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

[feature request] evaluate mIoU, accu, FID every N iteration #14

Closed
wasd96040501 opened this issue Apr 13, 2019 · 3 comments
Closed

[feature request] evaluate mIoU, accu, FID every N iteration #14

wasd96040501 opened this issue Apr 13, 2019 · 3 comments

Comments

@wasd96040501
Copy link

First, thanks for your amazing work!
In your paper, mIoU, accu, FID are evaluated to make quantitative comparison to related work.
And it seems that these evaluation codes are missing from this version of code?
I think it will be better evaluating and log (or print) these value when we training the model.
For those who what to develop a new method based on your codes (like me), the mIoU, acccu, FID curves will intuitively show us whether our work is promising or not.
Thanks!

@taesungp
Copy link
Contributor

Hello,

Unfortunately, we do not plan to include code for evaluation metrics because it was not written by us.

For FID, we used this code repo pretty much out of the box. https://github.com/mseitzer/pytorch-fid

For semantic segmentation score, we specified in paper which semantic segmentation network we used for evaluation.

@dgrid
Copy link

dgrid commented May 19, 2019

@taesungp
Hi, thanks for your great work!
I have a question.

For FID, especially on COCO-Stuff did you split dataset into train and val and evaluate FID with 5,000 images in val, or just use 50,000 images in train?

@ShihuaHuang95
Copy link

@dgrid Have you figured out which one is used in the FID calculation? @taesungp Would you like to make this clear? Many thanks!

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

4 participants