We can All draw simple shapes or sketchy people, cars and so on. But the real talent of the artist is endowed with a few. Oh and if it comes to photoshop, then to personal qualities is added the need to understand the intricacies of the program. But you've probably heard that high technology to facilitate our lives? Now, the moment has arrived: thanks to a new neural network right now, any of you without any special knowledge and skills can paint a pretty good picture.
For the development of the answer not the last people from the world of science, namely researchers from the Massachusetts Institute of Technology (MIT) and experts from units called the IBM Watson AI Lab. To create the drawings thanks to the special generative neural network GAN (Generative Adversarial Networks).
What do I need to do? In fact, nothing special. You have a set of elements: clouds, trees, grass, buildings and so on. As well as the actions that these items can be done — to add to the picture or to remove them. It looks very interesting. You just select the object and action, and then sketch the cursor to a specific area on the photo. Everything else makes the neural network.
Of Course, running a network is not without problems. For example, I would like to note that best it is to sozdatelyami miraculous objects like trees and grass. They look as natural as possible, while the facades of the buildings often look pretty ugly. Especially if you try to remove them or replace with something else.
the this is the turret sticking out from behind either trees, or grass for me to clean up failed
the And here is the opposite example. Originally pictured in the lower part was grass. It turned out clean, and the right part to fit the bushes. Looks very good.
the Rounded roof, added a round dome on the tower, removed the grass and replaced some of the trees on buildings
Yes, the neural network does not always cope with the task, but the first computer was not much computing power, occupying several rooms. This is only a demonstration of future technologies, with due attention will develop into something new and interesting.
In the meantime you can try yourself as an artist. This is a very addictive process. In addition, if you are interested in the internal structure of a neural network — you can watch the video below.
Do you believe in the promise of such technologies? Let us know in the comments and in our
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