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[Feature] Add detection distill algorithm LAD #436
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Thanks for your constructive PR, it is a great application example of the delivery
module.
Please make further modifications based on my comments to merge this PR into MMRazor
.
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| Teacher | Student | Training schedule | AP (val) | Config | Download | | ||
| :-----: | :-----: | :---------------: | :------: | :----------: | :----------------------: | | ||
| -- | R-50 | 1x | 40.4 | [config](<>) | [model](<>) \| [log](<>) | |
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Maybe can add the paths of config, model and log for the two baselines from MMClassification
.
| -- | R-50 | 1x | 40.4 | [config](<>) | [model](<>) \| [log](<>) | | ||
| -- | R-101 | 1x | 42.6 | [config](<>) | [model](<>) \| [log](<>) | | ||
| R-101 | R-50 | 1x | 41.4 | [config](<>) | [model](<>) \| [log](<>) | | ||
| R-50 | R-101 | 1x | 43.2 | [config](<>) | [model](<>) \| [log](<>) | |
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Please add the config of this distillation (lad_ppa_r50_ppa_r101_1x_coco.py).
And contact with @pppppM to upload the files (model and log) after training.
@@ -0,0 +1,30 @@ | |||
_base_ = ['mmdet::paa/paa_r101_fpn_1x_coco.py'] |
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Backbone
of the student model should be r50
.
* refactor(onnx2ncnn.cpp): split it to shape_inference, pass and utils * refactor(onnx2ncnn.cpp): split it to shape_inference, pass and utils * refactor(onnx2ncnn.cpp): split code * refactor(net_module.cpp): fix build error * ci(test_onnx2ncnn.py): add generate model adn run * ci(onnx2ncnn): add ncnn backend * ci(test_onnx2ncnn): add converted onnx model` * ci(onnx2ncnn): fix ncnn tar * ci(backed-ncnn): simplify dependency install * ci(onnx2ncnn): fix apt install * Update backend-ncnn.yml * Update backend-ncnn.yml * Update backend-ncnn.yml * Update backend-ncnn.yml * Update backend-ncnn.yml * Update backend-ncnn.yml * Update backend-ncnn.yml * Update backend-ncnn.yml * Update backend-ncnn.yml * Update backend-ncnn.yml * Update backend-ncnn.yml * fix(ci): add include algorithm * Update build.yml * parent aa85760 author q.yao <[email protected]> 1651287879 +0800 committer tpoisonooo <[email protected]> 1652169959 +0800 [Fix] Fix ci (open-mmlab#426) * fix ci * add nvidia key * remote torch * recover pytorch refactor(onnx2ncnn.cpp): split it to shape_inference, pass and utils * fix(onnx2ncnn): review * fix(onnx2ncnn): build error Co-authored-by: q.yao <[email protected]>
Hi @LiuQQQQQQQ !We are grateful for your efforts in helping improve this open-source project during your personal time. Welcome to join OpenMMLab 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 Thank you again for your contribution❤ |
Thanks for your contribution and we appreciate it a lot. The following instructions would make your pull request more healthy and more easily get feedback. If you do not understand some items, don't worry, just make the pull request and seek help from maintainers.
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