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I am working on some code with open cv to track the percentage of frames in which my face is detected in terms of "attention span". I intend to optimize this attention span with an evolutionary solver that iterates a combination of diffused and direct light levels in my environment with an arduino board. Owing to the long range of time over which a generation of light levels need to be iterated I am unsure as to the best Evolutionary algorithm library or approach i can use to do this. I am currently not connected to an arduino and am just trying to do this with dummy numbers (1-4,1-4) for diffused and direct respectively. The idea is that every 15 mins or so ( lets say 50,000 frames) the light levels assume a new and improved combination and wait for another 15.
I am new to python and coding in general so I am finding it harder to figure out which library and it's ideal implementation for this purpose I'd be grateful if you have any advice.
The text was updated successfully, but these errors were encountered:
Hey!
I am working on some code with open cv to track the percentage of frames in which my face is detected in terms of "attention span". I intend to optimize this attention span with an evolutionary solver that iterates a combination of diffused and direct light levels in my environment with an arduino board. Owing to the long range of time over which a generation of light levels need to be iterated I am unsure as to the best Evolutionary algorithm library or approach i can use to do this. I am currently not connected to an arduino and am just trying to do this with dummy numbers (1-4,1-4) for diffused and direct respectively. The idea is that every 15 mins or so ( lets say 50,000 frames) the light levels assume a new and improved combination and wait for another 15.
I am new to python and coding in general so I am finding it harder to figure out which library and it's ideal implementation for this purpose I'd be grateful if you have any advice.
The text was updated successfully, but these errors were encountered: