Why Using Image Recognition Software Can Save Your Cloud Platform a Ton of Resources

In recent years, we have seen significant growth in artificial intelligence technology and its use in different industries such as automotive, healthcare, e-commerce, gaming, e.t.c. Image recognition, one of the flagship applications of AI, has had wide adoption across industries. It is estimated that the worldwide market for image recognition will grow to $29.98 billion by 2020.

A major factor in the growing demand for image recognition technology has been the increased use of the internet and the move of small and medium enterprises (SMEs) to the cloud. With this move, the businesses have benefited from some of the advantages a cloud platform offers such as widespread reach, scalability, flexible billing options, rapid deployment and constant availability. With the move to the cloud, businesses have found it necessary to adopt technology that helps them better navigate the smarter and more connected platform; and image recognition is one of those technologies.

Image recognition (sometimes called computer vision) is the ability of software to analyze an image or video, identifying its content e.g. people, objects, places and text. It is widely used in different industries e.g. in self-driving cars, facial and optical character recognition software, disease diagnosis, e.t.c. For businesses that operate in the cloud, image recognition can offer numerous benefits as outlined below.

Automating Tasks with Image Recognition Software Saves Time

Unlike other resources that you can create or acquire more of, time is a finite resource that most likely, to stay competitive, you can't afford to waste.

Without a doubt, computers are faster than humans at some particular tasks, and so for those tasks, it makes sense to automate the job using software, leaving your employees free to work on other urgent tasks. Image recognition software can be used to automate such tasks as categorizing and tagging media content, content moderation and editing images (e.g. cropping or background removal).

Use of Image Recognition Software can Help Keep your Team Lean and Thus Save Costs

Use of image recognition software can reduce or eliminate required labour. Without image recognition, you would have to put people on the job to do such tasks as tagging and categorizing your digital assets, moderating user-generated content, individually editing images, e.t.c. In some cases, such a feat might be annoying and frustrating at best, but in other cases, it might be outright impossible to do. Take, for instance, a firm that might be offering Digital Asset Management services. The firm might have several clients, each having millions of digital content that needs to be processed. It would be very difficult, if not impossible to run such a service on manual labour alone. To keep its client's happy, the business will have to keep its asset processing time to a minimal, which means it would have to keep a lot of people on board to do the work. With time, as its client list increases or as the content each client maintains increases, the business's labour costs will also be skyrocketing. Running such a business on manual labour alone isn't sustainable. By automating some tasks with image recognition software, you can maintain a lean and cost-effective team.

Image Recognition can Reduce Human Error

To err is human, to forgive divine so the saying goes; but when you are running a business that depends on the accuracy of its operations, you might not be so lax about errors that might occur.

Human labour is susceptible to making errors. When tasked with entering a large amount of data, it is probable that some data will be recorded incorrectly. Human labour is also prone to tiring. When one has to process thousands of images or videos, they might not be as keen on processing a few thousands. With exhaustion and waning focus, errors might creep in here and there.

For some use cases, image recognition has been shown to give better results than humans. In the medical field, for instance, there is a visual recognition software that has a higher success rate in diagnosing a particular type of cancer. In the still infant field of self-driving cars, it has been said that driverless cars are safer than human drivers.

Image recognition can help eliminate or at least reduce the inaccuracies of human intervention. This will, in turn, save the business resources that would have been lost due to the errors, whether in the form of revenue, labour or time.

Image Recognition can Help you Innovate According to Market Trends

One advantage of running an online business is that a lot of your customers are also online. In this connected ecosystem, it is easier to monitor the market by observing what people share online. By analyzing visual content that is shared online, you might be able to recognize a trend that you can piggyback on when it comes to product release. With image recognition, you can also gain some insights into your competitors by detecting their online visual presence. You can observe how the market engages with the competitor's visual content and determine if their reaction to it is positive or not. This can, in turn, inform your product design decisions.

Instead of using tedious questionnaires and discovery processes to find out what users want, you can use data to determine this. You can determine what users gravitate towards online by observing what they share and how they react to different content. An example of this in use is Netflix which uses data to determine what shows to create. This can save you the effort and cost of creating something that won't be profitable once it hits the market.

Image Recognition can Improve your Marketing Efforts

Other than using image recognition to predict products that will be popular amongst your target market, you can also use it to determine how best to market the products to consumers. Using image recognition, you can mine your target market's visual content and monitor market trends in real time. In this way, you can gain insights on how visual posts spread online, what type of visuals get the most attention, the type of people engaging most with your content, the individual influencers driving most of the traffic and the best platform to post your content on. This can, in turn, help you launch marketing campaigns that are most likely to succeed. Your marketers don't have to waste their budget guessing at what will work, they can use data to decide on the way forward.

How something is presented can have a huge impact on the level of engagement people will have with it. Netflix discovered from conducting consumer research, that the artwork on their website was not only the biggest influencer to a member's decision to watch content, but it also constituted over 82% of their focus while browsing. This is why they go through so much effort to determine the best artwork to display on their website, a feat that would be impossible without image recognition and machine learning. If you are running an online business, you should pay attention to how you present your product or service. In a world where consumers are spoilt for choice when searching for a product or service, you should ensure that your website communicates the value of what you are trying to sell in the best way possible.

Image Recognition can Help Online MarketPlaces Fight Counterfeit Goods

According to the Organization for Economic Co-operation and Development (OECD), counterfeit products may cost the global economy up to $250 billion a year. Businesses running online platforms that allow sellers to sell goods always run the risk of having some sellers selling counterfeit products. This can damage the marketplace's reputation when consumers get products that are subpar to their genuine counterparts.

To counter this, marketplace websites have started turning to image recognition technology to help identify legit and counterfeit products. Using software, the platforms put uploaded product images through some checks to ensure their authenticity.

In General, Image Recognition Makes for Better Apps

Overall, incorporating image recognition improves the user experience of cloud applications and makes their operation effective and efficient. Using better apps is good for any business's bottom line as they reduce the overall overhead costs.

In the presence of numerous competition, most companies compete primarily on the basis of customer experience. Poor user experience can lead to customer churn, and in an interconnected world, it is very easy for disgruntled customers to spread the word about the terrible service they had at your hands; so it is always in your best interest to employ any technology you can to produce the best possible product for your target market.

Do you use image recognition in your product? If yes, let us know how you use it and how it has improved your business. If you would like to find out more about the Imagga Image Recognition API, please contact us and we'll get back to you promptly.


Multi Language Support - Imagga API

Language support Imagga Image Recogniton

We are happy to announce we are adding 50 languages (still in beta) to Imagga Auto-tagging and Categorization APIs. The tags/categories that the powerful Imagga image recognition API returns now speak your language.  All you need to do is to add the language parameter with corresponding language code you want the results to be displayed in. You can even add multiple languages (for example &language=de&language=fr).

Currently there are 50 languages supported with the following language codes: ar (Arabic), bg (Bulgarian), bs (Bosnian), ca (Catalan), cs (Czech), cy (Welsh), da (Danish), de (German), el (Greek), es (Spanish), et (Estonian), fa (Persian), fi (Finnish), fr (French), he (Hebrew), hi (Hindi), hr (Croatian), ht (Haitian Creole), hu (Hungarian), id (Indonesian), it (Italian), ja (Japanese), ko (Korean), lt (Lithuanian), lv (Latvian), ms (Malay), mt (Maltese), mww (Hmong Daw), nl (Dutch), no (Norwegian), otq (Querétaroo Otomi), pl (Polish), pt (Portuguese), ro (Romanian), ru (Russian), sk Slovak), sv (Swedish), sl (Slovenian), sr_cyrl (Serbian - Cyrillic), sr_latn (Serbian - Latin), th (Thai), tlh (Klingon), tlh_qaak (Klingon (pIqaD)), tr (Turkish), uk (Ukrainian), ur (Urdu), vi (Vietnamese), yua (Yucatec Maya), zh_chs (Chinese Simplified), zh_cht (Chinese Traditional)

Find out how to implement in Imagga API Docs.

You can see how auto-tagging and the language support works live on our demo page.

Not finding yours in the supported languages list? Talk to us.


Update Of Imagga Pricing Plans

Imagga Pricing Plans

We are excited to announce some changes to our API pricing policy. We’ve got lots of feedback and requests for more affordable ways to access our APIs.

Today, we are announcing Developer Plan for Imagga APIs, priced at $14/month that will allow the use of one of our APIs with up to 12 000 calls a month (3000/day, 2 requests/second). We believe this plan will bring on the table flexibility and the opportunity to apply our breakthrough technology on a more affordable price.

Hacker plan remains free but we are reducing the monthly calls to 2000 (200/day, 1 request per second) and will be available as before just for image tagging API.

We are eager to see you how gonna apply our technology in your projects! Send us feedback and any ideas you have regarding our technology offering in general or any tip you want to share.


Seedhack - an awesome experience!

As we announced last week - we were preparing to participate as an API partner in the 3rd edition of Seedhack druing the upcoming weekend. And we did! :) That was a really awesome experience for Imagga. The event started in Friday evening with a lot of hackers and fashionists. Surprisingly or not, most probably becaue of the topic, this was the first hackathon I've participtated with over 40% female attendance.

Seedhack opening
Seedhack opening

Passionate opening by the Seedcamp's team, followed by several keynote speeches from Nick Perrett from HarperCollins Publishers, Nick Cust from NET-A-PORTER.COM and Devin Hunt from Lyst, who provided a lot of inspiration to the participants.

They were followed by API speakers from HarperCollins, ASOS, Google, Net-A-Porter, Imagga (us) and Paypal. In our 5 min API presentation I tried to clearly communicate what Imagga and our APIs are about. It went quite well and a lot of excited people come nearby to talk after :). The word about the event and Imagga even managed to reach New York - in about half an hour after the presentation I got my first email from there, and another one two hours later, regarding the fashion week held in NY at the same time.

The serious hacking started Friday night and continued heavily through the next two days:

Heavy seedhacking
Heavy "seedhacking"

Now, let me share a few numbers that made us feel quite inspired to drill more deeply in the fashion vertical as an appropraite application field for what we do:

  • During the three days of Seedhack we received 11 trial API requests from the "seedhackers": two right away during the API presentation in Friday, two more later in the evening, four more in Saturday, and three more in Sunday. Quite good coverage given that the participating teams were 21 in total;
  • Three of the teams came several times to talk to me for more details about integration ideas, technical details, and pricing;
  • One of the teams - INDELIBLE STYLE (project Colourtag.me) - actually managed to integrate the API during the first day of the weekend! Great job for this team about their passion to levarege on colors, and special "hacker applauses" to Mart Karu who implemented, debugged, and integrated a Ruby client for our color API in no time! He promised to publish it on GutHub in a few days, so you'll be able to enjoy a Ruby blue-print quite soon :)

    Mark Karu and team after a few hours of happy hacking :)
    Mark Karu and team after a few hours of happy hacking :)

Happily enough, exactly this project was one of the five recognized at the award ceremony in Sunday! They win the "Fit & Finish" award, most probably because of their fast execution, including the implementation of a prototype and shooting a promotional video - http://www.youtube.com/watch?v=kPuPKRAV2Sc featuring the brain behind the project - Jessica Healy.

Colourtag.me winning the Fit & Finish award

Now back on Imagga - in addition to the lots of trial requests and the succesfull API integration, from the numerous people that we talked to we got several very creative ideas for potential applications of our cropping and color search, and also some reasonable feature and tweak requests for the APIs. Thank you all, guys!

In conlusion - the event had very very positive atmosphere and was quite well organizated - no tension, everything went smoothly. It also turned out that it's great to have a particular vertical/topic/theme for an event like this - it brings like-minded hackers, mentors and partners and also allows for more objective judging. Well done Seedcamp! Carlos, Kirsten, Ricardo, and Vincent were very supportive through the whole event :) It was a pleasure for me to present imagga and to try to help to the eager hackers there, in your company. Good luck with the future Seedhacks!

Another job well done, so part of the Colourtag.me team and I decided to go for a beer. Luckily there were a few tables for tennis there, so we did our best to beat the locals :):

Table tennis battle with the locals :)

Awesome Seedhack weekend, really!!! :)

P.S.: I think that we managed to improve the public oppinion about Bulgaria at least a little bit this weekend. It should be more clear now that not all Bulgarians are low-qualified labor craving for UK social benefits ;)

P.S.2: You can take a look at the Seedcamp's team perspective of the event, including more details on all particapating and winning teams, here.