Comments (5)
The limiting factor for speed is the time it takes to capture a screenshot. The neural net itself is very quick, but the screen capture FPS is slower. I'm looking into using Nvidia CUDA API's to extract the raw framebuffer from the GPU (rather than using the pywin32 API, which is much slower). ...
@petercunha I‘ve looked into this and I dont think its possible
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The limiting factor for speed is the time it takes to capture a screenshot. The neural net itself is very quick, but the screen capture FPS is slower. I'm looking into using Nvidia CUDA API's to extract the raw framebuffer from the GPU (rather than using the pywin32 API, which is much slower).
If you have any other ideas to improve speed, feel free to write the code and open a PR.
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@petercunha I believe why it is not possible because python runs in its own environment kinda like a virtual computer, at least based on my research and my use of python, which means that you can't really get a raw buffer from the GPU. But if anything you can with do it ctypes or something I have not heard of. You also might want to look into this https://github.com/SerpentAI/D3DShot Great Programmer used his SerpentAI Framework in the past,
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These are the fps rates:
2560x1440 on NVIDIA GTX 1080 Ti 1920x1080 on Intel UHD Graphics 630 1080x1920 (vertical) on Intel UHD Graphics 630
"pil" 29.717 FPS 47.75 FPS 35.95 FPS
"numpy" 57.667 FPS 58.1 FPS 58.033 FPS
"numpy_float" 18.783 FPS 29.05 FPS 27.517 FPS
"pytorch" 57.867 FPS 58.1 FPS 34.817 FPS
"pytorch_float" 18.767 FPS 28.367 FPS 27.017 FPS
Just imagine a 1060 6GB on 1080p
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@AutisticDragon thanks for sharing the benchmarks! I will also look into that library you recommended.
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