add unet #161
add unet #161
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Codecov Report
@@ Coverage Diff @@
## master #161 +/- ##
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+ Coverage 83.20% 83.64% +0.44%
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Files 83 85 +2
Lines 3924 4061 +137
Branches 619 643 +24
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+ Hits 3265 3397 +132
- Misses 522 525 +3
- Partials 137 139 +2
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Task linked: CU-4fp4hc UNet 模型 |
Co-authored-by: Jerry Jiarui XU <xvjiarui0826@gmail.com>
Co-authored-by: Jerry Jiarui XU <xvjiarui0826@gmail.com>
mmseg/models/backbones/unet.py
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| @UPSAMPLE_LAYERS.register_module(name='deconv_up2x') |
mmseg/models/backbones/unet.py
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| @UPSAMPLE_LAYERS.register_module(name='interp_up') |
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| @UPSAMPLE_LAYERS.register_module(name='interp_up') | |
| @UPSAMPLE_LAYERS.register_module() |
* add unet * add unet * add unet * update test_unet * update test_unet * update test_unet * update test_unet * fix bugs * add init method for unet * add test of UNet init_weights method * add registry * merge upsample * fix test * Update mmseg/models/backbones/unet.py Co-authored-by: Jerry Jiarui XU <xvjiarui0826@gmail.com> * Update mmseg/models/backbones/unet.py Co-authored-by: Jerry Jiarui XU <xvjiarui0826@gmail.com> * split UpConvBlock from UNet * use reversed * rename upsample module * rename upsample module * rename upsample module * rename upsample module Co-authored-by: Jerry Jiarui XU <xvjiarui0826@gmail.com>
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Hi @Junjun2016！First of all, we want to express our gratitude for your significant PR in the MMSegmentation 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 If you have WeChat account，welcome to join our community on WeChat. You can add our assistant ：openmmlabwx. Please add "mmsig + Github ID" as a remark when adding friends：） |
* Add the function to bulid optimizers for sub-models in a model. This function is used in adversarial training. The function is copied from mmediting. * Drop some notice.
add unet