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Update iou_loss.py #3394

Merged
merged 1 commit into from
Jul 24, 2020
Merged

Update iou_loss.py #3394

merged 1 commit into from
Jul 24, 2020

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PeterVennerstrom
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Fix NaN issue when predicted [x1,y1,x2,y2] box has no area e.g. [30., 75., 30., 75.]. Predicted boxes of zero area occur early in training of some anchor free detectors.

Fix NaN issue when predicted [x1,y1,x2,y2] box has no area e.g. [30., 75., 30., 75.].  Predicted boxes of zero area occur early in training of some anchor free detectors.
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CLAassistant commented Jul 23, 2020

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codecov bot commented Jul 24, 2020

Codecov Report

Merging #3394 into master will decrease coverage by 0.05%.
The diff coverage is 0.00%.

Impacted file tree graph

@@            Coverage Diff             @@
##           master    #3394      +/-   ##
==========================================
- Coverage   57.97%   57.92%   -0.06%     
==========================================
  Files         202      202              
  Lines       13491    13491              
  Branches     2282     2282              
==========================================
- Hits         7822     7815       -7     
- Misses       5310     5315       +5     
- Partials      359      361       +2     
Flag Coverage Δ
#unittests 57.92% <0.00%> (-0.06%) ⬇️

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Impacted Files Coverage Δ
mmdet/models/losses/iou_loss.py 29.94% <0.00%> (ø)
mmdet/models/roi_heads/test_mixins.py 48.38% <0.00%> (-5.38%) ⬇️
mmdet/datasets/pipelines/transforms.py 72.85% <0.00%> (-0.32%) ⬇️

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@hellock hellock merged commit 963cc00 into open-mmlab:master Jul 24, 2020
@PeterVennerstrom PeterVennerstrom deleted the CIoU-NaN-Fix branch July 24, 2020 12:09
mike112223 pushed a commit to mike112223/mmdetection that referenced this pull request Aug 25, 2020
Fix NaN issue when predicted [x1,y1,x2,y2] box has no area e.g. [30., 75., 30., 75.].  Predicted boxes of zero area occur early in training of some anchor free detectors.
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Dear PeterVennerstrom,
First of all, we want to express our gratitude for your significant PR in the MMDetection project. Your contribution is highly appreciated, and we are grateful for your efforts in helping improve this open-source project during your personal time. We believe that many developers will benefit from your PR.
If you are Chinese or have WeChat,welcome to join our community on WeChat. You can add our assistant :openmmlabwx. Please add "mmsig + Github ID" as a remark when adding friends:)
We would also like to invite you to join our Special Interest Group (SIG) private channel on Discord, where you can share your experiences, ideas, and build connections with like-minded peers. To join the SIG channel, simply message moderator— OpenMMLab on Discord or briefly share your open-source contributions in the #introductions channel and we will assist you. We look forward to seeing you there! Join us :https://discord.gg/raweFPmdzG
Thank you again for your contribution❤
Best regards! @PeterVennerstrom

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4 participants