Comments (4)
Hi UdonDa,
Thanks for asking.
But for now, the post-processing (DenseCRF) part has not been included in the repository.
The DenseCRF code is based on Matlab and was developed by another author.
Unfortunately, I currently have no access to his server.
I will upload them next week (after I return from the NeurIPS conference).
Cheng-Chun
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Thanks for replying.
You implement the CRF part by MATLAB, ok.
So, run_test function
in [here] (https://github.com/chengchunhsu/WSIS_BBTP/blob/master/tools/train_net.py#L79)do not work now, right?
I think that It's easier to implement CRF by pydencecrf.
After you upload the part, I will try!
Please do your best NeurlPS.
Thanks.
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Hi UdonDa,
Actually, the run_test
function will evaluate the performance of the trained model "without" post-processing (DenseCRF).
If you have implemented the post-processing part in python.
You can let me know by opening an issue or commits.
Thanks!
Cheng-Chun
from wsis_bbtp.
Hi @UdonDa , what is your mask AP on VOC 2012 validation set.
We strictly follow the author's settings, however, we cannot reproduce the results.
Box AP:
AP25: 0.81
AP50: 0.74
AP70: 0.54
AP75: 0.46
Mask AP: (wo/ CRF)
AP25: 0.74
AP50: 0.44
AP70: 0.16
AP75: 0.11
Could you please share your Mask AP result? We have at least 9 points gap compared to the author's reported results.
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Related Issues (13)
- When the code will be released? HOT 5
- How to download and prepare the MS-COCO dataset?
- Issues with IoU Computation in The Eval Code HOT 4
- Colab Interface?
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- Can you share your 'voc_2012_val_cocostyle' file? HOT 5
- questions with respect to the negative samples. HOT 3
- Implementation issue HOT 4
- can this one train without distributed
- Implementation issue
- Start training and ended HOT 2
- questions with the implementation of the pairwise term
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