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Thank you for open sourcing your paper! The results presented in the paper are extremely compelling.
I have some questions and requests:
do you plan to release all of the configs you used in the paper? I would greatly appreciate it so I can reproduce the Cityscapes results. Also, are there any weights that you can share to verify evaluations for Cityscapes and Pascal VOC?
do you have a specific way to evaluate the trained models? I was going to start training the only available config ('cps_meanteacher_3b_w1.5_...'), and was wondering if the saved checkpoints can be directly used for tools/test.py.
For ExpSemiLossCPSFAWS3 (which I assume is the Lst and Lss losses) seem to not use knowledge selection. Reading the code, the self.prob seems to be the threshold, but I don't see anywhere where that is set to 0.95 as in the paper.
The text was updated successfully, but these errors were encountered:
Thank you for open sourcing your paper! The results presented in the paper are extremely compelling.
I have some questions and requests:
tools/test.py
.ExpSemiLossCPSFAWS3
(which I assume is the Lst and Lss losses) seem to not use knowledge selection. Reading the code, theself.prob
seems to be the threshold, but I don't see anywhere where that is set to 0.95 as in the paper.The text was updated successfully, but these errors were encountered: