Hi.
I'm interested in capturing greyscale screenshots at a very high rate for use in machine learning tasks (see [1] for an example). I've found mss to be fast at capturing color and greyscale screenshots compared to other solutions. Nevertheless, on MacOS, to use cv2 with them via PIL, I think the BGR<->RGB happens twice (once in mss and another time in PIL) before I send it off to greyscale.
This made me think to ask you if an option to go straight to greyscale would make sense for mss. I saw an old issue closed stating that greyscale wasn't in line with project goals. I suspect that would be because someone can convert easily to greyscale down the line. However, if the conversion happens upstream at mss, the data flowing downstream is 1/3 the size I believe. Perhaps there would be an frames per second (performance) boost if greyscale could be captured early/directly?
Thanks for this great project.
Please let me know your thoughts. (I'm new to graphical processing in python3.)
Thanks,
Joshua
[1] https://www.youtube.com/watch?v=edWI4ZnWUGg
Hi.
I'm interested in capturing greyscale screenshots at a very high rate for use in machine learning tasks (see [1] for an example). I've found mss to be fast at capturing color and greyscale screenshots compared to other solutions. Nevertheless, on MacOS, to use
cv2with them via PIL, I think the BGR<->RGB happens twice (once in mss and another time in PIL) before I send it off to greyscale.This made me think to ask you if an option to go straight to greyscale would make sense for mss. I saw an old issue closed stating that greyscale wasn't in line with project goals. I suspect that would be because someone can convert easily to greyscale down the line. However, if the conversion happens upstream at mss, the data flowing downstream is 1/3 the size I believe. Perhaps there would be an frames per second (performance) boost if greyscale could be captured early/directly?
Thanks for this great project.
Please let me know your thoughts. (I'm new to graphical processing in python3.)
Thanks,
Joshua
[1] https://www.youtube.com/watch?v=edWI4ZnWUGg