image_recognition_brail

Image Recognition Revolutionizes the Online Experience for the Visually Impaired

People take seeing and technology for granted. For a specific group of internet users, the online experience is not so straightforward. The visually impaired need special assistance to experience the digital world. There are a few diverse low-vision aids but generally, they can be divided into two categories: translating visual information into alternative sensory information (sound or touch) and adapting visual transformation to make it more visible. However, the bigger problem remains how to help people who are blind. The emerging technology for assistance in this category uses image processing techniques to optimize the visual experience. Today we will be looking at how image recognition is revolutionizing the online experience for the visually impaired.

Blind Users Interacting with Visual Content

Let’s stop for a second to consider the whole online experience for the visually impaired. What happens when a regular person sees a webpage? He scans it, clicks links or fills in page information. For the visually impaired, the experience is different. They use a screen reader: a software that interprets a photo or image on the screen and reads it to the user. However, to narrate each page element in a fixed order including skipping is not easy. Sometimes there is a vast difference between the visual page elements (buttons, banners, etc.) and the alt-text read by the screen reader. SNS pages (social networking service) with unstructured visual elements and an abundance of links, with horizontally and vertically organized content make listening to the screen reader more confusing.

Interacting with Social Visual Content

SNSs make it easy to communicate through various types of visual content. To fully engage with images, visually impaired people need to overcome accessibility challenges associated with the visual content through workarounds or with outside help.

Advancements in artificial intelligence are allowing blind people to identify and understand the visual content. Some of them include image recognition, tactile graphics, and crowd-powered systems.

Facebook has already algorithmically generated useful and accurate descriptions of photos on a larger scale without latency in the user experience. They provide visuals a description as image alt-text, an HTML attribute designed for content managers to provide the text alternative for images.

Web Accessibility  Today

We might think that web accessibility is a universal thing, but web designers do not always have the resources to devote to accessibility or do not see the value in making sites accessible. A 2-dimensional web page translated into a 1-dimensional speech stream is not easy to decipher. One of the most annoying things is that the majority of websites have insufficient text labeling of graphic content, concurrent events, dynamic elements, or infinitely scrolling pages (i.e. a stream of feeds). Thus, many websites continue to be inaccessible through screen readers. Even the ones that are intended for universal access: library websites, university websites, and SNSs.

The World Wide Web Consortium (W3C), an international community where Member organizations and the public work together to develop Web standards, created accessibility standards.  Led by Web inventor Tim Berners-Lee and CEO Jeffrey Jaffe, W3C's mission is to lead the Web to its full potential.

Solutions Helping Visually Impaired Users

Aipoly
There is a new iPhone app which uses machine learning to identify objects for visually impaired people without an Internet connection. The free image-recognition app is called Aipoly and is making it easier for people to recognize their surroundings. How does it work? You simply point the phone’s rear camera at whatever you want to identify and it speaks what it sees. The app can identify one object after another as the user moves the phone around and it doesn’t require picture taking.The app can be helpful not only to people with impaired vision but also to the ones trying to learn a new language.

Aipoly cofounder Simon Edwardsson says it recognizes images by using deep learning, which is a machine-learning technique inspired by studies of the brain. This is the same technology used by Facebook for recognizing faces and Google for searching images. The app breaks down the image into different characteristics like lines, patterns, curves, etc. and uses them to determine the likelihood of that image to be a specific object. The app works fine for objects around the office. So far it can recognize around 1,000 objects, which is more than enough.

Banknote-reader (b-reader)
The banknote reader is a device that helps the visually impaired to recognize money. The banknote goes into the b-note holder for scanning and recognition (orientation doesn’t really matter), it gets photographed and sent securely to the cloud. There an Imagga-trained custom classifier recognizes the nominal value and returns the information to the b-note device. Then it plays a pre-recorded .mp3 file with the value if it is recognized. The project is part of TOM (Tikkun Olam Makers), a global movement of communities connecting makers, designers, engineers and developers with people with disabilities to develop technological solutions for everyday challenges. On the web platform, you can find full specs of the b-note prototype, including building instructions and camera code used for calling Images API, so that you can make a device like it for around 100 Euro or 115 USD.

LookTel
This is a combination of a Smartphone and advanced “artificial vision” software to create a helpful electronic assistant for anyone who is visually impaired or blind. It can be used to automatically scan and identify objects like money, packaged goods, DVDs, CDs, medication bottles, and even landmarks. All it takes is to point the device video camera at the object and the device pronounces the name quickly and clearly. It can be taught to identify all the objects and landmarks around you. With a little extra help, the LookTel can be a helpful assistant. It also incorporates a text reader which allows users to get access to print media.

Seeing AI
This is a smartphone app that uses computer vision to describe the world and is created by Microsoft. Once the app is downloaded, the user can point the camera at a person and it will announce who the person is and how they are feeling. The app also works with products. It is done by artificial intelligence running locally on the phone. So far the app is available for free in the US for iOS. It is unclear when the rest of the world and Android users will be able to download it.

The app works well for recognizing familiar people and household products (scanning barcodes). It can also read and scan documents and recognize US currency. This is not a small feat because the dollar bills are basically the same size and color, regardless of their value, so spotting the difference is sometimes difficult for the visually impaired. The app is using neural networks to identify objects, which is the same technology used for self-driving cars, drones, and others. The most basic functions take place on the phone itself, however most features require a connection.

Next  Challenges for Full Adoption

Facebook users upload more than 350 million photos a day. Websites are relying mostly on images and less on the text. Sharing visuals has become a major part of the online experience. So using screen readers and screen magnifiers on mobile and desktop platforms help the visually impaired. However, more efforts need to be put to make the web more accessible through design guidelines, designer awareness, and evaluation techniques.

The most difficult challenge ahead is the evaluation of the effectiveness of image processing. It needs to be held ultimately to the same standards as other clinical research in low vision. Image processing algorithms need to be tailored specifically to disease entities and be available on a variety of displays, including tablets. This field of research has the potential to deliver great benefits to a large number of people in short period of time.


The Top 5 Uses of Image Recognition

Not long ago, artificial intelligence sounded like a science fiction prophecy of a tech future. Today machine learning has become a driving force behind technological advancements used by people on a daily basis. Image recognition is one of the most accessible applications of it, and it’s fueling a visual revolution online.

Мachine learning embedded in consumer websites and applications is changing the way visual data is organized and processed. Visual recognition offers exciting opportunities similar to the ones in science fiction movies that made our imagination run wild.

Image recognition has grown so effective because it uses deep learning. This is a machine learning method designed to resemble the way a human brain functions. That’s how computers are taught to recognize visual elements within an image. By noticing emerging patterns and relying on large databases, machines can make sense of images and formulate relevant categories and tags.

From image organization and classification to face detection, here are five of the top applications of image recognition in the current consumer landscape.  

#1. Automated Image Organization - from Cloud Apps to Telecoms

image organization

One of the most popular applications of image recognition that we encounter daily is personal photo organization. Who wouldn’t like to better handle a large library of photo memories according to visual topics, from specific objects to broad landscapes?

Image recognition is empowering the user experience of photo organization apps. Besides offering a photo storage, apps want to go a step further by giving people better search and discovery functions. They can do that with the automated image organization capabilities provided by machine learning. The image recognition API integrated in the apps categorizes images on the basis of identified patterns and groups them thematically.

Take Eden Photos, a Mac app for photo organization, as an example. It uses Imagga’s image recognition to offer its users image tags, automatic keywording of photos, and auto-categorization on the basis of visual topics. Users can sync their photos’ metadata on all devices and get keyword search in the native Photos app on their iPhones too.

Telecoms are another set of companies that integrate image recognition to improve their users’ experience. They add value to their services by offering image organization and classification for photo libraries, which helps them attract and retain their customers. On the customer side, user experience is improved by allowing people to categorize and order their photo memories.

An illustration of this application is Imagga’s solution for Swisscom. The Swiss telecom needed an efficient and secure way to organize users’ photos for its myCloud online service. With Imagga’s image recognition API installed on premise, Swisscom now offers its customers a safe feature that organizes and categorizes their visual data.   

#2. Stock Photography and Video Websites

clients include stock photography

A powerful commercial use of image recognition can be seen in the field of stock photography and video. Stock websites provide platforms where photographers and videomakers can sell their content. Contributors need a way to tag large amounts of visual material, which is time-consuming and tedious. In the same time, without proper keyword attribution, their content cannot be indexed - and thus cannot be discovered by buyers.  

Image recognition is thus crucial for stock websites. It’s fueling billions of searches daily in stock websites. It provides the tools to make visual content discoverable by users via search. In the same time, image recognition is a huge relief for stock contributors. They get automatic keyword suggestions, which save them a ton of time and efforts. Image recognition can also give them creative ideas how to tag their content more successfully and comprehensively.

Keywording software tools like Qhero have integrated with Imagga’s image recognition AI to help stock contributors describe and tag their content with ease. Such tools analyze visual assets and propose relevant keywords. This reduces the time needed by photographers for processing of visual material. It makes manual keywording a thing of the past by suggesting the most appropriate words that describe an image.

#3. Image Classification for Websites with Large Visual Databases

A range of different businesses possess huge databases with visuals which is difficult to manage and make use of. Since they may not have an effective method to make sense of all the visual data, it might end up uncategorized and useless.

If a visual database does not contain metadata about the images, categorizing it is a huge hassle. Classification of images through machine learning is a key solution for this. With image recognition, companies can easily organize and categorize their database because it allows for automatic classification of images in large quantities. This helps them monetize their visual content without investing countless hours for manual sorting and tagging.

The best part about automated image classification is that it allows for custom training on top of the general image recognition API. This means that businesses can provide custom categories, which the AI is trained to recognize and use. Our case study on Tavisca is a good example of using custom classifiers in practice and automating the process of hotel photos categorization.

#4. Image and Face Recognition on Social Networks

image recognition

Visual recognition on social media is already a fact. Facebook released its facial recognition app Moments, and has been using facial recognition for tagging people on users’ photos for a while.

While face recognition remains a sensitive ground, Facebook hasn’t shied away from integrating it in users’ experience on the social media. Whenever users upload a photo, Facebook is able to recognize objects and scenes in it before people enter a description. The computer vision can distinguish objects, facial expressions, food, natural landscapes and sports, among others. Besides tagging of people on photos, image recognition is used to translate visual content for blind users and to identify inappropriate or offensive images.   

Image recognition is applied in other ways on social networks too. For example, the SmartHash iOs app employs Imagga’s API to offer its users an easy tool for automatically creating hashtags for their photos. This allows people to successfully share their images online without the need to research and brainstorm hashtags.

Photo recognition has also been embraced by other image-centric services online. Google Photos and Apple’s Photos app cluster photos on the basis of events and places, plus offer face detection. The application of image recognition significantly enhances users’ experience. It helps them organize their photos in meaningful series. They can easily exchange, say, travel photos with friends who were a part of the same trip.

#5. Interactive Marketing and Creative Campaigns

The applications of image recognition are not limited to consumer services only. Advertising and marketing agencies are already exploring its potential for creative and interactive campaigns. It opens new opportunities for learning more about target audiences and serving them with impressive branded content.

Social intelligence today is largely based on social listening. It involves following conversations on social media to learn more about prospects. But today, this knowledge can be gathered from visuals shared online with much higher efficiency. In a sea of abundant and often irrelevant visual content, extracting useful information is possible only through machine learning - or ‘visual listening.’ For example, image recognition can identify visual brand mentions and expression of emotion towards a brand, as well as logo and other brand data that would be otherwise undiscoverable. On the basis of collected information from analyzing images, marketers can better target their campaigns by using customization and personalization.

Besides valuable information about potential customers, image recognition can be used for crafting creative content that engages people and helps build their relationships with brands. To illustrate this: Imagga’s image recognition API was used in a KIA marketing project to create an interactive campaign. By profiling of participants’ image content online, each person is assigned to a different lifestyle group. Then they are matched to the right car that best fits their style among the 36 different car styles offered by KIA.

Celebrating the Power of Image Recognition

Image recognition holds potential for a wide array of uses and industries, so these five examples are certainly not all-encompassing. They do illustrate, though, the diversity of applications that machine learning can offer to businesses that work with large libraries of visual content.

What is your business experience with image recognition? 

free image recognition with imagga


Imagga Wins Porsche Hackathon

Hackathons are part of Imagga’s DNA - we love to hack and we definitely like to win. Porsche InnovationEngine hackathon took place in Salzburg, Austria on 8-10 June 2016. 12 teams all across Europe participated. We are happy to announce we won 1st prize but here’s a short report about this great event.

There were three tracks for the teams to complete - car recognition, financial optimization, the best car for me. It’s quite obvious we’ve decided to participate in the car recognition challenge.

Every great hackathon should start with nice dinner, and that’s what happened Friday night. As you can imagine we’ve been busy drafting the hack idea, meeting mentors and doing the actual hack. Literary we used the time and available napkins (great startup weapon to remember awesome ideas) to craft our winning strategy.

No surprise the next day we’ve digged straight into building our brilliant idea. Some mentors interrupted the process, but their insight on the car market was quite valuable. We’ve worked hard till midnight as we wanted to impress the jury with fully functional app including custom classification that was trained overnight.

Georgi presents at Porsche hackathon

During the final day of the hackathon we presented in front of 40 managers and 3 C-level executives (incl. the CEO) of Porsche Holding Group. Our demo went really smooth and all were impressed with the technology and that we were actually able to put together fully functional demo in such a short time.

Getting the first prize was such an honor and also an opportunity to work in that space - car discovery & search. Not to forget one of the perks winning Porsche hackathon - Audi Driving Experience! Looking forward to it!


Imagga @ Food Hacks Berlin

We are super thrilled to be part of Food Hacks Berlin, organized by HackerStolz. The idea of the hackathon is to find digital ideas that can revolutionize the food industry. Food delivery process has seen lots of innovation in recent years, but it’s obvious there’s so much that can be done: better services related to what we consume daily, smart apps that automate the burden of manual calories intake and many more.

Over 100 participants from 20 countries hacked in Rainmaking Loft, one of the well known startup destinations in Berlin. It’s inspiring to see so many motivated hackers with various experience in so many industries. One of the reasons we love hacker events in Berlin is the amazing mix of talent and the diversity of the participants. There was a group of bright Ukrainians that travel by bus over 12 hours, people from Poland, Holland, UK, Switzerland to name a few.Imagga Girls

Imagga was an API partner at the event. We’ve trained two special categorizers to help developers get the best out of our image recognition technology and to make sure they build amazing apps - meal classifier that can recognize over 300 cooked meals and food & veggies classifier.

Chris presented Imagga API at a dedicated workshop, talking about how you can use Imagga API to recgnize pictures of meals, fruites and veggies.

Amazing apps have been build during the weekend - from smart fridge that can find out what food is aging and needs to be thrown away and reordered to some quite creative ways to use food:

Neighborhood Cuisine - A mobile app that lets you get together with your neighbors to cook tasty recipes from your leftovers.

HelloFridge - the easiest way to save your ingredients from going bad by combining them to fit delicious recipes.

iTrash - the most intelligent trash can in the world

Surprise Meal - Provides surprise ideas for recipes.

Bulker - Early-morning bakery delivery that loves you

Super Quest - Food AR app for basic food education of children

Mint - A unique way to discover a new culture through music, art and food.

Vollkorntoast - New Shopping Experience

rcply - Search for recipes based on ingredients you already have at home

lekkerlekker - Your one stop shop for finding the best recipes and directly buy alls groceries you need.

VR-ify - Efficient food testing and prototyping process with VR and brain activity scanner

TraceYourFood - See the journey of the food you consume!

KeineWaste - KeineWaste connects food businesses and volunteers in real-time, converting food waste into food donations.

WTF: What the FOOD - So you'll never run out of müsli again.

Food-Sherlock

Our favorite hack is Food Sherlok, developed by Team Baker Street ;-) Food Sherlok lets you take a photo of any ingredient and gives your nutrition details, recipe suggestions and the possibility to buy it online. The mobile app utilizes Imagga API for the image recognition part, Spoonacular API for the nutrition details and HellowFresh API for the recipe suggestions and possible food delivery.

Here you can find the code of the hack.

Team Baker Street

Imagga prize - GoPro camera, t-shirts and free API access went to Team Baker Street for their incredible work and valuable feedback.

“Getting an idea took some time, so the first hours we decided on an idea, but it took another hour until it was clear for me what I had to do and how it should look like. Uploading the image and resizing it on the frontend was also harder than I thought, just because some of the APIs expect form data for images."

You can’t do much for the limited time of the hackathon, but the team is already making some bold plans for Food Sherlock. They think it will be quite useful if they can generate location based sate for retailers, work on improving the image recognition service with data specific for different geographic locations, experiment with new ways to visualize the results (may be adding something like search heat map overlay) and offer text to speech recognition to make sure refugees can also use the app.


Imagga Featured Hack: Hipster Bar

Hipster bar is where only hipsters are allowed! How do you reinforce that? With a physical doorman who’s job is to ruthlessly send back guys without beards, or, in the case of the Max Dovey’s project - using Imagga’s image recognition technology. The hipster bar was open to the public for the duration of WdW Festival 2015.

Let’s get into the details of this quite unique usage of Imagga’s powerful image recognition technology. To enter the bar, you need to stand in front of camera that snaps a photo of you and then sends it to Imagga servers. Then the tech analyses your look and as result returns how certain the system is you are a hipster.
If you are found over 90% hipster, the door of the bar will open and you can join great company of people that are hipster enough.

Hipster is quite loose term and usually is used to describe a subculture of people who attempt to keep up to date with the latest trend and remain 'hip'. These are men and women in their 20's and 30's that value progressive politics and independent thinking, and often have appetite for art and indie-rock & counterculture. Of course being hipster includes certain look - thick rimmed glasses, tight-fitting jeans, old-school sneakers,  side-swept bangs and beards (men only).

Max Dovey, an artist from Rotterdam, who initiated the project, sourced thousands of images of hipsters to be used by our team to build a special hipster deep learning mode.  The specific classifier was able to easily distinguish between snaps of hipsters and all the rest. Here’s how it actually worked:

https://vimeo.com/139604496

Have another crazy idea? Don’t hesitate to try it out - with our custom training only the sky is the limit... if you are hip enough ;)


Imagga among the 40 winners of UN-based World Summit Award 2015

Imagga @ World Summit Award

Imagga was selected as one of the winners of the World Summit Award, a global initiative in cooperation of the United Nations World Summit on the Information Society (WSIS) and UNESCO, UNIDO and UN GAID. WSA is the only ICT event worldwide, that reaches the mobile community in over 178 countries.

Imagga Image Recognition PaaS will be honored to receive the Award in e-Media & Journalism category in front of UN representatives, ICT ministries and the private sector at the World Summit Global Congress in Shenzhen, China, in February 2016.

“It’s extremely exciting to see two Bulgarian companies - Imagga (e-Media & Journalism category) and Bee Smart (e-Health and Environment category) as finalists of the World Summit Award 2015. Having two winning teams happens for the first time since Bulgaria participates in the prestigious award”, states Pavel Vurbanov, European Software Institute - Center Eastern Europe.

The 40 winners representing 24 countries were carefully selected from 386 nominations. The goal of the award is to showcase the world’s best practices in digital innovation - from Japan to Brazil and from Norway to Australia.

The WSA winners were selected by a jury of international ICT experts in two democratic rounds. Each UN Member State is eligible to nominate one product per category for the World Summit Award. This way any nomination results from a national pre-selection prior to the international WSA Jury.


Imagga Gets Big Players Award by HM King of Spain at South Summit 2015

Georgi Kadrev getting Tech for Big Players Award from HM Felipe VI, King of Spain
Georgi Kadrev getting Tech for Big Players Award from HM Felipe VI, King of Spain

Imagga was honored to get Tech for Big Players Award at South Summit 2015, that took place in Madrid, Spain. At the closing day HM Felipe VI, King of Spain himself awarded the finalists of the startup competition at the event and spent some time to talk with the winning companies. Out of the four startups being recognized at the event, Imagga is the only company that doesn't come from Spanish speaking country.

South Summit is the leading entrepreneurship event for the Spanish speaking world. Over 12,500 participants, 100 startups, 650  investors, 325 journalists и 275 speakers took place in the forum, held in the historic Las Ventas building - build in the beginning of 20 century and home of the famous bull fights. Special guest of the event was Steve Wozniak, co-founder of Apple together with Steve Jobs.

Imagga was one of the 100 carefully selected startups from 15 countries (3 companies in total from Bulgaria) and we competed in Tech for Big Players category (the other categories were; digital solutions for the mass market, healthcare and biotech, industrial revolution)

“Being able to stand and pitch on the very same arena famous for bullfighting actually raised the adrenalin and made the experience quite unique. It was great opportunity to meet fellow entrepreneurs, talk image recognition and AI, currently quite hot trends, and talk to investors and media”, shares Georgi Kadrev, co-founder and CEO of Imagga.

 

https://youtu.be/6UQirQBi2Jc?t=52m20s

Imagga's automated tagging is getting traction and we see great use cases and lots of business opportunities. South Summit opened up a new world of possibilities as we've never been that much focused on the Spanish speaking world, but we see it's big and interesting.

"I took some time to contemplate why I like this tree as a prize that much - it's not just because it was given by His Majesty the King of Spain and is the symbol of Madrid, but also as it is a very beautiful metaphor - it has been planted some time ago, and it took a while before it shows up above the ground. Now it's grown but it's still small and it still needs care until it grows and give some sweet fruits. I believe it's the same with our Imagga.", shares Georgi Kadrev

Being part of SouthSummit was fun and very rewarding. Thanks for inspiring us and at the same time acknowledging our efforts to democratize image recognition and make it useful for great variety of business use cases.


Imagga at Hack The Visual

Hack the Visual event in London. Shot for Canon Europe Ltd.
Hack the Visual event in London. Shot for Canon Europe Ltd.

During the last couple years we’ve been taking part in numerous hackathons and events. Hack The Visual was perfect fit for what we do at Imagga. The goal of the event is to connect different types of visual data to each other and create new and interesting prospective. All data is welcomed - pictures, music, video, geo-data, even open data, you name it. In just 48 hours over 100 participants were hacking on projects mashing existing APIs and data sets to find a solution for a real life visual problem.

The main challenge was to bring together photos, videos and other kind of imagery with hardware, interfaces, platforms, apps & services in order to unlock the next step in visual culture.

Tree main tracks have been set based on research by Imaging Mind (organizer of the event) regarding the future of imaging:

  • meshed capture - connecting multiple camera sources to generate new experiences. Winner: Camera Crowd - combining multiple photos and their location data with a photo of the area you are. A mesh of pictures from different sources blended into the space
  • new perspectives/interpretation of images - accessing various image data sets to extract value from them outside of the image itself. Winner: Hear The Picture - by linking each coloured pixel to its individual sound, a photo could be ‘heard’ through its own distinctive soundtrack
  • interactive visuals - reworking the static images into interactive new experience. Winner: Sharon - watch the same video source with multiple people, and allow synced manipulation of the video

Grand Prize went to Splatmap - web application that allows you to photograph buildings with your smartphone and plot the information into the application.

Hack the Visual event in London. Shot for Canon Europe Ltd.

The special Imagga API prize went to Remember - app that triggers your memories using your own photo collection. Re/Visit a place and Remember will remind you of pictures you or someone else snapped nearby. It can also search for relevant photos based on the topics in the photo (using Imagga’s image recognition tagging API), turning your photo library into a smart conversation starter wherever you might be.

Overall, great event! See you next time. And do not forget to give Imagga APIs a try!


Machine Learning Meetup in Sofia

ML Meetup Sofia

Three year ago when we publicly talked about machine learning, deep learning, convolutional neural networks and AI not many people were getting it. It was hard to explain what all this is about. Things have changed, and for good.

Last week we’ve invited a bunch of people to Machine Learning meetup. The first in Sofia. 60 people attended and it was awesome. It’s awesome to see so many people interested in AI and machine learning. And they were getting it. We are sure machine learning will be widely adopted in many tech verticals  in an year or so and are proud to be helping Bulgarian AI/ML community to exchange ideas and grow.

Judging by the number of people and cases that has been discussed, lots of startups are already exploring the power of machine learning in various industries - e-commerce, bitcoin landing, real estate, to mention few. It’s still the early days of ML community in Sofia, so we’ve started with some basics. Judging by the variety of the questions after our short intro presentation, next editions of Sofia Machine Learning Meetup will be quite geeky and interesting.


Imagga Partners with Aylien

aylien magga partnership

We are super excited to announce our partnership with AYLIEN - a natural language processing platform, that will make possible to add text analytics capabilities to our image recognition and analytics APIs. We believe this partnership will help users of both services better understand their multimedia content and do way more with it.

AYLIEN Text API is a package consisting of eight different Natural Language Processing, Information Retrieval and Machine Learning APIs that help developers extract meaning and insight from text documents. It can be applied in Ad-Targeting, Media Monitoring and Social Listening projects.

Imagga’s Image Recognition API utilizes machine learning, image recognition and deep learning algorithms to identify over 6,000 distinct objects and concepts and return relevant keywords that best describe what’s in the images.

Currently Imagga’s image analysis endpoint is being added to ALYIEN’s Natural Language Processing API, giving developers the ability to analyze text and images in one API.

test image tagging

Having access to two powerful technologies in a single API creates endless opportunities for businesses that need to deal with large volumes of user generated content. Users rarely input or share just text or images, so being able to analyze and understand both at once, gives amazing new opportunity for any business to distribute and monetize content.

Together with AYLIEN we’ve been testing how our technologies can compliment each other for some time and the results were very exciting. Text and images are different but complement well each other in many cases and applications.

You can try the new hybrid image and text analysis service here. There’s nice demo to play with before you are finally sold (you can see the results for some sample images, but also can upload your own)