-
Notifications
You must be signed in to change notification settings - Fork 4
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
OI Eval and Training Logs #7
Comments
@liuhengyue In terms of the log, I will try to find one (I am a bit oocupied lately.). |
Thanks for your quick reply. I was refering to the code starting RLIPv2/datasets/oi_sgg_eval.py Line 234 in aa91a6b
The ap is computed per GT triplet, whereas people compute per predicate class. The skip for unssen triplet is related to the codes below RLIPv2/datasets/oi_sgg_eval.py Lines 372 to 373 in aa91a6b
|
@liuhengyue For the second query, this is the default operation in mAP calculation for HOI detection. As I remember it, typical SGG mAP calculation has also done something similar to this. I assume that performance will degrade if we do not do this. |
@liuhengyue RLIP_PDA_v2_OISGGtrain_SwinL_VGCOCOO365_RQL_LSE_RPL_20e_L1_20e.txt RLIP_PDA_v2_OISGGtrain_SwinT_VGCOCOO365_RQL_LSE_RPL_20e_L1_20e.txt RLIP_PDA_v2_OISGGtrain_R50_VGCOO365_RQL_LSE_RPL_20e_L1_20e.txt |
Hi,
Fantastic work and thanks for releasing the codebase!
I noticed that your evaluation on Open Images seems different from other approaches. You are computing the mean per GT triplet, instead of per predicate class. You also skip computing for "unseen" triplet. I am not sure if these modifications would introduce big differences when comparing with other methods. Would you mind explain this?
I also would like to ask if you have the training logs that could share, especially on mAPs results for Open Images (object detection results per class, and predicate recall per class).
Thanks.
The text was updated successfully, but these errors were encountered: