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cgnet.yml
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cgnet.yml
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Collections:
- Name: CGNet
Metadata:
Training Data:
- Cityscapes
Paper:
URL: https://arxiv.org/abs/1811.08201
Title: 'CGNet: A Light-weight Context Guided Network for Semantic Segmentation'
README: configs/cgnet/README.md
Code:
URL: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/cgnet.py#L187
Version: v0.17.0
Converted From:
Code: https://github.com/wutianyiRosun/CGNet
Models:
- Name: cgnet_680x680_60k_cityscapes
In Collection: CGNet
Metadata:
backbone: M3N21
crop size: (680,680)
lr schd: 60000
inference time (ms/im):
- value: 32.78
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (680,680)
Training Memory (GB): 7.5
Results:
- Task: Semantic Segmentation
Dataset: Cityscapes
Metrics:
mIoU: 65.63
mIoU(ms+flip): 68.04
Config: configs/cgnet/cgnet_680x680_60k_cityscapes.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/cgnet/cgnet_680x680_60k_cityscapes/cgnet_680x680_60k_cityscapes_20201101_110253-4c0b2f2d.pth
- Name: cgnet_512x1024_60k_cityscapes
In Collection: CGNet
Metadata:
backbone: M3N21
crop size: (512,1024)
lr schd: 60000
inference time (ms/im):
- value: 32.11
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (512,1024)
Training Memory (GB): 8.3
Results:
- Task: Semantic Segmentation
Dataset: Cityscapes
Metrics:
mIoU: 68.27
mIoU(ms+flip): 70.33
Config: configs/cgnet/cgnet_512x1024_60k_cityscapes.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/cgnet/cgnet_512x1024_60k_cityscapes/cgnet_512x1024_60k_cityscapes_20201101_110254-124ea03b.pth