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The algorithm that calculates all tags positions solves the problem if there is a perfect solution (is possible to find a solution without coliding tags with other tags or frames).
But if there is no option, right now it just ignore all the constraints and decide in order of priority.
Im thinking about soft constraints. With them we can choose the option with less coliding tags.
The text was updated successfully, but these errors were encountered:
Well... in the past I thought that this is not a really important issue but after some tests I figure out that this is so important because it can cause efficiency problems while not getting a good result.
So, right now we need to improve intelligence (probably we will need ro recreate the constraints with scipy) while limitting the time expended (so if it calculates the tags position to slowly, just skip it and put it where ever you want).
I think we should change all our hard constraints with soft constraints (minimization of crossing areas).
The algorithm that calculates all tags positions solves the problem if there is a perfect solution (is possible to find a solution without coliding tags with other tags or frames).
But if there is no option, right now it just ignore all the constraints and decide in order of priority.
Im thinking about soft constraints. With them we can choose the option with less coliding tags.
The text was updated successfully, but these errors were encountered: