The Wolfram Language Image Identification Project is a new function of Wolfram Language that can be used to identify what images are about.
It is usually easy to identify what is shown on a picture. While it may sometimes be difficult to identify an object or people correctly, it is usually no problem to put it in a broader context.
For instance, while you may not know the specific model of a car or the name of a flower, you will be able to tell that a car or a flower is the main focus of a picture.
The Image Identification Project by Wolfram demonstrates how far computers have come when it comes to identifying images.
The demo website itself is easy to use. Just drag and drop an image onto it to have it identified by the algorithm.
The processing should not take longer than a couple of seconds with results being displayed on the next screen.
The algorithms success rate appears astonishingly high. While it may not deliver detailed results all of the time -- like when you use the sample images that are provided on the project website -- it seems capable of providing a broader classification more often than not.
It does a good job at identifying plants or animals correctly for instance. Additional information about the identified object are displayed on the same page.
You may also rate the identification of the image and may even add your own suggestions if the identification was not correct.
The algorithm won't identify people, art or buildings most of the time. If you upload Van Gogh's Starry Night picture for instance, it is identified as an artifact. John F. Kennedy on the other hand was identified correctly by the algorithm.
The image identification algorithm won't identify abstract art currently, most people and generally speaking things that are not everyday objects.
According to the FAQ, it uses natural clues in the identification process. For instance, it may identify a boat better if it is on water or a tree if ground is displayed on the picture as well.
Additional information about the algorithm and Wolfram Language are available on the official blog.
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