Comments (3)
I'll try to refine this question further:
If you're looking for categorization in downloads, this is already available in some sources (e.g. Wallhaven) while others have it as an open issue (e.g. Unsplash)
If you're looking for categorization in any arbitrary set of images, this is effectively delving into machine learning / neural networks territory (specifically, look for "image classification"). While a proof of concept of this applied to wallpapers would be quite interesting, it's probably out of Variety's scope and better implemented as a standalone program. In particular, if something can sort images into descriptive folders , then using those in Variety would be as simple as selecting the folders you want at any particular moment.
from variety.
The issue with any sort of ML in Variety is that we can't really bundle the necessary libraries and models with Variety to have the classification work on the user's machine (Tensorflow, numpy, scipy, etc. are all pretty big, and the trained models themselves tend to become quite huge, and also classification is somewhat resource and power-intensive, though this is less of an issue). Which would require us to do this on a server, and it makes things complex.
BUT for this particular use-case I don't even see the need - just curate and adjust your image sources according to what you want to see.
from variety.
Well said - closing as wontfix accordingly.
from variety.
Related Issues (20)
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from variety.