right away, thanks to Libor Vanek, our new member of developer team.

Available AI Services in the App

• Image Recognition — available for all users
• Generic Tagging — available for all users
• Fashion Tagging — for Business & Professional plans
• Image Similarity —available for all users

Image Similarity Search in The App

One of the core Ximilar services, available in the App, is Image Similarity. Given an image, the service returns the most visually similar images from your collection. It is made to process extensive collections in a fraction of a second. Ximilar offers two flavours — one is for generic photos and the other is tailored for product photos (especially fashion and home decor). It is one of the most GPU consuming services we offer and in terms of backend complexity, this one is the most challenging. And now, thanks to Ximilar, you don’t need to worry about that — just click Activate in the App and there you go! Read more about in our latest blog post.

There is even more to come. Each service has its own user interface & settings, so you can play and adjust each service 24/7. And — we’re working hard to bring all our Artificial Intelligence Services to be available within the Ximilar App. Stay tuned!

Better Traffic & API Credits Monitor

We have significantly upgraded the depth of information available on the main service dashboard, giving you extensive information on how the given service performs as well as more information about use of traffic and your API credits.

Payments by Credit Card

This one is a biggie. For a long time, we have been working on all the services and their feature set. And we’ve postponed this rather challenging feature for later. This fall, Martin Novak took the charge of this bit and we now proudly offer instant payments. That brings easy activation and upgrades from Free plan, to Business or Professional plans.

Payments are then recurrent. Processed automatically each month. You don’t need to think about wire-transfers being processed manually any more.

Team Collaboration

For the Professional plan, we’ve also added quite a requested feature, offering you a single Workspace, which you can access from several user accounts. So it is now much easier to work on a large project with your co-workers.

PrestaShop Plugin

As we grow in the fashion AI business and overall E-commerce, the time has come to address various plugins for platforms like Shopify, Magento & others. PrestaShop plugin being the first of the fleet, named Visually Related Products and soon to be available in the PrestaShop Addons Marketplace.

Model Download & Mobile Usage

Yes! This news will make many Ximilar users happy.

Honestly, it takes some time to migrate from one framework to another. But it was definitely worth the effort. With the new TensorFlow 2, our models can be downloaded for mobile usage. Thanks to Ximilar, you are able to train image classifiers without writing a single line of code. Isn’t that amazing?

You are able to download the model for offline usage. Meaning all kinds of devices including cellphones and various IoT home appliances. You are now fully independent of our API in the production environment. The models work on Android, iOS and qualified IoT platforms. This feature is currently in the testing phase and is only available in custom plans. If you would like to try it, please contact sales@ximilar.com to find a suitable setup for your needs.

Fashion Improvements

Our team of editors, managed by Nessi Voinova, is working hard on all things Fashion. Most important is a comprehensive guide to Ximilar Fashion Taxonomy, with examples showing precisely all the crazy garment names such as blouses, cardigans, polo-shirts, shirts, sweaters, sweatshirts, tops, t-shirts, tunics, vests & some hundreds more for clothes, shoes & accessories.

Annotate App

Another long-awaited tool we are introducing is our comprehensive Annotate App. It is a quite advanced annotation app for product & fashion photography, developed initially only for our skilled internal team of content editors. We quickly realized, that such a tool might also help you if you already know a little about how computer vision and artificial intelligence work.

There is also an improved and redesigned Fashion Demo for you to try.

The App Features

• Annotation Jobs — manage your annotation pipeline in complex projects
• Comprehensive Tagging — single image view, with all available tasks and tags
• Image Canvas drawing (beta) — photoshop-like tool for drawing on images
• Custom Object Detection (beta) — train models predicting the location of objects in the photo

Annotate App is now available for our existing customers on higher pricing plans as a new feature, and we hope this will hugely improve your ability to optimize and enhance your own product data to deliver more relevant content for your online outlets as well as for any internal technology, that might require this kind of manual work. You can read more about the annotate application in our next blog post, which will be released soon.

Services Status Monitoring

As we grew also in terms of the amount of servers, their complexity and stability, we have super-powered, load-balanced and backed up everything we could to deliver faster & more reliable service to our customer base. All Ximilar services are now monitored by a reliable external tool and the availability is always within easy reach at status.ximilar.com.

It brings better insight to you and us on how all services perform and if there is any kind of unexpected or planned outage.

Behind the Scene

There were multiple technical updates under the hood, that had a simple target → to deliver faster, easy accessible AI services to each of our customers. We have improved the accuracy of all our services, implemented a machine learning loop (storing images uploaded by customers and adding them to your training data) and did all kinds of refactoring and updates. All that while delivering quality Proof Of Concepts to custom solutions requested by some advanced customers requiring quite challenging AI applications.

We gathered experience from projects related to healthcare (microscopy analysis of biological samples, X-ray imaging), OCR and Visual Quality Assurance in the industry. Deployment to our new cloud was also a great challenge, but thanks to our DevOps team we managed it flawlessly.

Other changes were not so technical, we grow as a team and our previous offices were not enough for our needs. So we decided to move to our new offices at South Moravian Innovation Centre. We love the startup culture and the people around us are very helpful.

Future Plans at Ximilar

And that is not the end. We are constantly working on many new features for Ximilar App and Annotate App. Some of them will be unveiled in Q1 2020, and some will remain highly customized for each special use case. The first feature which we are working on is Flows which would help you connect multiple recognition tasks to one workflow. We are also improving machine learning to match current standards and knowledge, and that requires a little bigger team → so we are happy to welcome some super-brains at Ximilar.

We also have ideas for new, never seen, services which will help your business grow. But hey, the day only has 24 hours, so we surely need to prioritize. That being said, we are so happy about how the last year turned out. We have stabilised our fast growth on all major fronts — technology, team, service quality & reliability, and business development. Wow, what a year!

The post Major Updates Across the Board for 2020 appeared first on Ximilar: Visual AI for Business.

New Label Types: Categories & Tags

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