378 lines
14 KiB
YAML
378 lines
14 KiB
YAML
Collections:
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- Name: UNet
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Metadata:
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Training Data:
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- Cityscapes
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- DRIVE
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- STARE
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- CHASE_DB1
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- HRF
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Paper:
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URL: https://arxiv.org/abs/1505.04597
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Title: 'U-Net: Convolutional Networks for Biomedical Image Segmentation'
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README: configs/unet/README.md
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Code:
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URL: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/unet.py#L225
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Version: v0.17.0
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Converted From:
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Code: http://lmb.informatik.uni-freiburg.de/people/ronneber/u-net
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Models:
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- Name: unet-s5-d16_fcn_4xb4-160k_cityscapes-512x1024
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In Collection: UNet
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Metadata:
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backbone: UNet-S5-D16
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crop size: (512,1024)
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lr schd: 160000
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inference time (ms/im):
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- value: 327.87
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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: (512,1024)
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Training Memory (GB): 17.91
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Results:
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- Task: Semantic Segmentation
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Dataset: Cityscapes
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Metrics:
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mIoU: 69.1
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mIoU(ms+flip): 71.05
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Config: configs/unet/unet-s5-d16_fcn_4xb4-160k_cityscapes-512x1024.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/unet/fcn_unet_s5-d16_4x4_512x1024_160k_cityscapes/fcn_unet_s5-d16_4x4_512x1024_160k_cityscapes_20211210_145204-6860854e.pth
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- Name: unet-s5-d16_fcn_4xb4-40k_drive-64x64
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In Collection: UNet
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Metadata:
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backbone: UNet-S5-D16
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crop size: (64,64)
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lr schd: 40000
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Training Memory (GB): 0.68
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Results:
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- Task: Semantic Segmentation
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Dataset: DRIVE
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Metrics:
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Dice: 78.67
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Config: configs/unet/unet-s5-d16_fcn_4xb4-40k_drive-64x64.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/unet/fcn_unet_s5-d16_64x64_40k_drive/fcn_unet_s5-d16_64x64_40k_drive_20201223_191051-5daf6d3b.pth
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- Name: unet-s5-d16_fcn_4xb4-ce-1.0-dice-3.0-40k_drive-64x64
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In Collection: UNet
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Metadata:
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backbone: UNet-S5-D16
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crop size: (64,64)
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lr schd: 40000
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Training Memory (GB): 0.582
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Results:
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- Task: Semantic Segmentation
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Dataset: DRIVE
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Metrics:
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Dice: 79.32
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Config: configs/unet/unet-s5-d16_fcn_4xb4-ce-1.0-dice-3.0-40k_drive-64x64.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/unet/fcn_unet_s5-d16_ce-1.0-dice-3.0_64x64_40k_drive/fcn_unet_s5-d16_ce-1.0-dice-3.0_64x64_40k_drive_20211210_201820-785de5c2.pth
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- Name: unet-s5-d16_pspnet_4xb4-40k_drive-64x64
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In Collection: UNet
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Metadata:
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backbone: UNet-S5-D16
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crop size: (64,64)
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lr schd: 40000
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Training Memory (GB): 0.599
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Results:
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- Task: Semantic Segmentation
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Dataset: DRIVE
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Metrics:
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Dice: 78.62
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Config: configs/unet/unet-s5-d16_pspnet_4xb4-40k_drive-64x64.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/unet/pspnet_unet_s5-d16_64x64_40k_drive/pspnet_unet_s5-d16_64x64_40k_drive_20201227_181818-aac73387.pth
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- Name: unet-s5-d16_pspnet_4xb4-ce-1.0-dice-3.0-40k_drive-64x64
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In Collection: UNet
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Metadata:
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backbone: UNet-S5-D16
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crop size: (64,64)
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lr schd: 40000
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Training Memory (GB): 0.585
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Results:
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- Task: Semantic Segmentation
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Dataset: DRIVE
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Metrics:
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Dice: 79.42
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Config: configs/unet/unet-s5-d16_pspnet_4xb4-ce-1.0-dice-3.0-40k_drive-64x64.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/unet/pspnet_unet_s5-d16_ce-1.0-dice-3.0_64x64_40k_drive/pspnet_unet_s5-d16_ce-1.0-dice-3.0_64x64_40k_drive_20211210_201821-22b3e3ba.pth
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- Name: unet-s5-d16_deeplabv3_4xb4-40k_drive-64x64
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In Collection: UNet
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Metadata:
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backbone: UNet-S5-D16
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crop size: (64,64)
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lr schd: 40000
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Training Memory (GB): 0.596
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Results:
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- Task: Semantic Segmentation
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Dataset: DRIVE
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Metrics:
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Dice: 78.69
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Config: configs/unet/unet-s5-d16_deeplabv3_4xb4-40k_drive-64x64.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/unet/deeplabv3_unet_s5-d16_64x64_40k_drive/deeplabv3_unet_s5-d16_64x64_40k_drive_20201226_094047-0671ff20.pth
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- Name: unet-s5-d16_deeplabv3_4xb4-ce-1.0-dice-3.0-40k_drive-64x64
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In Collection: UNet
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Metadata:
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backbone: UNet-S5-D16
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crop size: (64,64)
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lr schd: 40000
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Training Memory (GB): 0.582
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Results:
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- Task: Semantic Segmentation
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Dataset: DRIVE
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Metrics:
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Dice: 79.56
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Config: configs/unet/unet-s5-d16_deeplabv3_4xb4-ce-1.0-dice-3.0-40k_drive-64x64.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/unet/deeplabv3_unet_s5-d16_ce-1.0-dice-3.0_64x64_40k_drive/deeplabv3_unet_s5-d16_ce-1.0-dice-3.0_64x64_40k_drive_20211210_201825-6bf0efd7.pth
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- Name: unet-s5-d16_fcn_4xb4-40k_stare-128x128
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In Collection: UNet
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Metadata:
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backbone: UNet-S5-D16
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crop size: (128,128)
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lr schd: 40000
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Training Memory (GB): 0.968
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Results:
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- Task: Semantic Segmentation
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Dataset: STARE
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Metrics:
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Dice: 81.02
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Config: configs/unet/unet-s5-d16_fcn_4xb4-40k_stare-128x128.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/unet/fcn_unet_s5-d16_128x128_40k_stare/fcn_unet_s5-d16_128x128_40k_stare_20201223_191051-7d77e78b.pth
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- Name: unet-s5-d16_fcn_4xb4-ce-1.0-dice-3.0-40k_stare-128x128
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In Collection: UNet
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Metadata:
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backbone: UNet-S5-D16
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crop size: (128,128)
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lr schd: 40000
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Training Memory (GB): 0.986
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Results:
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- Task: Semantic Segmentation
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Dataset: STARE
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Metrics:
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Dice: 82.7
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Config: configs/unet/unet-s5-d16_fcn_4xb4-ce-1.0-dice-3.0-40k_stare-128x128.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/unet/fcn_unet_s5-d16_ce-1.0-dice-3.0_128x128_40k_stare/fcn_unet_s5-d16_ce-1.0-dice-3.0_128x128_40k_stare_20211210_201821-f75705a9.pth
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- Name: unet-s5-d16_pspnet_4xb4-40k_stare-128x128
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In Collection: UNet
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Metadata:
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backbone: UNet-S5-D16
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crop size: (128,128)
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lr schd: 40000
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Training Memory (GB): 0.982
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Results:
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- Task: Semantic Segmentation
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Dataset: STARE
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Metrics:
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Dice: 81.22
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Config: configs/unet/unet-s5-d16_pspnet_4xb4-40k_stare-128x128.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/unet/pspnet_unet_s5-d16_128x128_40k_stare/pspnet_unet_s5-d16_128x128_40k_stare_20201227_181818-3c2923c4.pth
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- Name: unet-s5-d16_pspnet_4xb4-ce-1.0-dice-3.0-40k_stare-128x128
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In Collection: UNet
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Metadata:
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backbone: UNet-S5-D16
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crop size: (128,128)
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lr schd: 40000
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Training Memory (GB): 1.028
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Results:
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- Task: Semantic Segmentation
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Dataset: STARE
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Metrics:
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Dice: 82.84
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Config: configs/unet/unet-s5-d16_pspnet_4xb4-ce-1.0-dice-3.0-40k_stare-128x128.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/unet/pspnet_unet_s5-d16_ce-1.0-dice-3.0_128x128_40k_stare/pspnet_unet_s5-d16_ce-1.0-dice-3.0_128x128_40k_stare_20211210_201823-f1063ef7.pth
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- Name: unet-s5-d16_deeplabv3_4xb4-40k_stare-128x128
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In Collection: UNet
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Metadata:
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backbone: UNet-S5-D16
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crop size: (128,128)
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lr schd: 40000
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Training Memory (GB): 0.999
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Results:
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- Task: Semantic Segmentation
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Dataset: STARE
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Metrics:
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Dice: 80.93
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Config: configs/unet/unet-s5-d16_deeplabv3_4xb4-40k_stare-128x128.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/unet/deeplabv3_unet_s5-d16_128x128_40k_stare/deeplabv3_unet_s5-d16_128x128_40k_stare_20201226_094047-93dcb93c.pth
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- Name: unet-s5-d16_deeplabv3_4xb4-ce-1.0-dice-3.0-40k_stare-128x128
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In Collection: UNet
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Metadata:
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backbone: UNet-S5-D16
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crop size: (128,128)
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lr schd: 40000
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Training Memory (GB): 1.01
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Results:
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- Task: Semantic Segmentation
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Dataset: STARE
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Metrics:
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Dice: 82.71
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Config: configs/unet/unet-s5-d16_deeplabv3_4xb4-ce-1.0-dice-3.0-40k_stare-128x128.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/unet/deeplabv3_unet_s5-d16_ce-1.0-dice-3.0_128x128_40k_stare/deeplabv3_unet_s5-d16_ce-1.0-dice-3.0_128x128_40k_stare_20211210_201825-21db614c.pth
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- Name: unet-s5-d16_fcn_4xb4-40k_chase-db1-128x128
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In Collection: UNet
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Metadata:
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backbone: UNet-S5-D16
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crop size: (128,128)
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lr schd: 40000
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Training Memory (GB): 0.968
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Results:
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- Task: Semantic Segmentation
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Dataset: CHASE_DB1
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Metrics:
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Dice: 80.24
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Config: configs/unet/unet-s5-d16_fcn_4xb4-40k_chase-db1-128x128.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/unet/fcn_unet_s5-d16_128x128_40k_chase_db1/fcn_unet_s5-d16_128x128_40k_chase_db1_20201223_191051-11543527.pth
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- Name: unet-s5-d16_fcn_4xb4-ce-1.0-dice-3.0-40k_chase-db1-128x128
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In Collection: UNet
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Metadata:
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backbone: UNet-S5-D16
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crop size: (128,128)
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lr schd: 40000
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Training Memory (GB): 0.986
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Results:
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- Task: Semantic Segmentation
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Dataset: CHASE_DB1
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Metrics:
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Dice: 80.4
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Config: configs/unet/unet-s5-d16_fcn_4xb4-ce-1.0-dice-3.0-40k_chase-db1-128x128.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/unet/fcn_unet_s5-d16_ce-1.0-dice-3.0_128x128_40k_chase-db1/fcn_unet_s5-d16_ce-1.0-dice-3.0_128x128_40k_chase-db1_20211210_201821-1c4eb7cf.pth
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- Name: unet-s5-d16_pspnet_4xb4-40k_chase-db1-128x128
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In Collection: UNet
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Metadata:
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backbone: UNet-S5-D16
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crop size: (128,128)
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lr schd: 40000
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Training Memory (GB): 0.982
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Results:
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- Task: Semantic Segmentation
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Dataset: CHASE_DB1
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Metrics:
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Dice: 80.36
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Config: configs/unet/unet-s5-d16_pspnet_4xb4-40k_chase-db1-128x128.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/unet/pspnet_unet_s5-d16_128x128_40k_chase_db1/pspnet_unet_s5-d16_128x128_40k_chase_db1_20201227_181818-68d4e609.pth
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- Name: unet-s5-d16_pspnet_4xb4-ce-1.0-dice-3.0-40k_chase-db1-128x128
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In Collection: UNet
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Metadata:
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backbone: UNet-S5-D16
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crop size: (128,128)
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lr schd: 40000
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Training Memory (GB): 1.028
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Results:
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- Task: Semantic Segmentation
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Dataset: CHASE_DB1
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Metrics:
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Dice: 80.28
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Config: configs/unet/unet-s5-d16_pspnet_4xb4-ce-1.0-dice-3.0-40k_chase-db1-128x128.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/unet/pspnet_unet_s5-d16_ce-1.0-dice-3.0_128x128_40k_chase-db1/pspnet_unet_s5-d16_ce-1.0-dice-3.0_128x128_40k_chase-db1_20211210_201823-c0802c4d.pth
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- Name: unet_s5-d16_deeplabv3_4xb4-40k_chase-db1-128x128
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In Collection: UNet
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Metadata:
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backbone: UNet-S5-D16
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crop size: (128,128)
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lr schd: 40000
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Training Memory (GB): 0.999
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Results:
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- Task: Semantic Segmentation
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Dataset: CHASE_DB1
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Metrics:
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Dice: 80.47
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Config: configs/unet/unet_s5-d16_deeplabv3_4xb4-40k_chase-db1-128x128.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/unet/deeplabv3_unet_s5-d16_128x128_40k_chase_db1/deeplabv3_unet_s5-d16_128x128_40k_chase_db1_20201226_094047-4c5aefa3.pth
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- Name: unet-s5-d16_deeplabv3_4xb4-ce-1.0-dice-3.0-40k_chase-db1-128x128
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In Collection: UNet
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Metadata:
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backbone: UNet-S5-D16
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crop size: (128,128)
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lr schd: 40000
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Training Memory (GB): 1.01
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Results:
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- Task: Semantic Segmentation
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Dataset: CHASE_DB1
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Metrics:
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Dice: 80.37
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Config: configs/unet/unet-s5-d16_deeplabv3_4xb4-ce-1.0-dice-3.0-40k_chase-db1-128x128.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/unet/deeplabv3_unet_s5-d16_ce-1.0-dice-3.0_128x128_40k_chase-db1/deeplabv3_unet_s5-d16_ce-1.0-dice-3.0_128x128_40k_chase-db1_20211210_201825-4ef29df5.pth
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- Name: unet-s5-d16_fcn_4xb4-40k_hrf-256x256
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In Collection: UNet
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Metadata:
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backbone: UNet-S5-D16
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crop size: (256,256)
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lr schd: 40000
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Training Memory (GB): 2.525
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Results:
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- Task: Semantic Segmentation
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Dataset: HRF
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Metrics:
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Dice: 79.45
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Config: configs/unet/unet-s5-d16_fcn_4xb4-40k_hrf-256x256.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/unet/fcn_unet_s5-d16_256x256_40k_hrf/fcn_unet_s5-d16_256x256_40k_hrf_20201223_173724-d89cf1ed.pth
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- Name: unet-s5-d16_fcn_4xb4-ce-1.0-dice-3.0-40k_hrf-256x256
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In Collection: UNet
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Metadata:
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backbone: UNet-S5-D16
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crop size: (256,256)
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lr schd: 40000
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Training Memory (GB): 2.623
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Results:
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- Task: Semantic Segmentation
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Dataset: HRF
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Metrics:
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Dice: 80.87
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Config: configs/unet/unet-s5-d16_fcn_4xb4-ce-1.0-dice-3.0-40k_hrf-256x256.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/unet/fcn_unet_s5-d16_ce-1.0-dice-3.0_256x256_40k_hrf/fcn_unet_s5-d16_ce-1.0-dice-3.0_256x256_40k_hrf_20211210_201821-c314da8a.pth
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- Name: unet-s5-d16_pspnet_4xb4-40k_hrf-256x256
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In Collection: UNet
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Metadata:
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backbone: UNet-S5-D16
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crop size: (256,256)
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lr schd: 40000
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Training Memory (GB): 2.588
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Results:
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- Task: Semantic Segmentation
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Dataset: HRF
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Metrics:
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Dice: 80.07
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Config: configs/unet/unet-s5-d16_pspnet_4xb4-40k_hrf-256x256.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/unet/pspnet_unet_s5-d16_256x256_40k_hrf/pspnet_unet_s5-d16_256x256_40k_hrf_20201227_181818-fdb7e29b.pth
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- Name: unet-s5-d16_pspnet_4xb4-ce-1.0-dice-3.0-40k_hrf-256x256
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In Collection: UNet
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Metadata:
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backbone: UNet-S5-D16
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crop size: (256,256)
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lr schd: 40000
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Training Memory (GB): 2.798
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Results:
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- Task: Semantic Segmentation
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Dataset: HRF
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Metrics:
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Dice: 80.96
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Config: configs/unet/unet-s5-d16_pspnet_4xb4-ce-1.0-dice-3.0-40k_hrf-256x256.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/unet/pspnet_unet_s5-d16_ce-1.0-dice-3.0_256x256_40k_hrf/pspnet_unet_s5-d16_ce-1.0-dice-3.0_256x256_40k_hrf_20211210_201823-53d492fa.pth
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- Name: unet-s5-d16_deeplabv3_4xb4-40k_hrf-256x256
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In Collection: UNet
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Metadata:
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backbone: UNet-S5-D16
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crop size: (256,256)
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lr schd: 40000
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Training Memory (GB): 2.604
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Results:
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- Task: Semantic Segmentation
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Dataset: HRF
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Metrics:
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Dice: 80.21
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Config: configs/unet/unet-s5-d16_deeplabv3_4xb4-40k_hrf-256x256.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/unet/deeplabv3_unet_s5-d16_256x256_40k_hrf/deeplabv3_unet_s5-d16_256x256_40k_hrf_20201226_094047-3a1fdf85.pth
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- Name: unet-s5-d16_deeplabv3_4xb4-ce-1.0-dice-3.0-40k_hrf-256x256
|
|
In Collection: UNet
|
|
Metadata:
|
|
backbone: UNet-S5-D16
|
|
crop size: (256,256)
|
|
lr schd: 40000
|
|
Training Memory (GB): 2.607
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Results:
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- Task: Semantic Segmentation
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Dataset: HRF
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Metrics:
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Dice: 80.71
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Config: configs/unet/unet-s5-d16_deeplabv3_4xb4-ce-1.0-dice-3.0-40k_hrf-256x256.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/unet/deeplabv3_unet_s5-d16_ce-1.0-dice-3.0_256x256_40k_hrf/deeplabv3_unet_s5-d16_ce-1.0-dice-3.0_256x256_40k_hrf_20211210_202032-59daf7a4.pth
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