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add missing mode "giou" in comments for iou2d_calculator.py #4283

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merged 1 commit into from
Dec 11, 2020

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kaiyux
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@kaiyux kaiyux commented Dec 11, 2020

Add missing mode "giou" in comment of mmdet/core/bbox/iou_calculators/iou2d_calculator.py. It made me a little confusing that I thought "giou" was not supported, hope this helps : )

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codecov bot commented Dec 11, 2020

Codecov Report

Merging #4283 (99fb755) into master (3e902c3) will increase coverage by 0.03%.
The diff coverage is 42.85%.

Impacted file tree graph

@@            Coverage Diff             @@
##           master    #4283      +/-   ##
==========================================
+ Coverage   62.66%   62.70%   +0.03%     
==========================================
  Files         232      232              
  Lines       17597    17607      +10     
  Branches     2942     2945       +3     
==========================================
+ Hits        11028    11041      +13     
+ Misses       6031     6027       -4     
- Partials      538      539       +1     
Flag Coverage Δ
unittests 62.66% <42.85%> (+0.03%) ⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files Coverage Δ
...mdet/core/bbox/iou_calculators/iou2d_calculator.py 96.77% <ø> (ø)
mmdet/models/dense_heads/gfl_head.py 27.35% <ø> (ø)
mmdet/models/dense_heads/yolo_head.py 34.04% <ø> (ø)
mmdet/models/necks/pafpn.py 39.58% <0.00%> (-3.60%) ⬇️
mmdet/core/post_processing/bbox_nms.py 85.96% <33.33%> (-3.13%) ⬇️
mmdet/datasets/samplers/distributed_sampler.py 33.33% <50.00%> (+3.92%) ⬆️
mmdet/models/losses/cross_entropy_loss.py 100.00% <100.00%> (ø)
mmdet/models/necks/fpn.py 94.04% <100.00%> (+0.22%) ⬆️
mmdet/models/dense_heads/corner_head.py 76.77% <0.00%> (+1.91%) ⬆️
mmdet/models/detectors/cornernet.py 100.00% <0.00%> (+5.12%) ⬆️

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@ZwwWayne
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Hi @SiriusKY ,
Thanks for your kind PR. It indeed helps~

@ZwwWayne ZwwWayne merged commit 9ab9aab into open-mmlab:master Dec 11, 2020
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Hi!
@kaiyux
First of all, we want to express our gratitude for your significant PR in the OpenMMLab 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.

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. Look forward to seeing you there! Join us :https://discord.gg/UjgXkPWNqA

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4 participants