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Reimplement AutoAssign #4295

Merged
merged 40 commits into from
Apr 21, 2021
Merged

Reimplement AutoAssign #4295

merged 40 commits into from
Apr 21, 2021

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jshilong
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@jshilong jshilong commented Dec 13, 2020

I reimplemented autoassign.
I got a similar accuracy of 40.4 vs 40.5 in origin implementation, and the performance is unstable with 1x setting and may fluctuate by about 0.3 mAP. Results between 40.3 and 40.6 are acceptable.

@jshilong jshilong changed the title Reimplement AutoAssign [WIP]Reimplement AutoAssign Dec 13, 2020
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codecov bot commented Dec 13, 2020

Codecov Report

Merging #4295 (9ef65a2) into master (bca2766) will increase coverage by 0.43%.
The diff coverage is 94.32%.

Impacted file tree graph

@@            Coverage Diff             @@
##           master    #4295      +/-   ##
==========================================
+ Coverage   65.59%   66.02%   +0.43%     
==========================================
  Files         255      259       +4     
  Lines       20036    20272     +236     
  Branches     3407     3448      +41     
==========================================
+ Hits        13142    13385     +243     
+ Misses       6188     6172      -16     
- Partials      706      715       +9     
Flag Coverage Δ
unittests 65.99% <94.32%> (+0.44%) ⬆️

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

Impacted Files Coverage Δ
mmdet/models/dense_heads/fcos_head.py 70.08% <ø> (+13.39%) ⬆️
mmdet/models/dense_heads/autoassign_head.py 93.92% <93.92%> (ø)
mmdet/models/dense_heads/__init__.py 100.00% <100.00%> (ø)
mmdet/models/detectors/__init__.py 100.00% <100.00%> (ø)
mmdet/models/detectors/autoassign.py 100.00% <100.00%> (ø)
mmdet/models/necks/fpn.py 95.40% <100.00%> (+0.16%) ⬆️
mmdet/models/detectors/cornernet.py 94.87% <0.00%> (-5.13%) ⬇️
mmdet/apis/inference.py 38.18% <0.00%> (-5.12%) ⬇️
mmdet/models/dense_heads/corner_head.py 73.72% <0.00%> (-1.88%) ⬇️
mmdet/datasets/coco.py 46.25% <0.00%> (-0.06%) ⬇️
... and 10 more

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@Johnson-Wang Johnson-Wang left a comment

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General comments:
The overall code structure is fine to me despite too many hard-coded hyperparameters. Is it possible to specify loss_pos and loss_neg in AutoAssignHead, so that others may be free to change to other loss styles?

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@ZwwWayne
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ZwwWayne commented Feb 2, 2021

  1. Please resolve the conflicts and comments.
  2. After resolving the comments, @jshilong can benchmark models for release

@jshilong jshilong requested a review from ZwwWayne April 7, 2021 16:33
@jshilong jshilong changed the title [WIP]Reimplement AutoAssign Reimplement AutoAssign Apr 19, 2021
@ZwwWayne ZwwWayne merged commit b838270 into open-mmlab:master Apr 21, 2021
@jshilong jshilong deleted the autoassign branch June 1, 2021 12:57
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3 participants