mmsegmentation/configs/erfnet/erfnet.yml

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YAML

Collections:
- Name: ERFNet
Metadata:
Training Data:
- Cityscapes
Paper:
URL: http://www.robesafe.uah.es/personal/eduardo.romera/pdfs/Romera17tits.pdf
Title: 'ERFNet: Efficient Residual Factorized ConvNet for Real-time Semantic Segmentation'
README: configs/erfnet/README.md
Code:
URL: https://github.com/open-mmlab/mmsegmentation/blob/v0.20.0/mmseg/models/backbones/erfnet.py#L321
Version: v0.20.0
Converted From:
Code: https://github.com/Eromera/erfnet_pytorch
Models:
- Name: erfnet_fcn_4x4_512x1024_160k_cityscapes
In Collection: ERFNet
Metadata:
backbone: ERFNet
crop size: (512,1024)
lr schd: 160000
inference time (ms/im):
- value: 65.53
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (512,1024)
Training Memory (GB): 6.04
Results:
- Task: Semantic Segmentation
Dataset: Cityscapes
Metrics:
mIoU: 71.08
mIoU(ms+flip): 72.6
Config: configs/erfnet/erfnet_fcn_4x4_512x1024_160k_cityscapes.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/erfnet/erfnet_fcn_4x4_512x1024_160k_cityscapes/erfnet_fcn_4x4_512x1024_160k_cityscapes_20211126_082056-03d333ed.pth