Skip to content
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

NMS in GPU #28

Open
MaskVulcan opened this issue Jan 9, 2018 · 2 comments
Open

NMS in GPU #28

MaskVulcan opened this issue Jan 9, 2018 · 2 comments

Comments

@MaskVulcan
Copy link

I find NMS operations is in CPU.Is there any way to switch to GPU?

@RobertCsordas
Copy link
Owner

As far as I know, TF has only a CPU based NMS implementation. I don't think so that it can be parallelized so well that it can get any significant performance gains on GPU.

@machanic
Copy link

machanic commented Jan 12, 2018

@xdever I think if you calculate all pairs of boxes IOU first, then just for-loop once will ultimately boost speed, there have some trick in it, just see the source code in https://github.com/rbgirshick/py-faster-rcnn/tree/master/lib/nms
I think cuda version of NMS is faster than CPU version if we compile against tensorflow. The above code still have one issue if we use in tensorflow: it moves the data from cpu to gpu memory. We just need to define a new op and copy the source code of rbgirshick in it.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

3 participants