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mmsegmentation/configs/twins/twins.yml

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Models:
- Name: twins_pcpvt-s_fpn_fpnhead_8x4_512x512_80k_ade20k
In Collection: FPN
Metadata:
backbone: PCPVT-S
crop size: (512,512)
lr schd: 80000
inference time (ms/im):
- value: 36.83
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (512,512)
Training Memory (GB): 6.6
Results:
- Task: Semantic Segmentation
Dataset: ADE20K
Metrics:
mIoU: 43.26
mIoU(ms+flip): 44.11
Config: configs/twins/twins_pcpvt-s_fpn_fpnhead_8x4_512x512_80k_ade20k.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/twins/twins_pcpvt-s_fpn_fpnhead_8x4_512x512_80k_ade20k/twins_pcpvt-s_fpn_fpnhead_8x4_512x512_80k_ade20k_20211201_204132-41acd132.pth
- Name: twins_pcpvt-s_uperhead_8x4_512x512_160k_ade20k
In Collection: UPerNet
Metadata:
backbone: PCPVT-S
crop size: (512,512)
lr schd: 160000
inference time (ms/im):
- value: 70.22
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (512,512)
Training Memory (GB): 9.67
Results:
- Task: Semantic Segmentation
Dataset: ADE20K
Metrics:
mIoU: 46.04
mIoU(ms+flip): 46.92
Config: configs/twins/twins_pcpvt-s_uperhead_8x4_512x512_160k_ade20k.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/twins/twins_pcpvt-s_uperhead_8x4_512x512_160k_ade20k/twins_pcpvt-s_uperhead_8x4_512x512_160k_ade20k_20211201_233537-8e99c07a.pth
- Name: twins_pcpvt-b_fpn_fpnhead_8x4_512x512_80k_ade20k
In Collection: FPN
Metadata:
backbone: PCPVT-B
crop size: (512,512)
lr schd: 80000
inference time (ms/im):
- value: 50.84
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (512,512)
Training Memory (GB): 8.41
Results:
- Task: Semantic Segmentation
Dataset: ADE20K
Metrics:
mIoU: 45.66
mIoU(ms+flip): 46.48
Config: configs/twins/twins_pcpvt-b_fpn_fpnhead_8x4_512x512_80k_ade20k.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/twins/twins_pcpvt-b_fpn_fpnhead_8x4_512x512_80k_ade20k/twins_pcpvt-b_fpn_fpnhead_8x4_512x512_80k_ade20k_20211130_141019-d396db72.pth
- Name: twins_pcpvt-b_uperhead_8x2_512x512_160k_ade20k
In Collection: UPerNet
Metadata:
backbone: PCPVT-B
crop size: (512,512)
lr schd: 160000
inference time (ms/im):
- value: 83.06
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (512,512)
Training Memory (GB): 6.46
Results:
- Task: Semantic Segmentation
Dataset: ADE20K
Metrics:
mIoU: 47.91
mIoU(ms+flip): 48.64
Config: configs/twins/twins_pcpvt-b_uperhead_8x2_512x512_160k_ade20k.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/twins/twins_pcpvt-b_uperhead_8x2_512x512_160k_ade20k/twins_pcpvt-b_uperhead_8x2_512x512_160k_ade20k_20211130_141020-02094ea5.pth
- Name: twins_pcpvt-l_fpn_fpnhead_8x4_512x512_80k_ade20k
In Collection: FPN
Metadata:
backbone: PCPVT-L
crop size: (512,512)
lr schd: 80000
inference time (ms/im):
- value: 69.83
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (512,512)
Training Memory (GB): 10.78
Results:
- Task: Semantic Segmentation
Dataset: ADE20K
Metrics:
mIoU: 45.94
mIoU(ms+flip): 46.7
Config: configs/twins/twins_pcpvt-l_fpn_fpnhead_8x4_512x512_80k_ade20k.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/twins/twins_pcpvt-l_fpn_fpnhead_8x4_512x512_80k_ade20k/twins_pcpvt-l_fpn_fpnhead_8x4_512x512_80k_ade20k_20211201_105226-bc6d61dc.pth
- Name: twins_pcpvt-l_uperhead_8x2_512x512_160k_ade20k
In Collection: UPerNet
Metadata:
backbone: PCPVT-L
crop size: (512,512)
lr schd: 160000
inference time (ms/im):
- value: 93.46
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (512,512)
Training Memory (GB): 7.82
Results:
- Task: Semantic Segmentation
Dataset: ADE20K
Metrics:
mIoU: 49.35
mIoU(ms+flip): 50.08
Config: configs/twins/twins_pcpvt-l_uperhead_8x2_512x512_160k_ade20k.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/twins/twins_pcpvt-l_uperhead_8x2_512x512_160k_ade20k/twins_pcpvt-l_uperhead_8x2_512x512_160k_ade20k_20211201_075053-c6095c07.pth
- Name: twins_svt-s_fpn_fpnhead_8x4_512x512_80k_ade20k
In Collection: FPN
Metadata:
backbone: SVT-S
crop size: (512,512)
lr schd: 80000
inference time (ms/im):
- value: 33.57
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (512,512)
Training Memory (GB): 5.8
Results:
- Task: Semantic Segmentation
Dataset: ADE20K
Metrics:
mIoU: 44.47
mIoU(ms+flip): 45.42
Config: configs/twins/twins_svt-s_fpn_fpnhead_8x4_512x512_80k_ade20k.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/twins/twins_svt-s_fpn_fpnhead_8x4_512x512_80k_ade20k/twins_svt-s_fpn_fpnhead_8x4_512x512_80k_ade20k_20211130_141006-0a0d3317.pth
- Name: twins_svt-s_uperhead_8x2_512x512_160k_ade20k
In Collection: UPerNet
Metadata:
backbone: SVT-S
crop size: (512,512)
lr schd: 160000
inference time (ms/im):
- value: 66.27
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (512,512)
Training Memory (GB): 4.93
Results:
- Task: Semantic Segmentation
Dataset: ADE20K
Metrics:
mIoU: 46.08
mIoU(ms+flip): 46.96
Config: configs/twins/twins_svt-s_uperhead_8x2_512x512_160k_ade20k.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/twins/twins_svt-s_uperhead_8x2_512x512_160k_ade20k/twins_svt-s_uperhead_8x2_512x512_160k_ade20k_20211130_141005-e48a2d94.pth
- Name: twins_svt-b_fpn_fpnhead_8x4_512x512_80k_ade20k
In Collection: FPN
Metadata:
backbone: SVT-B
crop size: (512,512)
lr schd: 80000
inference time (ms/im):
- value: 47.39
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (512,512)
Training Memory (GB): 8.75
Results:
- Task: Semantic Segmentation
Dataset: ADE20K
Metrics:
mIoU: 46.77
mIoU(ms+flip): 47.47
Config: configs/twins/twins_svt-b_fpn_fpnhead_8x4_512x512_80k_ade20k.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/twins/twins_svt-b_fpn_fpnhead_8x4_512x512_80k_ade20k/twins_svt-b_fpn_fpnhead_8x4_512x512_80k_ade20k_20211201_113849-88b2907c.pth
- Name: twins_svt-b_uperhead_8x2_512x512_160k_ade20k
In Collection: UPerNet
Metadata:
backbone: SVT-B
crop size: (512,512)
lr schd: 160000
inference time (ms/im):
- value: 78.99
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: 48.04
mIoU(ms+flip): 48.87
Config: configs/twins/twins_svt-b_uperhead_8x2_512x512_160k_ade20k.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/twins/twins_svt-b_uperhead_8x2_512x512_160k_ade20k/twins_svt-b_uperhead_8x2_512x512_160k_ade20k_20211202_040826-0943a1f1.pth
- Name: twins_svt-l_fpn_fpnhead_8x4_512x512_80k_ade20k
In Collection: FPN
Metadata:
backbone: SVT-L
crop size: (512,512)
lr schd: 80000
inference time (ms/im):
- value: 56.18
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (512,512)
Training Memory (GB): 11.2
Results:
- Task: Semantic Segmentation
Dataset: ADE20K
Metrics:
mIoU: 46.55
mIoU(ms+flip): 47.74
Config: configs/twins/twins_svt-l_fpn_fpnhead_8x4_512x512_80k_ade20k.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/twins/twins_svt-l_fpn_fpnhead_8x4_512x512_80k_ade20k/twins_svt-l_fpn_fpnhead_8x4_512x512_80k_ade20k_20211130_141005-1d59bee2.pth
- Name: twins_svt-l_uperhead_8x2_512x512_160k_ade20k
In Collection: UPerNet
Metadata:
backbone: SVT-L
crop size: (512,512)
lr schd: 160000
inference time (ms/im):
- value: 93.2
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (512,512)
Training Memory (GB): 8.41
Results:
- Task: Semantic Segmentation
Dataset: ADE20K
Metrics:
mIoU: 49.65
mIoU(ms+flip): 50.63
Config: configs/twins/twins_svt-l_uperhead_8x2_512x512_160k_ade20k.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/twins/twins_svt-l_uperhead_8x2_512x512_160k_ade20k/twins_svt-l_uperhead_8x2_512x512_160k_ade20k_20211130_141005-3e2cae61.pth
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