mmsegmentation/configs/mae/mae.yml

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YAML

Models:
- Name: upernet_mae-base_fp16_8x2_512x512_160k_ade20k
In Collection: UperNet
Metadata:
backbone: ViT-B
crop size: (512,512)
lr schd: 160000
inference time (ms/im):
- value: 140.06
hardware: V100
backend: PyTorch
batch size: 1
mode: FP16
resolution: (512,512)
Training Memory (GB): 9.96
Results:
- Task: Semantic Segmentation
Dataset: ADE20K
Metrics:
mIoU: 48.13
mIoU(ms+flip): 48.7
Config: configs/mae/upernet_mae-base_fp16_8x2_512x512_160k_ade20k.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mae/upernet_mae-base_fp16_8x2_512x512_160k_ade20k/upernet_mae-base_fp16_8x2_512x512_160k_ade20k_20220426_174752-f92a2975.pth