mmsegmentation/configs/hrnet/fcn_hr18s_512x512_80k_loveda.py
Kingdrone 2bd7f60785
[Feature] Support LoveDA dataset (#1028)
* update LoveDA dataset api

* revised lint errors in dataset_prepare.md

* revised lint errors in loveda.py

* revised lint errors in loveda.py

* revised lint errors in dataset_prepare.md

* revised lint errors in dataset_prepare.md

* checked with isort and yapf

* checked with isort and yapf

* checked with isort and yapf

* Revert "checked with isort and yapf"

This reverts commit 686a51d9

* Revert "checked with isort and yapf"

This reverts commit b877e121bb2935ceefc503c09675019489829feb.

* Revert "revised lint errors in dataset_prepare.md"

This reverts commit 2289e27c

* Revert "checked with isort and yapf"

This reverts commit 159db2f8

* Revert "checked with isort and yapf"

This reverts commit 159db2f8

* add configs & fix bugs

* update new branch

* upload models&logs and add format-only

* change pretraied model path of HRNet

* fix the errors in dataset_prepare.md

* fix the errors in dataset_prepare.md and configs in loveda.py

* change the description in docs_zh-CN/dataset_prepare.md

* use init_cfg

* fix test converage

* adding pseudo loveda dataset

* adding pseudo loveda dataset

* adding pseudo loveda dataset

* adding pseudo loveda dataset

* adding pseudo loveda dataset

* adding pseudo loveda dataset

* Update docs/dataset_prepare.md

Co-authored-by: Junjun2016 <hejunjun@sjtu.edu.cn>

* Update docs_zh-CN/dataset_prepare.md

Co-authored-by: Junjun2016 <hejunjun@sjtu.edu.cn>

* Update docs_zh-CN/dataset_prepare.md

Co-authored-by: Junjun2016 <hejunjun@sjtu.edu.cn>

* Delete unused lines of unittest and Add docs

* add convert .py file

* add downloading links from zenodo

* move place of LoveDA and Cityscapes in doc

* move place of LoveDA and Cityscapes in doc

Co-authored-by: MengzhangLI <mcmong@pku.edu.cn>
Co-authored-by: Junjun2016 <hejunjun@sjtu.edu.cn>
2021-11-24 19:41:19 +08:00

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Python

_base_ = './fcn_hr18_512x512_80k_loveda.py'
model = dict(
backbone=dict(
init_cfg=dict(
type='Pretrained',
checkpoint='open-mmlab://msra/hrnetv2_w18_small'),
extra=dict(
stage1=dict(num_blocks=(2, )),
stage2=dict(num_blocks=(2, 2)),
stage3=dict(num_modules=3, num_blocks=(2, 2, 2)),
stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2)))))