These updates aim to improve your experience and streamline plan setup and credit consumption optimization. Here’s a quick rundown of what’s new.

Plan Setup: Simplified Subscription Management

We’ve revamped the subscription page with new features and better functionality. The Plan Setup page now allows you to choose between Free, Business, or Professional plans, customize your monthly credit supply using a slider, and access our new API Credit Consumption Calculator—a handy tool to help you make informed decisions.

The entire checkout process has been streamlined as well, allowing you to adjust your payment method directly before completing your purchase.

Manage Your Payment Methods and Currencies

You can change the default currency for plan setup and payments in the Settings. To update your payment method, simply access the Stripe Portal from your Plan Overview under “More Actions.” If you prefer a different payment method or have any additional questions, feel free to reach out to us!

Credit Calculator: Estimate & Optimise Your Credit Consumption

One of the most exciting additions to the app is the new Credit Calculator, now available directly within the platform. While this tool was previously featured on our Pricing page, it’s now integrated into the app as well, allowing you to not only estimate your credit needs but also preset your subscription plan directly from the calculator.

Once you’ve adjusted your credits based on projected usage, you can proceed straight to checkout, making the entire process of optimizing and purchasing credits smoother and more efficient.

Plan Overview: A Complete View of Your Plans and Credits

The page Plan Overview gives you a comprehensive view of your active subscription, any past plans, and your pre-paid credit packs. Previously, credit information was limited to your dashboard, but now you have detailed insight into your credit usage and plan history.

In the Plan Overview, you can view all your current active subscription plans. If you upgrade or downgrade, multiple plans may temporarily appear, as credits from your previous plan remain available until the end of the billing period.

Reports: Detailed Insights into Credit Usage

Our new Reports page enables you to gain deeper insights into your API credit usage. It provides two types of reports: credit consumption by AI solution (e.g., Card Grading) and by individual operation within a solution (e.g., “grade one card” within the Card Grading solution).

Credit Packs: Flexibility to Buy Extra Credits Anytime

API Credit packs act as a safety net for unexpected system loads. Now available on their dedicated page, you can purchase additional API credit packs as needed. You can also compare pricing against higher subscription plans and choose the most cost-effective option. Both your active and used credit packs will be displayed on the Plan Overview page.

Invoices: All Your Purchases in One Place

This updated page neatly lists all your invoices, including both subscription payments and one-time credit pack purchases, ensuring that all your financial information is in one place.

Greater Control & Flexibility For the Users

These updates are designed to provide you with greater control, transparency, and flexibility as you build and deploy visual AI solutions. All of these features are now accessible in your sidebar. Check them out, and feel free to reach out with any questions!

The post We Introduce Plan Overview & Advanced Plan Setup appeared first on Ximilar: Visual AI for Business.

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.

Sports Cards Collecting on The Rise

Collecting sports cards, including hockey cards, has been a popular hobby for many people. Especially during my childhood, I collected hockey cards, as a big fan of the sport. Today, card collecting has evolved into an investment, and many new collectors enter the community solely to buy and sell cards on various marketplaces.

Some traditional baseball rookie cards can have significant value, for example, the estimated price of a vintage Mickey Mantle PSA 10 1952 Topps rookie baseball card is $15 million – $30 million.

Our Existing Solutions for Card Collector Sites & Apps

Last year, we already released several services focused on trading cards:

• First, we released a Trading Card Game Identifier API. It can identify trading card games (TCGs), such as Pokémon, Magic The Gathering: MTG and Yu-Gi-Oh!, and more. We believe that this system is amongst the fastest, most precise and accurate in the world.

• Second, we built a Card Grading and fast Card Conditioning API for both sports and trading card games. This service can instantly evaluate each corner, edges, and surface, and check the centring in a card scan, screenshot or photo in a matter of seconds. Each of these features is graded independently, resulting in an overall grade. The outputs can be both values or conditions-based (eBay or TCGPlayer naming). You can test it here.

• We have also been building custom visual search engines for private collections of trading cards and other collectibles. With this feature, people can visit marketplaces or use their apps to upload card images, and effortlessly search for identical or similar items in their database with a click. Visual search is a standard AI-powered function in major price comparators. If a particular game is not on our list, or if you wish to search within your own collection, list, or portfolio of other collectibles (e.g., coins, stamps, or comic books), we can also create it for you – let us know.

We have been gradually establishing a track record of successful projects in the collectibles field. From the feedback of our customers, we hear that our services are much more precise than the competition. So a couple of months ago, we started building a sports card scanning system as well. It allows users to send the scan to the API, and get back precise identification of the card.

Our API is open to all developers, just sign up to Ximilar App, and you can start building your own great product on top of it!

Test it Now in Live Demo

This solution is already available for testing in our public demo. Try it for free now!

The Main Features of Sports Cards

There are several factors determining the value of the card:

• Rarity & Scarcity: Cards with limited production runs or those featuring star players are often worth more.

• Condition: Like any collectible item, the condition of a sports card is crucial. Cards in mint or near-mint condition are generally worth more than those with wear and tear.

• Grade & Grading services: Graded cards (from PSA or Beckett) typically have higher prices in the market.

• The fame of the player: Names of legends like Michael Jordan or Shohei Ohtani instantly add value to the trading cards in your collection.

• Autographs, memorabilia, and other features, that add to the card’s rarity.

Each card manufacturer must have legal rights and licensing agreements with the sports league, teams, or athletes. Right now, there are several main producers:

• Panini – This Italian company is the largest player in the market in terms of licensing agreements and number of releases.

• Topps – Topps is an American company with a long history. They are now releasing cards from Baseball, Basketball or MMA.

• Upper Deck – Upper Deck is a company with an exclusive license for hockey cards from the NHL.

• Futera – Futera focuses mostly on soccer cards.

Dozens of other card manufacturers were acquired by these few players. They add their brands or names as special sets in their releases. For example, the Fleer company was acquired by Upper Deck in 2005 and Donruss was bought by Panini.

Identifying Sports Cards With Artificial Intelligence

When it comes to sports cards, it’s crucial to recognize that the identification challenge is more complex than that of Pokémon or Magic The Gathering cards. While these games present challenges such as identical trading card artworks in multiple sets or different language variants, sports cards pose distinct difficulties in recognition and identification, such as:

• Amount of data/cards – The companies add a lot of new cards into their portfolio each year. As of the latest date, the total figure exceeds tens of millions of cards.

• Parallels, variations, and colours – The card can have multiple variants with different colours, borders, various foil effects, patterns, or even materials. More can be read in a great article by getcardbase.com. Look at the following example of the NBA’s LeBron James card, and some of its variants.

• Special cards: Short Print (SP) and Super Short Print (SSP) cards are intentionally produced in smaller quantities than the rest of the particular set. The most common special cards are Rookie cards (RC) that feature a player in their rookie season and that is why they hold sentimental and historical value.

• Serial numbered cards: A type of trading cards that have a unique serial number printed directly on the card itself.

• Authentic signature/autograph: These are usually official signature cards, signed by players. To examine the authenticity of the signature, and thus ensure the card’s value, reputable trading card companies may employ card authentication processes.

• Memorabilia: In the context of trading cards, memorabilia cards are special cards that feature a piece of an athlete’s equipment, such as a patch from a uniform, shoe, or bat. Sports memorabilia are typically more valuable because of their rarity. These cards are also called relic cards.

As you can see, it’s not easy to identify the card and its price and to keep track of all its different variants.

Example: Panini Prizm Football Cards

Take for example the 2022 Panini Prizm Football Cards and the parallel cards. Gold Prizms (10 cards) are worth much more than the Orange Prizms (with 250 cards) because of their scarcity. Upon the release of a card set, the accompanying checklist, presented as a population table, is typically made available. This provides detailed information about the count for each variation.

Next, for Panini Prizm, there are more than 20 parallel foil patterns like Speckle, Hyper, Diamond, Fast Break/Disco/No Huddle, Flash, Mozaic, Mojo, Pulsar, Shimmer, etc. with all possible combinations of colours such as green, blue, pink, purple, gold, and so on.

These combinations matter because some of them are more rare than others. There are also different names for the foil cards between companies. Topps has chrome Speckle patterns which are almost identical to the Panini Prizm Sparkle pattern.

Lastly, no database contains each picture for every card in the world. This makes visual search extremely hard for cards that have no picture on the internet.

Luckily, we developed (and are actively improving) an AI service that is trying to tackle the mentioned problems with sports cards identification. This service is available on click as an open REST API, so anyone can connect to develop and integrate their system with ours. The results are in seconds and it’s one of the fastest services available in the market.

How to Identify Sports Cards Via API?

In general, you can use and connect to the REST API with any programming language like Python or Javascript. Our developer’s documentation will serve you as a guide with many helpful instructions and tips.

To access our API, sign in Ximilar App to get your unique API authentication token. You will find the administration of your services under Collectibles Recognition. Here is an example REST Request via curl:

$ curl https://api.ximilar.com/collectibles/v2/sport_id -H "Content-Type: application/json" -H "Authorization: Token __API_TOKEN__" -d '{
    "records": [
        { "_url": "__PATH_TO_IMAGE_URL__"}
    ], "slab_id": false
}'

The API response will be as follows:

• When the system succesfuly indetifies the card, it will return you full identification. You will get a list of features such as the name of the player/person, the name of the set, card number, company, team and features like foil, autograph, colour and more. It is also able to generate URL links for eBay searches so you can check the card values or purchase them directly.
• If we are not sure about the identification (or we don’t have a specific card in our system) the system will return empty search results. In such case, feel free to ask for support.

How AI Sports Cards Identification Works?

Our identification system uses advanced machine learning models with smart algorithms for post-processing. The system is a complex flow of models that incorporates visual search. We trained the system on a large amount of data, curated by our own annotation team.

First, we identify the location of the card in your photo. Second, we do multiple AI analyses of the card to identify whether it has autograph and more. The third step is to find the card in our collection with visual search (reverse image search). Lastly, we use AI to rerank the results to make them as precise as possible.

What Sports Cards Can Ximilar Identify?

Our sports cards database contains a few million cards. Of course, this is just a small subset of all collectible cards that were produced. Right now we focus on 6 main domains: Baseball cards, Football cards, Basketball cards, Hockey cards, Soccer and MMA, and the list expands based on demand. We continually add more data and improve the system.

We try to track and include new releases every month. If you see that we are missing some cards and you have the collection, let us know. We can agree on adding them to training data and giving you a discount on API requests. Since we want to build the most accurate system for card identification in the world, we are always looking for ways to gather more cards and improve the software’s accuracy.

Who Will Benefit From AI-Powered Sports Cards Identifier?

Access to our REST API can improve your position in the market especially if:

• You own e-commerce sites/marketplaces that buy & sell cards – If you have your own shop, site or market for people who collect cards, this solution can boost your traffic and sales.

• You are planning to design and publish your own collector app and need an all-in-one API for the recognition and grading of cards.

• You want to manage, organize and add data to your own card collection.

Is My Data Safe?

Yes. First of all, we don’t save the analysed images. We don’t even have so much storage capacity to store each analysed image, photo, scan and screen you add to your collection. Once our system processes an image, it removes it from the memory. Also, GDPR applies to all photos that enter our system. Read more in our FAQs.

How Fast is the System, Can I Connect it to a Scanner?

The system can identify one card scan in one second. You can connect it to any card scanner available in the market. The scanning outputs the cards into the folders, to which you can apply a script for card identification.

Sports Cards Recognition Apps You Can Build With Our API

Here are a few ideas for apps that you can build with our Sport Card Identifier and REST API:

• Automatic card scanning system – create a simple script that will be connected to our API and your scanners like Fujitsu fi-8170. The system will be able to document your cards with incredible speed. Several of our customers are already organizing their collections of TCGs (like Magic The Gathering or Pokémon) and adding new cards on the go.

• Price checking app or portfolio analysis – create your phone app alternative to Ludex or CollX. Start documenting the cards by taking pictures and grading your trading card collection. Our system can provide card IDs, pre-grade cards, and search them in an online marketplace. Easily connect with other collectors, purchase & sell the cards. Test our system’s ability to provide URLs to marketplaces here.

• Analysing eBay submission – would you like to know what your card’s worth and how many are currently available in the market? For how much was the card sold in the past? Track the price of the card over time? Or what is the card population? With our technology, you can build a system that can analyse it.

AI for Trading Cards and Collectors

So this is our latest narrow AI service for the collector community. It is quite easy to integrate it into any system. You can use it for automatic documentation of your collection or simply to list your cards on online markets.

For more information, contact us via chat or contact page, and we can schedule a call with you and talk about the technical and business details. If you want to go straight and implement it, take look at our developer’s API documentation and don’t hesitate to ask for guidance anytime.

Right now we are also working on Comics identification (Comic book, magazines and manga). If you would like to hear more then just contact us via email or chat.

The post How to Identify Sports Cards With AI appeared first on Ximilar: Visual AI for Business.

Today we are releasing three public API endpoints for evaluating card grade, centering and card condition with AI:

• Card Grading – the most complex endpoint that evaluates corners, edges, surface and centering
• Card Centering – computing just the centering of the card
• Card Condition – simple API for getting condition of the card for marketplace (ebay) submission

In this blog post, I would like to get more in-depth about the AI card grading solution. How we built it, what are the pros and cons, how it is different from PSA grading or Beckett grading services, and how you can use it via REST API for your website or app.

AI Card Grading Services as API

With the latest advances in artificial intelligence, it is becoming increasingly common in our daily lives, and collectible cards are a field that doesn’t get left behind. A lot of startups are developing their own card grading, identification, scanning and documenting systems. Some of them were already successfully sold to big players like eBay or PSA. Just to mention a few:

• CollX raises $5.5M to scan and evaluate the value of trading cards

• eBay acquires several startups from the collectors industry like TCGplayer and 3PM Shield LLC

• Collectible card trading platform Alt raises $75M

• PSA Acquires Genamint to introduce Next-Generation Grading process

• AI trading card startup Ludex raises $8M

To understand why card grading is so popular, let’s look at the standard grading process and how the industry works.

Standard Grading Process

Card grading has gained widespread popularity in the world of collectibles by offering a trusted way to assess trading cards to collectors. It’s a method that gives a fair and unbiased evaluation of a card’s condition, ensuring its authenticity and value. This appeals to both seasoned collectors who want to preserve their cards’ worth and newcomers looking to navigate the collectible market confidently.

The process involves sending cards to experts who carefully inspect them for qualities like centering, corners, edges, and surface. The standard grading process for trading cards involves these key steps:

1. Submission: Collectors send their cards to grading companies.

2. Authentication: Cards are checked for authenticity.

3. Grading: Cards are assessed for condition and assigned a grade from 1 to 10 on a grading scale by an expert.

4. Encapsulation: Graded cards are sealed in protective holders.

5. Labelling & Certification: Labels with card details and grades are added. Cards’ information is recorded for verification. Special labels (such as fugitive ink, QR codes, or serial numbers) are introduced to prevent tampering.

6. Return/Sale: Graded cards are returned to owners or sold for higher value.

Costs of Grading Services

The price for submitting cards and their grading depends on the company and the card. For example, the minimal grading price per card by PSA (Professional Sports Authenticator) is 15 USD, and it’s much more for more expensive cards.

You can pay hundreds of dollars if you have some rare baseball card from Topps or non-sports cards from Magic The Gathering or Yu-Gi-Oh! If your modern card collection contains hundreds of cards, the pricing can reach astronomical values. Of course, grading often makes the card’s value higher, depending on its condition and grade.

Pros And Cons of Classic Grading

Besides its costliness, classic grading has several other drawbacks:

• It is a time-consuming offline process that is not particularly ideal for large-scale grading of whole collections.
• Some grading companies would only grade cards with minimum submission value (declared value that is used for insurance).
• Also, customers can usually submit only cards from popular series such as Pokémon, Magic The Gathering, Yu-Gi-Oh!, Sport Topps cards, and Sport Panini cards.

Of course, there are also advantages – like a physically sealed slab with a graded card, confirming its authenticity, and grading done by experts who can look at a card from all different angles and not just from a single image.

Nevertheless, there are a lot of steps involved in card grading, and the entire process takes a lot of time and effort. AI grading can help with the entire workflow, from authentication to grading and labelling.

Computer vision can easily and consistently spot printing defects, analyze corners and edges individually and compute centering in a matter of seconds and for a fraction of the price.

Introducing Online AI Card Grading REST API Service

Fast & Affordable AI Card Grading

Our intention is by no means to replace expert grading companies like PSA, BGS, SGC or CGC with AI-powered card grading. We would rather like it to be a faster, more consistent & cheaper alternative for anyone who needs bulk pre-grading of their collections.

One use case for our AI grading service is to use it to automate the estimation of the declared value of the card. A declared value is the estimated value of the collectible card after PSA has graded it (read PSA’s explanation here).

First, you will submit your card for grading by just sending the photo to our API. After obtaining a grade from our service, you can use our visual search system or card ID for a price guide. Actually, you will not only get the final grade of the card but a detailed grading breakdown (for edges, corners, centering, and surface). Then you can decide by yourself if you want to spend more money for physical grading or to sell it on eBay.

How Do We Train AI to Grade Cards?

To build an AI grading system powered by computer vision and machine learning techniques, we needed a lot of data that imitated real-world use cases (usually user-generated content such as smartphone pictures).

We spent a lot of time building our own dataset, including damaging our own cards. Our purpose from the beginning was to have a grader that would work both on sports cards and trading card games (TCGs), as well as images of different qualities and with different positioning of the cards.

AI Card Grader Consists of Several AI Models

Our card grading solution integrates a number of machine learning models trained on specific datasets. After you upload a photo of a card, the system needs to be able to correctly detect its position. It then identifies the type of the card: a sports card or a trading card game. Another recognition model identifies whether the picture shows the front or back of the card.

After localization & simple identification, the card gets an individual evaluation of its parts. We trained numerous models for individual grading of corners, edges, card surface, and centering, in accordance with grading standards such as PSA or Beckett.

Of course, different types of cards require a different approach, which is why, for example, we have two different models for corners. While sports cards should have sharp corners, TCG cards are typically more rounded.

From the individual grades, we compute a final grade with condition evaluation. Another model is identifying autographed cards. The cards with autographs are generally more valuable.

The big advantage is that the output of the card grading is easy to visualize. That is why we also provide a simple image with the report for each graded card. There you can see a detailed grading breakdown for every part of the card.

Limitations of AI and Machine Learning in Card Grading

Of course, both humans and AI can make mistakes. There are some limitations of the system. Estimating card grades from the images requires relatively high-resolution images, with good lighting conditions and with low post-processing.

As a matter of fact, a lot of modern cameras in smartphones are currently not very good at close-up photos. Their sensors have gotten bigger over the years, and their AI is upscaling the photos. This makes them artificially sharp with cartoon-like effects. This can of course corrupt the overall results. However, as I previously mentioned, that is why we train the models on real-life images and gradually improve their performance.

Let’s Get Some Cards Graded Via Our Online API

Modern Basketball Card

We can test our AI grader via Ximilar App. For this purpose, I chose one of the classic basketball cards of Michael Jordan. BGS (Beckett) gave this card a grade of 6 (EX-MT).

Our online grading system assigned this card a final grade of 6.5. The centering is quite off, so the system graded it 6/10. The grading is still not perfect, as it misses the surface by quite a large margin. However, the final grade is quite close to the one received by Beckett.

In the breakdown image, you can see how the system evaluated individual parts of the card. The lines are drawn on the image, so you can see the details of individual grades for corners and edges. We hope that this brings more transparency to the algorithmic grading.

Vintage Baseball Card

Now let’s take a look at an image of a vintage sports card without an autograph. As an example, I chose the baseball card with Ed Mathews.

The final grade that the card receives is 6.0. The average corner value assigned by the system is 4.0 and edges are 7.0. The grade for the surface is 5.5 and the centering is 7.0 (left/right is 36/65 and top/bottom is 38/62).

We can take a look at the corners and think whether a professional grader would assign the same values. I personally think that the grade is reasonable. However, getting grades from a single image is hard. We’re also not trying to make the values precise up to decimals (e.g., 4.12453 for the upper left corner). We want this to be an affordable soft pre-grading solution.

Card corners are a bit blurry, so ideally, we would like to have a sharper image. However, we can see that the corners are not in the range of 7–10 grades but rather lower (4-6).

How Do We Compute the Final Grade?

We compute the final grade for corners and edges simply as an average of the individual values. We trained the centering grader according to the Beckett grading scale. It is in our opinion much better (has higher demands) than PSA in this case. So to get 10 points for centering, you need to have a 50/50 ratio – on top/bottom and left/right.

The good thing is, that since we provide values for all parts of the card, you don’t need to use our final grades. You can actually create and use your own formula for computing the final grade.

Card Centering API with AI

Some of our customers would like to compute just the centering of the card. That is why we publish also endpoint for this. It will return you offsets from left, right and top and bottom borders of the card. The offsets are relative and also absolute so you can visualize it in your application. Each API response contains image with visualized centering as part of the output:

Lightweight Grading, alias Card Condition Assessment

For customers that want to submit cards to online marketplaces and need to know just the condition of the card like Near Mint, Lightly Played, Heavily Played or Damaged we offer an additional endpoint for getting rough condition of your card. Because this endpoint (/v2/condition) is much simpler and also significantly cheaper than our /v2/grade endpoint. It’s great for a massive amount of data and suitable for collector shops all over the world. The API endpoint can be called from your application or we can write your own script that is able to analyze images/cards from Fujitsu scanners (Fujitsu FI-8170). If you also want to have a card identification service, our visual search AI can identify the TCGs like Pokemon, Magic The Gathering or Yugioh! with more than 98% accuracy.

You can ask to return the condition in several different formats like TCGPlayer, Ebay or our own.

The more about /v2/condition endpoint can be found in our documentation.

How You Can Test Ximilar Card Grader?

To test our online card grader API, you will need to log into the Ximilar App, where it is currently available to users of all plans for testing purposes. We are also currently working on a public demo.

The system is not perfect, neither is the real human grader. It will take us some time to develop something that will be near perfect and very stable. But I believe that we are on the right track to make AI-powered solutions in the collectibles industry more accessible and cheaper.

To Sum Up

The AI card grader is just one of many solutions by Ximilar that the collector community can use. Make sure to check out our AI Recognition of Collectibles. It is a universal service for the automated detection and recognition of all kinds of collectible items.

Automatic Recognition of Collectibles

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

Read more

If you would like us to customize any solution for collectors, just contact us and we will get back to you. We created these solutions (Card Identification and Card Grading) to be the best publicly available AI tools for collectors.

The post AI Card Grading – Automate Sports Cards Pre-Grading appeared first on Ximilar: Visual AI for Business.

However, as the world of trading card games expands, collectors increasingly require a versatile trading card game identifier. This tool should swiftly recognize various collectible cards, irrespective of your private collection or database. We accepted this challenge and built a Trading Card Game Identifier (Card ID). In this article, I will describe how it works, and how you can use it for your own App or website. We will also take a brief look at other additions to our Collectibles Recognition: OCR & grading system for both TCGs and sports.

Trading Card Games Identifier

What is the Card Identifier?

Card Identifier is an AI-powered tool by Ximilar able to recognize trading game cards in any image format and provide you with their attributes, such as the name, exact set, series, codes, number, or year of release. It also provides attributes such as information on whether the card is holo (foil-treated) or what alphabet or language it uses.

This solution is an extension of our core service AI Recognition of Collectibles (which does the basic image recognition of all collectible items) and expands its functionalities by detailed identification of specific trading games.

Card ID works independently of keywords and metadata. As a matter of fact, you can use it to generate keywords. You can save the output in JSON or use it for searching and filtering items on your webpage.

The attributes of cards, such as their name, date of release and set, are also typically used to find the trading card’s average price on marketplaces such as TCGPlayer or eBay. That is why for some cards, we can provide links to these sites right away.

There are several use-cases that you can use our card identifier, here are few of them:

• you can connect your card scanner like Fujitsu (fi-8170) and create an system for documenting & digitalising your card collectors inventory, save thousands of hours with AI analysis
• you can build a smartphone app that is able to identify a card from photo and get average price on ebay or tcgplayer
• you can create your own marketplace website for card reselling & listing. Our technology will help with card identification of incoming submissions.

Because our solutions are powered by computer vision, you can upload photos of as many cards as you want, with or without sleeves, under different lighting and conditions.

Which Games Can the Trading Card Game Identifier Recognize?

Pokémon TCG

The Pokémon Trading Card Game is one of the most popular trading games. Fans of all generations and nationalities have been playing Pokémon TCG ever since its release in 1998. Our identifier recognizes Pokémon cards in both English & Japanese and provides their attributes.

Magic The Gathering

MGT is a highly popular game. As of 2023, over 100 MTG sets have been released, with their numbers continually rising, making it increasingly challenging to keep pace with all the sets and new cards. Our identifier provides all basic information about the Magic The Gathering card in an uploaded photo, and we keep adding new attributes.

Yu-Gi-Oh!

Yu-Gi-Oh! is an iconic trading card game based on an anime series. Since its 1999 release, Yu-Gi-Oh! has garnered a dedicated community of players and collectors. Recognized as a top-selling TCG in 2009 by Guinness World Records, with over 22 billion cards sold worldwide, the demand for an AI model to assist with card identification is understandable.

From MetaZoo to Lorcana

TCGs such as MetaZoo TCG, Flesh and Blood TCG, One Piece Card Game, or Lorcana TCG are all smaller or more recent games, but they are starting to be more and more popular both in English-speaking and Asian countries.

Independent of card type, this endpoint will also provide information such as:

• Side – front or back of the card.

• Alphabet – such as Latin, Japanese, Korean, Chinese, and more.

• Holo/Foil – whether the card has a holo effect (aluminium foil).

• Autograph – this particular feature is common rather for baseball and other sports cards.

All this information is necessary to value trading cards properly. For instance, a Japanese card can have a different value than an English one, and a holo card can have a higher value than a regular one.

How Identifying Trading Card Games via API Works?

Connect to API

Once you register in Ximilar App, you will automatically get your own unique API token. You will need at least business pricing plan. Then you can access and use our solutions both via App & API:

• In the App, Card ID is a part of the Collectibles Recognition service. So if you upload your images there, the trading cards in them will be automatically recognized and identified.

• The REST API endpoint is simple to use and easy to integrate into your mobile app, website or card-sorting machines. If you’re new to deploying solutions via API, the API documentation is here to help you with the basic setup. You can also find a lot of helpful information in our Help Center.

• For a lot of cards we are able to provide links to TCG Player or Cardmarket so you will know the price of analysed cards immediatelly.

To access the Card Identifier by Ximilar, use the endpoint /v2/tcg_id:

https://api.ximilar.com/collectibles/v2/tcg_id

We are always here to answer your questions through the contact form or live chat and can also do the setup for you.

Implement Trading Card Game Identifier in Your App

Imagine you are building an app or a site catering to Yu-Gi-Oh! fans and collectors. When a visitor uploads a picture of a new card, our AI Recognition of Collectibles instantly detects the card’s position and confirms it as a trading card. Thanks to its object detection & image recognition capabilities, users can upload pictures containing multiple cards.

Subsequently, the Card ID provides the card’s attributes Name, Full Name, Set, Set Code, Card Number, Rarity and Year. This happens independently of your portfolio (collection) or database.

The identification of the record is fast (usually takes a second to process) and the results are provided in JSON. This way, the user can be provided with structured data on their trading card in a matter of seconds.

The identification works for almost all popular TCGs. And the good news is that our AI for card recognition is so powerful that we can extend it to other games. Let us know if you are missing any games.

New Solutions For Sports Cards

Sports Card Text Analysis With OCR & GPT

Because there are millions of sports cards, and it’s very hard to gather data for them, we have recently released another solution for text extraction from sports cards. The system is accessible via following endpoints:

https://api.ximilar.com/collectibles/v2/card_ocr_id
https://api.ximilar.com/collectibles/v2/sport_id

For the first endpoint. This technology is able to read all the texts in the photo with a card via Optical Character Recognition (OCR) and then provide information on the athlete via Large Language model (LLM) – GPT. This model is still in the works, however, it can help you with the automatization and labelling of the cards. If you have your own collection of sport’s cards then we can build you a precise, fast and affordable AI system for sports card identification.

The second endpoint actually uses a limited sports cards database for identification. You can try to play with both of them and choose the solution that works for you. If you have your own database of sports cards we can build a similar system just on your data.

You can read more about this solution in the article When OCR Meets ChatGPT AI in One API.

Read Graded Slab Labels With AI

Sports card grading is gaining popularity not only in the USA but also in Europe and Asia, as collectors recognize the value of their cards. Having rare foiled cards evaluated by esteemed companies like PSA or Beckett may be a good investment.

Online trading has become a prevalent trend, with eBay leading the pack as the go-to marketplace for collectibles. However, searching for the best deal among thousands of results for a specific query, like a “Michael Jordan Graded Card” can be incredibly time-consuming and challenging.

Our endpoint slab_id reads the graded slabs and helps to automate the identification of promising cards:

https://api.ximilar.com/collectibles/v2/slab_id

It will read the slab and return attributes such as grade, name, grade company and certification number. You can use it to automatically find and filter items with certain grades or conditions (8/9/10, near mint, gem mint, and so on).

Pre-Grading of Sports Cards With AI

We also provide an alternative to the slab reader in case the uploaded card doesn’t have a grade yet. It is an AI-powered grader for websites that evaluate & sell sports cards. The system can grade whole cards as well as individual parts like corners, edges, or centering. It is accessible via endpoint grade (precise) or condition (lightweight and fast):

https://api.ximilar.com/card-grader/v2/grade
https://api.ximilar.com/card-grader/v2/condition

Because identifying grades from a single picture cannot fully replace a professional grader, this endpoint serves mainly as a pre-grading solution. As I write this article, it is currently in beta testing. Nonetheless, it has already proven effective in specific scenarios, particularly with high-resolution pictures of sports cards without sleeves or slabs. This feature was highly requested by many of our customers. So we made it accessible to both Business and Professional plan users.

Solving this challenge is no simple task, and it is a long-term project for us. We are working hard both on gathering training data and improving the model architecture. It serves also as a research project, as we encounter a lot of new and not quite standard things and problems. I will write more about this service, technology, and development in a future blog post. So stay tuned!

Automation in Collectibles Industry Makes Sense

Here are a few reasons why I think the trading card industry is growing rapidly, and will use AI-powered automation more in the future:

• According to Business Research Insights, the global collectible card game market was valued at 13 billion USD in 2021. And it is projected to grow by 16% annually.

• In 2022 alone, 10 million sports cards were graded, indicating significant demand for grading services.

• The TCG potential has caught the attention of major corporations including Disney, evident from their release of the Lorcana TCG in 2023.

• Companies like Nintendo earned nearly 43 million USD from card games playing last year.

• Magic The Gathering remains Hasbro’s most profitable business venture.

Get a Solution Tailored to Your Business

All the services mentioned in this article are easy to combine with each other and with the rest of our solutions. One of the most popular solutions in the field of collectibles is a visual search and similar item recommendation. If you are aiming to have your own visual search engine, I suggest reading Pokémon TCG Search Engine: Use AI to Catch Them All and then contacting us.

The collector community’s feedback and thoughts serve as our primary motivation to develop tailor-made solutions for this amazing field. Contact us anytime and we can discuss your goals.

The post Build Your Own Trading Card Game Identifier With Our API appeared first on Ximilar: Visual AI for Business.

That is why we in Ximilar have recently developed an OCR system, integrated it with ChatGPT and made it available via API. It is one of the first publicly available services combining OCR software and the GPT model, supporting several alphabets and languages. In this article, I will provide an overview of what OCR and ChatGPT are, how they work, and – more importantly – how anyone can benefit from their combination.

What is Optical Character Recognition (OCR)?

OCR (Optical Character Recognition) is a technology that can quickly scan documents or images and extract text data from them. OCR engines are powered by artificial intelligence & machine learning. They use object detection, pattern recognition and feature extraction.

An OCR software can actually read not only printed but also handwritten text in an image or a document and provide you with extracted text information in a file format of your choosing.

How Optical Character Recognition Works?

When an OCR engine is provided with an image, it first detects the position of the text. Then, it uses AI model for reading individual characters to find out what the text in the scanned document says (text recognition).

This way, OCR tools can provide accurate information from virtually any kind of image file or document type. To name a few examples: PDF files containing camera images, scanned documents (e.g., legal documents), old printed documents such as historical newspapers, or even license plates.

Most OCR tools are optimized for specific languages and alphabets. We can tune these tools in many ways. For example, to automate the reading of invoices, receipts, or contracts. They can also specialize in handwritten or printed paper documents.

The basic outputs from OCR tools are usually the extracted texts and their locations in the image. The data extracted with these tools can then serve various purposes, depending on your needs. From uploading the extracted text to simple Word documents to turning the recognized text to speech format for visually impaired users.

OCR programs can also do a layout analysis for transforming text into a table. Or they can integrate natural language processing (NLP) for further text analysis and extraction of named entities (NER). For example, identifying numbers, famous people or locations in the text, like ‘Albert Einstein’ or ‘Eiffel Tower’.

Technologies Related to OCR

You can also meet the term optical word recognition (OWR). This technology is not as widely used as the optical character recognition software. It involves the recognition and extraction of individual words or groups of words from an image.

There is also optical mark recognition (OMR). This technology can detect and interpret marks made on paper or other media. It can work together with OCR technology, for instance, to process and grade tests or surveys.

And last but not least, there is intelligent character recognition (ICR). It is a specific OCR optimised for the extraction of handwritten text from an image. All these advanced methods share some underlying principles.

What are GPT and ChatGPT?

Generative pre-trained transformer (GPT), is an AI text model that is able to generate textual outputs based on input (prompt). GPT models are large language models (LLMs) powered by deep learning and relying on neural networks. They are incredibly powerful tools and can do content creation (e.g., writing paragraphs of blog posts), proofreading and error fixing, explaining concepts & ideas, and much more.

The Impact of ChatGPT

ChatGPT introduced by OpenAI and Microsoft is an extension of the GPT model, which is further optimized for conversations. It has had a great impact on how we search, work with and process data.

GPT models are trained on huge amounts of textual data. So they have better knowledge than an average human being about many topics. In my case, ChatGPT has definitely better English writing & grammar skills than me. Here’s an example of ChatGPT explaining quantum computing:

It is no overstatement to say that the introduction of ChatGPT revolutionized data processing, analysis, search, and retrieval.

How Can OCR & GPT Be Combined For Smart Text Extraction

The combination of OCR with GPT models enables us to use this technology to its full potential. GPT can understand, analyze and edit textual inputs. That is why it is ideal for post-processing of the raw text data extracted from images with OCR technology. You can give the text to the GPT and ask simple questions such as “What are the items on the invoice and what is the invoice price?” and get an answer with the exact structure you need.

This was a very hard problem just a year ago, and a lot of companies were trying to build intelligent document-reading systems, investing millions of dollars in them. The large language models are really game changers and major time savers. It is great that they can be combined with other tools such as OCR and integrated into visual AI systems.

It can help us with many things, including extraction of essential information from images and putting them into text documents or JSON. And in the future, it can revolutionize search engines, and streamline automated text translation or entire workflows of document processing and archiving.

Examples of OCR Software & ChatGPT Working Together

So, now that we can combine computer vision and advanced natural language processing, let’s take a look at how we can use this technology to our advantage.

Reading, Processing and Mining Invoices From PDFs

One of the typical examples of OCR software is reading the data from invoices, receipts, or contracts from image-only PDFs (or other documents). Imagine a part of invoices and receipts your accounting department accepts are physical printed documents. You could scan the document, and instead of opening it in Adobe Acrobat and doing manual data entry (which is still a standard procedure in many accounting departments today), you would let the automated OCR system handle the rest.

Scanned documents can be automatically sent to the API from both computers and mobile phones. The visual AI needs only a few hundred milliseconds to process an image. Then you will get textual data with the desired structure in JSON or another format. You can easily integrate such technology into accounting systems and internal infrastructures to streamline invoice processing, payments or SKU numbers monitoring.

Trading Card Identifying & Reading Powered by AI

In recent years, the collector community for trading cards has grown significantly. This has been accompanied by the emergence of specialized collector websites, comparison platforms, and community forums. And with the increasing number of both cards and their collectors, there has been a parallel demand for automating the recognition and cataloguing collectibles from images.

Ximilar has been developing AI-powered solutions for some of the biggest collector websites on the market. And adding an OCR system was an ideal solution for data extraction from both cards and their graded slabs.

Automatic Recognition of Collectibles

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

Read more

We developed an OCR system that extracts all text characters from both the card and its slab in the image. Then GPT processes these texts and provides structured information. For instance, the name of the player, the card, its grade and name of grading company, or labels from PSA.

Needless to say, we are pretty big fans of collectible cards ourselves. So we’ve been enjoying working on AI not only for sports cards but also for trading card games. We recently developed several solutions tuned specifically for the most popular trading card games such as Pokémon, Magic the Gathering or YuGiOh! and have been adding new features and games constantly. Do you like the idea of trading card recognition automation? See how it works in our public demo.

How Can I Use the OCR & GPT API On My Images or PDFs?

Our OCR software is publicly available via an online REST API. This is how you can use it:

1. Log into Ximilar App

   • Get your free API TOKEN to connect to API – Once you sign up to Ximilar App, you will get a free API token, which allows your authentication. The API documentation is here to help you with the basic setup. You can connect it with any programming language and any platform like iOS or Android. We provide a simple Python SDK for calling the API.

   • You can also try the service directly in the App under Computer Vision Platform.

2. For simple text extraction from your image, call the endpoint read.

   https://api.ximilar.com/ocr/v2/read

3. For text extraction from an image and its post-processing with GPT, use the endpoint read_gpt. To get the results in a deserved structure, you will need to specify the prompt query along with your input images in the API request, and the system will return the results immediately.

   https://api.ximilar.com/ocr/v2/read_gpt

4. The output is JSON with an ‘_ocr’ field. This dictionary contains texts that represent a list of polygons that encapsulate detected words and sentences in images. The full_text field contains all strings concatenated together. The API is returning also the language name (“lang_name”) and language code (“lang”; ISO 639-1). Here is an example:

   {
     "_url": "__URL_PATH_TO_IMAGE__
     "_ocr": {
        "texts": [
          {
             "polygon": [[53.0,76.0],[116.0,76.0],[116.0,94.0],[53.0,94.0]],
             "text": "MICKEY MANTLE",
             "prob": 0.9978849291801453
          },
          ...
        ],
        "full_text": "MICKEY MANTLE 1st Base Yankees",
        "lang_name": "english",
        "lang_code": "en
     }
   }

   Our OCR engine supports several alphabets (Latin, Chinese, Korean, Japanese and Cyrillic) and languages (English, German, Chinese, …).

Integrate the Combination of OCR and ChatGPT In Your System

All our solutions, including the combination of OCR & GPT, are available via API. Therefore, they can be easily integrated into your system, website, app, or infrastructure.

Here are some examples of up-to-date solutions that can easily be built on our platform and automate your workflows:

• Detection, recognition & text extraction system – You can let the users of your website or app upload images of collectibles and get relevant information about them immediately. Once they take an image of the item, our system detects its position (and can mark it with a bounding box). Then, it recognizes their features (e.g., name of the card, collectible coin or comic book), extracts texts with OCR and you will get text data for your website (e.g., in a table format).

• Card grade reading system – If your users upload images of graded cards or other collectibles, our system can detect everything including the grades and labels on the slabs in a matter of milliseconds.

• Comic book recognition & search engine – You can extract all texts from each image of a comic book and automatically match it to your database for cataloguing.

• Giving your collection or database of collectibles order – Imagine you have a website featuring a rich collection of collectible items, getting images from various sources and comparing their prices. The metadata can be quite inconsistent amongst source websites, or be absent in the case of user-generated content. AI can recognize, match, find and extract information from images based purely on computer vision and independent of any kind of metadata.

Let’s Build Your Solution

If you would like to learn more about how you can automate the workflows in your company, I recommend browsing our page All Solutions, where we briefly explained each solution. You can also check out pages such as Visual AI for Collectibles, or contact us right away to discuss your unique use case. If you’d like to learn more about how we work on customer projects step by step, go to How it Works.

Ximilar’s computer vision platform enables you to develop AI-powered systems for image recognition, visual quality control, and more without knowledge of coding or machine learning. You can combine them as you wish and upgrade any of them anytime.

Don’t forget to visit the free public demo to see how the basic services work. Your custom solution can be assembled from many individual services. This modular structure enables us to upgrade or change any piece anytime, while you save your money and time.

The post When OCR Meets ChatGPT AI in One API appeared first on Ximilar: Visual AI for Business.

All Important Things at Hand

Ximilar provides a platform for visual AI, where anyone can create, train and deploy custom-made visual AI solutions based on the techniques of machine learning and computer vision. The platform is accessible via API and a web-based App, where users from all around the world work with both ready-to-use and custom solutions. They implement them into their own apps, quality control or monitoring systems in factories, healthcare tools and so on.

We created the new interface to adapt to the ever-increasing number of services we provide. It now makes better use of both the dashboard and sidebar, showcases useful articles and guides, and provides more support. So, let’s take a look at the major new features!

Service Categories & News

We grouped our services based on how they work with data and the degree of possible customization. After you log into the application, you will see the cards of four service groups with short descriptions on the dashboard. Below them, you can see the newest articles from our Blog, where we publish a lot of useful tips on how to create and implement custom visual AI solutions.

The service groups are following:

1. Ready-to-use Image Recognition includes all the services, that you can use straight away without the need for additional training, custom tags and labels. In principle, these services analyze your data (i.e., your image collection) and provide you with information based on image recognition, object detection, analysis of colors & styles etc. Here you will find Fashion Tagging, Home Decor Tagging, Photo Tagging and Dominant Colors.
2. Custom Image Recognition allows you to train custom Categorization & Tagging and Object Detection models. Flows, that enable you to combine the models, are also under this category. To prepare the training data for object detection seamlessly and fast, you can use our own tool Annotate.
3. Visual Search encompasses all services able to identify, analyze and compare visually similar content. Image Similarity can find, compare and recommend visually similar images or products. You can also use Image Matching to identify duplicates or near-duplicates in your collection, or create a fully custom visual search. Fashion Search is a complex service based on visual search and fashion tagging for apparel image collections.
4. Image Tools are online tools based on computer vision and machine learning that will when provided with an image, modify it. You can then either use the result or implement these image tools in your Flows. Here you will find Remove Background and Image Upscaler.

Do you want to learn more about AI and machine learning? Check the list of The Best Resources on Artificial Intelligence and Machine Learning.

Discover Services

Within the service groups, you can now browse all our services, including the ones that are not in your pricing scheme. Every service dashboard features a service overview and links to documentation, useful guides, case studies & video tutorials.

Do you want to know what you pay for when using our App? Check our article on API credit packs or the documentation.

Guides & Help at Hand

The sidebar underwent some major changes. It now displays all service groups and services. At the bottom, you will find the Guides & Help section with all necessary links to the beginner App Overview tutorial, Guides, Documentation & Contacts in case you need help.

How to make the most of a computer vision solution? Our guides are packed with useful tips & tricks, as well as first-hand experience of our machine learning specialists.

Customize the Sidebar With Favorites

Since each use case is highly specific, our users usually use a small group of services or only one service at a time. That is why you can now pin your most-used services as Favorites.

When you first log into the new front end, all of your previously used services will be marked as favourites. You can then choose which of them will stay on top.

What’s next?

This front-end update is just a first step out of many we’ve been working on. We focus on adding some major features to the platform, such as explainability, as well as custom image regression models. The Ximilar platform provides one of the most advanced Visual AI tools with API on the market, and you can test them for free. Nevertheless, the key to the improvement of our services and App are your opinions and user experience. Let us know what you think!

The post Ximilar Introduces a Brand New App 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.

No more testing using Postman, Insomnia or Python script. We want our vision services to be easy to use. With the new Ximilar Preview feature in Ximilar App, you can test your custom AI models on different devices in the browser. Our no-code AI cloud platform can simply share and present your model to colleagues and coworkers.

We made it easy to test and share API. Just click on the Classify button (left menu in Categorization & Tagging service) after your task is trained and upload an image. You can access Preview on both mobile and desktop devices. You can inspect the behaviour of our REST API, copy the curl request or see the JSON response from the endpoint.

Visualizing results from AI services online

The previewing is available for multiple of our AI services as Custom Image Recognition, Image Tools, Ready-To-Use Image Recognition and more. Object Detection Preview is able to draw bounding boxes/detected objects on the image, so you can immediately visualize the results of your trained detection model. Fashion Tagging preview shows you all objects, features, and tags analysed on the image with our deep image tagging technology. Image upscaler preview can compare the details of the upscaled image with the original one.

How do you like the Preview feature? Would you like to customize your preview interface to serve your customers? Let us know.

The post Introducing Preview  – The Easiest Way to Test and Share Your AI Task appeared first on Ximilar: Visual AI for Business.