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[Refactor] Add simple_test to dense heads #5061

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shinya7y
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This PR improves consistency of implementation (single-stage vs. two-stage, normal dense heads vs. RPN heads, simple_test vs. aug_test).
Related discussion: #3638 (review)

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codecov bot commented Apr 26, 2021

Codecov Report

Merging #5061 (69a4ed7) into master (24b6f93) will decrease coverage by 0.04%.
The diff coverage is 74.15%.

❗ Current head 69a4ed7 differs from pull request most recent head 90656ee. Consider uploading reports for the commit 90656ee to get more accurate results
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@@            Coverage Diff             @@
##           master    #5061      +/-   ##
==========================================
- Coverage   65.33%   65.28%   -0.05%     
==========================================
  Files         276      275       -1     
  Lines       21204    21215      +11     
  Branches     3522     3524       +2     
==========================================
- Hits        13854    13851       -3     
- Misses       6601     6617      +16     
+ Partials      749      747       -2     
Flag Coverage Δ
unittests 65.25% <71.91%> (-0.05%) ⬇️

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

Impacted Files Coverage Δ
mmdet/models/dense_heads/cascade_rpn_head.py 22.71% <0.00%> (ø)
mmdet/models/detectors/detr.py 100.00% <ø> (ø)
mmdet/models/roi_heads/point_rend_roi_head.py 19.62% <ø> (ø)
mmdet/models/dense_heads/yolact_head.py 79.32% <33.33%> (-2.44%) ⬇️
mmdet/models/dense_heads/embedding_rpn_head.py 93.18% <50.00%> (-4.32%) ⬇️
mmdet/models/detectors/yolact.py 94.28% <75.00%> (+20.28%) ⬆️
mmdet/models/dense_heads/detr_head.py 88.54% <80.00%> (-0.45%) ⬇️
mmdet/models/dense_heads/dense_test_mixins.py 45.12% <86.84%> (+32.07%) ⬆️
mmdet/models/dense_heads/base_dense_head.py 91.30% <100.00%> (+0.82%) ⬆️
mmdet/models/dense_heads/centernet_head.py 83.45% <100.00%> (+0.12%) ⬆️
... and 8 more

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@hhaAndroid
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Thank you for your contribution, I think it is very good. Can you resolve the conflict?

The outer list corresponds to each image. The inner list
corresponds to each class.
"""
return self.simple_test_bboxes(
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Seems you add this arguments postprocess to get raw results of boxes in yolact, but I believe original design keep bbbox2results is single-stage would a better design and can do the same thing, Is there other reasons?

In addition, I think keeping this operation in the SingleStageDetector instead of simple_test_bboxes would be more consistent with the two-tage models.
just like

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I added the argument postprocess to simplify code for onnx.

# skip post-processing when exporting to ONNX
postprocess = False

The original reason disappeared after #5205

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@jshilong jshilong May 31, 2021

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The overall design looks good to me, and I would help to move bbbox2results to simple_test of single_stage.py.
It would be merged soon, Thanks for your contribution.

v-qjqs and others added 5 commits May 31, 2021 16:56
…arable performance (open-mmlab#5136)

* Supports for exporting CornerNet to ONNX with dynamic shapes and comparable performance

* add docs for exporting cornernet, and simplify code

* fix doc

* format doc

* fix docstring
* Update fcn_mask_head.py

* Update fcn_mask_head.py

* Update fcn_mask_head.py

* Resolve format issues

Co-authored-by: Wenwei Zhang <40779233+ZwwWayne@users.noreply.github.com>
* evaluate trt models

* update version of onnx

* update maskrcnn results

* add backend argument

* update fcos results

* update

* fix bug

* update  doc
* update changelog

* update changelog

* Improvements

* Improvements

* update for v2.13.0

Co-authored-by: hhaAndroid <1286304229@qq.com>
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ZwwWayne commented Jun 3, 2021

Merged through #5264. So this PR is closed.

@ZwwWayne ZwwWayne closed this Jun 3, 2021
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7 participants