-
Notifications
You must be signed in to change notification settings - Fork 206
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
How can I Speed up the modle #8
Comments
Hi, The current version is slow because the face alignment method (from the dlib library) requires face detection to run in every frame. For now you can download this faster version from Dropbox here: Keep in mind that you need to install additional Python modules as detailed in the Deep Alignment Network repo. You will also need a gpu compatible with CUDA if you want it to work fast. Let me know if that helps. Marek |
@MarekKowalski |
Yeah, it defienietly has to run on GPU to be fast. |
How can I run this program on GPU, please let me know. |
Hi, If you mean the program I linked on Dropbox then please take a look at the installation requirements in this repo: Marek |
Hi, Minhaz |
Hi, No idea, look at the theano documentation and see there (theano is the library that uses the GPU). Marek |
Hi, |
Hi, Are you using the version that I supplied above in dropbox or the version in the repo? Marek |
Hi, The performance of the face alignment step (DAN) would definitely be lower than what you would get from a GPU equipped desktop computer. There would definitely be some room for performance improvements in other places, as there are some things that Python is very slow at. I am however not sure that it would be sufficiently fast. One thing you might want to try to improve the DAN performance is to only use a single stage instead of two stages. You can specify that in the constructor parameters. Best regards, Marek |
The speed is very slow, and imges delay to the camera.
How to optimize it to speed up it's speed?
The text was updated successfully, but these errors were encountered: