mmsegmentation/configs/hrnet/fcn_hr18s_512x512_80k_loved...

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[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
_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)))))