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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. ## Motivation Support DDRNet Paper: [Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes](https://arxiv.org/pdf/2101.06085) official Code: https://github.com/ydhongHIT/DDRNet There is already a PR https://github.com/open-mmlab/mmsegmentation/pull/1722 , but it has been inactive for a long time. ## Current Result ### Cityscapes #### inference with converted official weights | Method | Backbone | mIoU(official) | mIoU(converted weight) | | ------ | ------------- | -------------- | ---------------------- | | DDRNet | DDRNet23-slim | 77.8 | 77.84 | | DDRNet | DDRNet23 | 79.5 | 79.53 | #### training with converted pretrained backbone | Method | Backbone | Crop Size | Lr schd | Inf time(fps) | Device | mIoU | mIoU(ms+flip) | config | download | | ------ | ------------- | --------- | ------- | ------- | -------- | ----- | ------------- | ------------ | ------------ | | DDRNet | DDRNet23-slim | 1024x1024 | 120000 | 85.85 | RTX 8000 | 77.85 | 79.80 | [config](https://github.com/whu-pzhang/mmsegmentation/blob/ddrnet/configs/ddrnet/ddrnet_23-slim_in1k-pre_2xb6-120k_cityscapes-1024x1024.py) | model \| log | | DDRNet | DDRNet23 | 1024x1024 | 120000 | 33.41 | RTX 8000 | 79.53 | 80.98 | [config](https://github.com/whu-pzhang/mmsegmentation/blob/ddrnet/configs/ddrnet/ddrnet_23_in1k-pre_2xb6-120k_cityscapes-1024x1024.py) | model \| log | The converted pretrained backbone weights download link: 1. [ddrnet23s_in1k_mmseg.pth](https://drive.google.com/file/d/1Ni4F1PMGGjuld-1S9fzDTmneLfpMuPTG/view?usp=sharing) 2. [ddrnet23_in1k_mmseg.pth](https://drive.google.com/file/d/11rsijC1xOWB6B0LgNQkAG-W6e1OdbCyJ/view?usp=sharing) ## To do - [x] support inference with converted official weights - [x] support training on cityscapes dataset --------- Co-authored-by: xiexinch <xiexinch@outlook.com>
47 lines
1.8 KiB
Python
47 lines
1.8 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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from .ann_head import ANNHead
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from .apc_head import APCHead
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from .aspp_head import ASPPHead
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from .cc_head import CCHead
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from .da_head import DAHead
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from .ddr_head import DDRHead
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from .dm_head import DMHead
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from .dnl_head import DNLHead
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from .dpt_head import DPTHead
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from .ema_head import EMAHead
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from .enc_head import EncHead
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from .fcn_head import FCNHead
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from .fpn_head import FPNHead
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from .gc_head import GCHead
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from .ham_head import LightHamHead
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from .isa_head import ISAHead
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from .knet_head import IterativeDecodeHead, KernelUpdateHead, KernelUpdator
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from .lraspp_head import LRASPPHead
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from .mask2former_head import Mask2FormerHead
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from .maskformer_head import MaskFormerHead
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from .nl_head import NLHead
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from .ocr_head import OCRHead
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from .pid_head import PIDHead
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from .point_head import PointHead
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from .psa_head import PSAHead
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from .psp_head import PSPHead
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from .segformer_head import SegformerHead
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from .segmenter_mask_head import SegmenterMaskTransformerHead
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from .sep_aspp_head import DepthwiseSeparableASPPHead
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from .sep_fcn_head import DepthwiseSeparableFCNHead
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from .setr_mla_head import SETRMLAHead
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from .setr_up_head import SETRUPHead
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from .stdc_head import STDCHead
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from .uper_head import UPerHead
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__all__ = [
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'FCNHead', 'PSPHead', 'ASPPHead', 'PSAHead', 'NLHead', 'GCHead', 'CCHead',
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'UPerHead', 'DepthwiseSeparableASPPHead', 'ANNHead', 'DAHead', 'OCRHead',
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'EncHead', 'DepthwiseSeparableFCNHead', 'FPNHead', 'EMAHead', 'DNLHead',
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'PointHead', 'APCHead', 'DMHead', 'LRASPPHead', 'SETRUPHead',
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'SETRMLAHead', 'DPTHead', 'SETRMLAHead', 'SegmenterMaskTransformerHead',
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'SegformerHead', 'ISAHead', 'STDCHead', 'IterativeDecodeHead',
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'KernelUpdateHead', 'KernelUpdator', 'MaskFormerHead', 'Mask2FormerHead',
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'LightHamHead', 'PIDHead', 'DDRHead'
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]
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