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280 lines
9.0 KiB
YAML
280 lines
9.0 KiB
YAML
Collections:
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- Name: twins
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Metadata:
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Training Data:
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- ADE20K
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Paper:
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URL: https://arxiv.org/pdf/2104.13840.pdf
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Title: 'Twins: Revisiting the Design of Spatial Attention in Vision Transformers'
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README: configs/twins/README.md
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Code:
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URL: https://github.com/open-mmlab/mmsegmentation/blob/v0.20.0/mmseg/models/backbones/twins.py#L352
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Version: v0.20.0
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Converted From:
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Code: https://github.com/Meituan-AutoML/Twins
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Models:
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- Name: twins_pcpvt-s_fpn_fpnhead_8x4_512x512_80k_ade20k
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In Collection: twins
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Metadata:
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backbone: PCPVT-S
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crop size: (512,512)
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lr schd: 80000
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inference time (ms/im):
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- value: 36.83
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hardware: V100
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backend: PyTorch
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batch size: 1
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mode: FP32
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resolution: (512,512)
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Training Memory (GB): 6.6
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Results:
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- Task: Semantic Segmentation
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Dataset: ADE20K
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Metrics:
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mIoU: 43.26
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mIoU(ms+flip): 44.11
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Config: configs/twins/twins_pcpvt-s_fpn_fpnhead_8x4_512x512_80k_ade20k.py
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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
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- Name: twins_pcpvt-s_uperhead_8x4_512x512_160k_ade20k
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In Collection: twins
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Metadata:
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backbone: PCPVT-S
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crop size: (512,512)
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lr schd: 160000
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inference time (ms/im):
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- value: 70.22
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hardware: V100
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backend: PyTorch
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batch size: 1
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mode: FP32
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resolution: (512,512)
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Training Memory (GB): 9.67
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Results:
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- Task: Semantic Segmentation
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Dataset: ADE20K
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Metrics:
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mIoU: 46.04
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mIoU(ms+flip): 46.92
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Config: configs/twins/twins_pcpvt-s_uperhead_8x4_512x512_160k_ade20k.py
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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
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- Name: twins_pcpvt-b_fpn_fpnhead_8x4_512x512_80k_ade20k
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In Collection: twins
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Metadata:
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backbone: PCPVT-B
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crop size: (512,512)
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lr schd: 80000
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inference time (ms/im):
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- value: 50.84
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hardware: V100
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backend: PyTorch
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batch size: 1
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mode: FP32
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resolution: (512,512)
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Training Memory (GB): 8.41
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Results:
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- Task: Semantic Segmentation
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Dataset: ADE20K
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Metrics:
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mIoU: 45.66
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mIoU(ms+flip): 46.48
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Config: configs/twins/twins_pcpvt-b_fpn_fpnhead_8x4_512x512_80k_ade20k.py
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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
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- Name: twins_pcpvt-b_uperhead_8x2_512x512_160k_ade20k
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In Collection: twins
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Metadata:
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backbone: PCPVT-B
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crop size: (512,512)
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lr schd: 160000
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inference time (ms/im):
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- value: 83.06
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hardware: V100
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backend: PyTorch
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batch size: 1
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mode: FP32
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resolution: (512,512)
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Training Memory (GB): 6.46
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Results:
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- Task: Semantic Segmentation
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Dataset: ADE20K
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Metrics:
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mIoU: 47.91
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mIoU(ms+flip): 48.64
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Config: configs/twins/twins_pcpvt-b_uperhead_8x2_512x512_160k_ade20k.py
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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
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- Name: twins_pcpvt-l_fpn_fpnhead_8x4_512x512_80k_ade20k
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In Collection: twins
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Metadata:
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backbone: PCPVT-L
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crop size: (512,512)
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lr schd: 80000
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inference time (ms/im):
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- value: 69.83
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hardware: V100
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backend: PyTorch
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batch size: 1
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mode: FP32
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resolution: (512,512)
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Training Memory (GB): 10.78
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Results:
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- Task: Semantic Segmentation
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Dataset: ADE20K
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Metrics:
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mIoU: 45.94
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mIoU(ms+flip): 46.7
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Config: configs/twins/twins_pcpvt-l_fpn_fpnhead_8x4_512x512_80k_ade20k.py
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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
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- Name: twins_pcpvt-l_uperhead_8x2_512x512_160k_ade20k
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In Collection: twins
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Metadata:
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backbone: PCPVT-L
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crop size: (512,512)
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lr schd: 160000
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inference time (ms/im):
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- value: 93.46
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hardware: V100
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backend: PyTorch
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batch size: 1
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mode: FP32
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resolution: (512,512)
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Training Memory (GB): 7.82
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Results:
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- Task: Semantic Segmentation
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Dataset: ADE20K
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Metrics:
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mIoU: 49.35
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mIoU(ms+flip): 50.08
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Config: configs/twins/twins_pcpvt-l_uperhead_8x2_512x512_160k_ade20k.py
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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
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- Name: twins_svt-s_fpn_fpnhead_8x4_512x512_80k_ade20k
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In Collection: twins
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Metadata:
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backbone: SVT-S
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crop size: (512,512)
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lr schd: 80000
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inference time (ms/im):
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- value: 33.57
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hardware: V100
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backend: PyTorch
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batch size: 1
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mode: FP32
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resolution: (512,512)
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Training Memory (GB): 5.8
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Results:
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- Task: Semantic Segmentation
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Dataset: ADE20K
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Metrics:
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mIoU: 44.47
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mIoU(ms+flip): 45.42
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Config: configs/twins/twins_svt-s_fpn_fpnhead_8x4_512x512_80k_ade20k.py
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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
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- Name: twins_svt-s_uperhead_8x2_512x512_160k_ade20k
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In Collection: twins
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Metadata:
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backbone: SVT-S
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crop size: (512,512)
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lr schd: 160000
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inference time (ms/im):
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- value: 66.27
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hardware: V100
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backend: PyTorch
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batch size: 1
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mode: FP32
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resolution: (512,512)
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Training Memory (GB): 4.93
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Results:
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- Task: Semantic Segmentation
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Dataset: ADE20K
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Metrics:
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mIoU: 46.08
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mIoU(ms+flip): 46.96
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Config: configs/twins/twins_svt-s_uperhead_8x2_512x512_160k_ade20k.py
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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
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- Name: twins_svt-b_fpn_fpnhead_8x4_512x512_80k_ade20k
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In Collection: twins
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Metadata:
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backbone: SVT-B
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crop size: (512,512)
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lr schd: 80000
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inference time (ms/im):
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- value: 47.39
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hardware: V100
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backend: PyTorch
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batch size: 1
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mode: FP32
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resolution: (512,512)
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Training Memory (GB): 8.75
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Results:
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- Task: Semantic Segmentation
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Dataset: ADE20K
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Metrics:
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mIoU: 46.77
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mIoU(ms+flip): 47.47
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Config: configs/twins/twins_svt-b_fpn_fpnhead_8x4_512x512_80k_ade20k.py
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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
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- Name: twins_svt-b_uperhead_8x2_512x512_160k_ade20k
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In Collection: twins
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Metadata:
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backbone: SVT-B
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crop size: (512,512)
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lr schd: 160000
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inference time (ms/im):
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- value: 78.99
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hardware: V100
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backend: PyTorch
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batch size: 1
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mode: FP32
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resolution: (512,512)
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Training Memory (GB): 6.77
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Results:
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- Task: Semantic Segmentation
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Dataset: ADE20K
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Metrics:
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mIoU: 48.04
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mIoU(ms+flip): 48.87
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Config: configs/twins/twins_svt-b_uperhead_8x2_512x512_160k_ade20k.py
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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
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- Name: twins_svt-l_fpn_fpnhead_8x4_512x512_80k_ade20k
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In Collection: twins
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Metadata:
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backbone: SVT-L
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crop size: (512,512)
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lr schd: 80000
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inference time (ms/im):
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- value: 56.18
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hardware: V100
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backend: PyTorch
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batch size: 1
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mode: FP32
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resolution: (512,512)
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Training Memory (GB): 11.2
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Results:
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- Task: Semantic Segmentation
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Dataset: ADE20K
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Metrics:
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mIoU: 46.55
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mIoU(ms+flip): 47.74
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Config: configs/twins/twins_svt-l_fpn_fpnhead_8x4_512x512_80k_ade20k.py
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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
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- Name: twins_svt-l_uperhead_8x2_512x512_160k_ade20k
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In Collection: twins
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Metadata:
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backbone: SVT-L
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crop size: (512,512)
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lr schd: 160000
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inference time (ms/im):
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- value: 93.2
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hardware: V100
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backend: PyTorch
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batch size: 1
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mode: FP32
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resolution: (512,512)
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Training Memory (GB): 8.41
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Results:
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- Task: Semantic Segmentation
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Dataset: ADE20K
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Metrics:
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mIoU: 49.65
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mIoU(ms+flip): 50.63
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Config: configs/twins/twins_svt-l_uperhead_8x2_512x512_160k_ade20k.py
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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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