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poolformer.yml
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Models:
- Name: fpn_poolformer_s12_8x4_512x512_40k_ade20k
In Collection: FPN
Metadata:
backbone: PoolFormer-S12
crop size: (512,512)
lr schd: 40000
inference time (ms/im):
- value: 42.59
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (512,512)
Training Memory (GB): 4.17
Results:
- Task: Semantic Segmentation
Dataset: ADE20K
Metrics:
mIoU: 36.68
mIoU(ms+flip): 38.22
Config: configs/poolformer/fpn_poolformer_s12_8x4_512x512_40k_ade20k.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/poolformer/fpn_poolformer_s12_8x4_512x512_40k_ade20k/fpn_poolformer_s12_8x4_512x512_40k_ade20k_20220501_115154-b5aa2f49.pth
- Name: fpn_poolformer_s24_8x4_512x512_40k_ade20k
In Collection: FPN
Metadata:
backbone: PoolFormer-S24
crop size: (512,512)
lr schd: 40000
inference time (ms/im):
- value: 63.53
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (512,512)
Training Memory (GB): 5.47
Results:
- Task: Semantic Segmentation
Dataset: ADE20K
Metrics:
mIoU: 40.12
mIoU(ms+flip): 40.97
Config: configs/poolformer/fpn_poolformer_s24_8x4_512x512_40k_ade20k.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/poolformer/fpn_poolformer_s24_8x4_512x512_40k_ade20k/fpn_poolformer_s24_8x4_512x512_40k_ade20k_20220503_222049-394a7cf7.pth
- Name: fpn_poolformer_s36_8x4_512x512_40k_ade20k
In Collection: FPN
Metadata:
backbone: PoolFormer-S36
crop size: (512,512)
lr schd: 40000
inference time (ms/im):
- value: 88.18
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (512,512)
Training Memory (GB): 6.77
Results:
- Task: Semantic Segmentation
Dataset: ADE20K
Metrics:
mIoU: 41.61
mIoU(ms+flip): 42.61
Config: configs/poolformer/fpn_poolformer_s36_8x4_512x512_40k_ade20k.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/poolformer/fpn_poolformer_s36_8x4_512x512_40k_ade20k/fpn_poolformer_s36_8x4_512x512_40k_ade20k_20220501_151122-b47e607d.pth
- Name: fpn_poolformer_m36_8x4_512x512_40k_ade20k
In Collection: FPN
Metadata:
backbone: PoolFormer-M36
crop size: (512,512)
lr schd: 40000
inference time (ms/im):
- value: 111.48
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (512,512)
Training Memory (GB): 8.59
Results:
- Task: Semantic Segmentation
Dataset: ADE20K
Metrics:
mIoU: 41.95
mIoU(ms+flip): 43.24
Config: configs/poolformer/fpn_poolformer_m36_8x4_512x512_40k_ade20k.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/poolformer/fpn_poolformer_m36_8x4_512x512_40k_ade20k/fpn_poolformer_m36_8x4_512x512_40k_ade20k_20220501_164230-3dc83921.pth
- Name: fpn_poolformer_m48_8x4_512x512_40k_ade20k
In Collection: FPN
Metadata:
backbone: PoolFormer-M48
crop size: (512,512)
lr schd: 40000
inference time (ms/im):
- value: 149.48
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (512,512)
Training Memory (GB): 10.48
Results:
- Task: Semantic Segmentation
Dataset: ADE20K
Metrics:
mIoU: 42.43
mIoU(ms+flip): 43.6
Config: configs/poolformer/fpn_poolformer_m48_8x4_512x512_40k_ade20k.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/poolformer/fpn_poolformer_m48_8x4_512x512_40k_ade20k/fpn_poolformer_m48_8x4_512x512_40k_ade20k_20220504_003923-64168d3b.pth