{"id":780,"date":"2016-06-24T15:21:37","date_gmt":"2016-06-24T12:21:37","guid":{"rendered":"https:\/\/imagga.com\/blog\/?p=780"},"modified":"2019-06-06T15:56:18","modified_gmt":"2019-06-06T12:56:18","slug":"image-detection-bots-and-imagga","status":"publish","type":"post","link":"https:\/\/imagga.com\/blog\/image-detection-bots-and-imagga\/","title":{"rendered":"Image Detection Bots and Imagga"},"content":{"rendered":"

Looks like 2016 will be the year of bots and almost all of them pretend to use some form of machine learning to do their job even better. Microsoft just released an image detection bot called CaptionBot<\/a>. As all related to image recognition via machine learning, the bot does quite a good job detecting some concepts and quite a bad when it comes to others.<\/p>\n

We always find it fun to compare image recognition services and see how Imagga performs with photos used by users. This blog post was provoked by a friend who posted this on Facebook:<\/p>\n

It\u2019s about an article on TNW about Microsoft CaptionBot<\/a> written by Natt Garun<\/a> and it\u2019s failure to deliver consistent results. We love Microsoft and even use Azure and Microsoft’s Translation tools to improve the language support for tags, but it\u2019s quite tempting to run the test and share.<\/p>\n

We\u2019ve run the same photos included in the article through Imagga API demo, and that\u2019s what our image recognition thinks about it. It\u2019s still not perfect! Have fun exploring the results.<\/p>\n

The first photo is of a home metal hook:<\/p>\n

\"Metal<\/p>\n

We’ve nailed that one, seriously!<\/p>\n

\"AsianObvious description of the photo will be something like Beautiful Asian girl siting in a vegie garden. We are quite close to it with tags like yard, grass, outdors, people. Well, we didn\u2019t figure the rase properly, but that\u2019s something we are cureenlty working on and lots of imporvements coming in couple of months.<\/p>\n

\"Asian<\/p>\n

There\u2019s something about that photo that makes it difficult for the tech to figure out. We didn\u2019t go exeptionally good job here. Well, at least we tagged with happy, witch is obvious from the shaning face of that Asian woman.<\/p>\n

\"Centipede\"<\/p>\n

It\u2019s obvious we do well with living creatures. Thanks good we do not need to figure out if they are male or female and how happy they are.<\/p>\n

\"Darth<\/p>\n

This one is quite dificult as it brings alot of contect, that the machine need to know about. We haven\u2019t trained for movie characters, but tags are in general good. Well, we can argue about the guitar – if you have wild\u00a0imagination you can definately picture Darth Vader with guitar. Human do not apply much in this case, and we are happy with the low confidence level \ud83d\ude09<\/p>\n

\"Man<\/p>\n

Ever wondered where do people come up with ideas for testing? This one is classic. Definately no surfboard and yes, it\u2019s an attractive fashionable male model \ud83d\ude09<\/p>\n

\"Robot\"<\/p>\n

Toy elephents may look like that in the forseeble future, but to us this looks like a man robot. Automation is all what robots are predestened for, right?<\/p>\n

\"Man<\/p>\n

Can\u2019t agree more that the person laying in the grass looks like an alligator. Tags like summer and grass bring a bit of balance to the results. If not accurate at least a bit closer then a cow laying down in a grassy field.<\/p>\n

 <\/p>\n

\"Butter\"<\/p>\n

This one is quite though. What\u2019s quite visible for a person to see, it\u2019s not so visible for the machine, who\u2019s lacking the context of the two mager objects on this photos.<\/p>\n

\"Copy<\/p>\n

It\u2019s great idea to put bed next to any desk in the office. May be one next to the copy machine will not be that good idea – to much noice and traffic arround it.<\/p>\n

\"Brown<\/p>\n

We\u2019ve tried to describe this picture and results are not too bad \ud83d\ude09<\/p>\n

\"Gay<\/p>\n

Last but not least, we do not see donuts but happy, male cople in love. Well, we\u2019ve got a bit of spicy results with less confidence as wife and caucasian, but still\u2026<\/p>\n","protected":false},"excerpt":{"rendered":"

Looks like 2016 will be the year of bots and almost all of them pretend to use some form of […]<\/p>\n","protected":false},"author":2,"featured_media":1218,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[1,4],"tags":[45,64,92,94],"yoast_head":"\nImage Detection Bots by Imagga Image Recognition - Imagga Blog<\/title>\n<meta name=\"description\" content=\"Imagga's image recognition API through a variety of difficult cases. 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