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Issue in reproducing evaluation results with sparse rcnn checkpoint #30

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ihjasahammedm opened this issue Mar 3, 2023 · 2 comments

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@ihjasahammedm
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ihjasahammedm commented Mar 3, 2023

First of all thank you for releasing the code and ckpts.
I am not able to reproduce the results using config file "sparse_rcnn_focalnet_tiny_fpn_300_proposals_crop_mstrain_480-800_3x_coco_lrf.py" and it's corresponding checkpoint given in readme. The code itself is showing that there is mismatches in state dictionary.
For this to run I also had to update the line 1 in config from _base_ = '../_base_/sparse_rcnn_focalnet_fpn.py' to _base_ = '../_base_/models/sparse_rcnn_focalnet_fpn.py'
image
The metrics obtained are very low and close to zero!
Following is the command I used to run the evaluation:

python tools/test.py configs/focalnet/sparse_rcnn_focalnet_tiny_fpn_300_proposals_crop_mstrain_480-800_3x_coco_lrf.py ckpts/focalnet_tiny_lrf_sparsercnn_3x.pth --eval bbox

Following is mAP values obtained:
image
Could you please look into this and let me know if I am doing something wrong here?

@jwyang
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jwyang commented Mar 10, 2023

thanks for your interest!

I will take a look on it.

@VimukthiRandika1997
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I think in the config section there are no configs relevant to modulation based bbox_head. The one you have evaluated is attention based one. Those files are missing!

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