[Feature] Support DDRNet

[qyyyyq]

trafficstars

Hi. I'm a beginner and I want to try to submit an implementation of DDRNet

Motivation

Support DDRNet Paper: Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes official Code: https://github.com/ydhongHIT/DDRNet

Modification

Added backbone code. Added config file for cityscapes. Added tools for converting pretrained models.

Note

1 The training tricks in the paper are not used.Only the basic configuration of mmsegmentation is used. 2 Pretrained models(ImageNet),including the official pretrained weight and the converted pretrained weight can be downloaded from https://drive.google.com/drive/folders/1By_LJCoZGN98i-JsP8xv22VnhIvZnm3w

[CLAassistant]

All committers have signed the CLA.

[MengzhangLI]

Hi, thanks for your nice PR. We have planned to support DDRNet and it is very helpful for this repo.

First, could you please run normally on those models with provided ckpts?

From DDRNet repo ddrnet-23-slim_in1k-pre_2x8_1024x1024_160k_cityscapes.py should be 77.4, ddrnet-23_in1k-pre_2x8_1024x1024_160k_cityscapes.py should be 79.4 and ddrnet-39_in1k-pre_2x8_1024x1024_160k_cityscapes.py should be 80.4.

Thanks in advance!

[codecov[bot]]

Codecov Report

Merging #1722 (6a2bcb3) into master (5c113d9) will decrease coverage by 1.38%. The diff coverage is 19.04%.

@@            Coverage Diff             @@
##           master    #1722      +/-   ##
==========================================
- Coverage   90.24%   88.86%   -1.39%     
==========================================
  Files         142      143       +1     
  Lines        8486     8654     +168     
  Branches     1432     1453      +21     
==========================================
+ Hits         7658     7690      +32     
- Misses        588      724     +136     
  Partials      240      240              

Flag	Coverage Δ
unittests	88.86% <19.04%> (-1.39%)	:arrow_down:

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

Impacted Files	Coverage Δ
mmseg/models/backbones/ddrnet.py	18.56% <18.56%> (ø)
mmseg/models/backbones/__init__.py	100.00% <100.00%> (ø)

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[MengzhangLI]

Hi, @qyyyyq

Refactory code is necessary and we may leave out more comments in the next few days. You can refer to my re-implementing code of STDC for example.

Original: https://github.com/MichaelFan01/STDC-Seg/blob/master/nets/stdcnet.py Ours:https://github.com/open-mmlab/mmsegmentation/blob/master/mmseg/models/backbones/stdc.py

Best,

[MengzhangLI]

Hi, @qyyyyq Can you send your wechat id to my e-mail? We could use it to discuss more effectively if you can speak chinese.

[tommiekerssies]

What is the status of this PR?

[OpenMMLab-Assistant-004]

Hi @qyyyyq ！We are grateful for your efforts in helping improve mmsegmentation 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 If you have a 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：）

Thank you again for your contribution❤