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mmsegmentation/configs/mask2former/metafile.yaml

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Collections:
- Name: Mask2Former
License: Apache License 2.0
Metadata:
Training Data:
- Usage
- Cityscapes
- ADE20K
Paper:
Title: Masked-attention Mask Transformer for Universal Image Segmentation
URL: https://arxiv.org/abs/2112.01527
README: configs/mask2former/README.md
Frameworks:
- PyTorch
Models:
- Name: mask2former_r50_8xb2-90k_cityscapes-512x1024
In Collection: Mask2Former
Results:
Task: Semantic Segmentation
Dataset: Cityscapes
Metrics:
mIoU: 80.44
Config: configs/mask2former/mask2former_r50_8xb2-90k_cityscapes-512x1024.py
Metadata:
Training Data: Cityscapes
Batch Size: 16
Architecture:
- R-50-D32
- Mask2Former
Training Resources: 8x A100 GPUS
Memory (GB): 5.67
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_r50_8xb2-90k_cityscapes-512x1024/mask2former_r50_8xb2-90k_cityscapes-512x1024_20221202_140802-ffd9d750.pth
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_r50_8xb2-90k_cityscapes-512x1024/mask2former_r50_8xb2-90k_cityscapes-512x1024_20221202_140802.json
Paper:
Title: Masked-attention Mask Transformer for Universal Image Segmentation
URL: https://arxiv.org/abs/2112.01527
Code: https://github.com/open-mmlab/mmdetection/blob/3.x/mmdet/models/dense_heads/mask2former_head.py
Framework: PyTorch
- Name: mask2former_r101_8xb2-90k_cityscapes-512x1024
In Collection: Mask2Former
Results:
Task: Semantic Segmentation
Dataset: Cityscapes
Metrics:
mIoU: 80.8
Config: configs/mask2former/mask2former_r101_8xb2-90k_cityscapes-512x1024.py
Metadata:
Training Data: Cityscapes
Batch Size: 16
Architecture:
- R-101-D32
- Mask2Former
Training Resources: 8x A100 GPUS
Memory (GB): 6.81
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_r101_8xb2-90k_cityscapes-512x1024/mask2former_r101_8xb2-90k_cityscapes-512x1024_20221130_031628-43e68666.pth
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_r101_8xb2-90k_cityscapes-512x1024/mask2former_r101_8xb2-90k_cityscapes-512x1024_20221130_031628.json
Paper:
Title: Masked-attention Mask Transformer for Universal Image Segmentation
URL: https://arxiv.org/abs/2112.01527
Code: https://github.com/open-mmlab/mmdetection/blob/3.x/mmdet/models/dense_heads/mask2former_head.py
Framework: PyTorch
- Name: mask2former_swin-t_8xb2-90k_cityscapes-512x1024
In Collection: Mask2Former
Results:
Task: Semantic Segmentation
Dataset: Cityscapes
Metrics:
mIoU: 81.71
Config: configs/mask2former/mask2former_swin-t_8xb2-90k_cityscapes-512x1024.py
Metadata:
Training Data: Cityscapes
Batch Size: 16
Architecture:
- Swin-T
- Mask2Former
Training Resources: 8x A100 GPUS
Memory (GB): 6.36
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_swin-t_8xb2-90k_cityscapes-512x1024/mask2former_swin-t_8xb2-90k_cityscapes-512x1024_20221127_144501-36c59341.pth
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_swin-t_8xb2-90k_cityscapes-512x1024/mask2former_swin-t_8xb2-90k_cityscapes-512x1024_20221127_144501.json
Paper:
Title: Masked-attention Mask Transformer for Universal Image Segmentation
URL: https://arxiv.org/abs/2112.01527
Code: https://github.com/open-mmlab/mmdetection/blob/3.x/mmdet/models/dense_heads/mask2former_head.py
Framework: PyTorch
- Name: mask2former_swin-s_8xb2-90k_cityscapes-512x1024
In Collection: Mask2Former
Results:
Task: Semantic Segmentation
Dataset: Cityscapes
Metrics:
mIoU: 82.57
Config: configs/mask2former/mask2former_swin-s_8xb2-90k_cityscapes-512x1024.py
Metadata:
Training Data: Cityscapes
Batch Size: 16
Architecture:
- Swin-S
- Mask2Former
Training Resources: 8x A100 GPUS
Memory (GB): 8.09
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_swin-s_8xb2-90k_cityscapes-512x1024/mask2former_swin-s_8xb2-90k_cityscapes-512x1024_20221127_143802-9ab177f6.pth
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_swin-s_8xb2-90k_cityscapes-512x1024/mask2former_swin-s_8xb2-90k_cityscapes-512x1024_20221127_143802.json
Paper:
Title: Masked-attention Mask Transformer for Universal Image Segmentation
URL: https://arxiv.org/abs/2112.01527
Code: https://github.com/open-mmlab/mmdetection/blob/3.x/mmdet/models/dense_heads/mask2former_head.py
Framework: PyTorch
- Name: mask2former_swin-b-in22k-384x384-pre_8xb2-90k_cityscapes-512x1024
In Collection: Mask2Former
Results:
Task: Semantic Segmentation
Dataset: Cityscapes
Metrics:
mIoU: 83.52
Config: configs/mask2former/mask2former_swin-b-in22k-384x384-pre_8xb2-90k_cityscapes-512x1024.py
Metadata:
Training Data: Cityscapes
Batch Size: 16
Architecture:
- Swin-B
- Mask2Former
Training Resources: 8x A100 GPUS
Memory (GB): 10.89
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_swin-b-in22k-384x384-pre_8xb2-90k_cityscapes-512x1024/mask2former_swin-b-in22k-384x384-pre_8xb2-90k_cityscapes-512x1024_20221203_045030-9a86a225.pth
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_swin-b-in22k-384x384-pre_8xb2-90k_cityscapes-512x1024/mask2former_swin-b-in22k-384x384-pre_8xb2-90k_cityscapes-512x1024_20221203_045030.json
Paper:
Title: Masked-attention Mask Transformer for Universal Image Segmentation
URL: https://arxiv.org/abs/2112.01527
Code: https://github.com/open-mmlab/mmdetection/blob/3.x/mmdet/models/dense_heads/mask2former_head.py
Framework: PyTorch
- Name: mask2former_swin-l-in22k-384x384-pre_8xb2-90k_cityscapes-512x1024
In Collection: Mask2Former
Results:
Task: Semantic Segmentation
Dataset: Cityscapes
Metrics:
mIoU: 83.65
Config: configs/mask2former/mask2former_swin-l-in22k-384x384-pre_8xb2-90k_cityscapes-512x1024.py
Metadata:
Training Data: Cityscapes
Batch Size: 16
Architecture:
- Swin-L
- Mask2Former
Training Resources: 8x A100 GPUS
Memory (GB): 15.83
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_swin-l-in22k-384x384-pre_8xb2-90k_cityscapes-512x1024/mask2former_swin-l-in22k-384x384-pre_8xb2-90k_cityscapes-512x1024_20221202_141901-28ad20f1.pth
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_swin-l-in22k-384x384-pre_8xb2-90k_cityscapes-512x1024/mask2former_swin-l-in22k-384x384-pre_8xb2-90k_cityscapes-512x1024_20221202_141901.json
Paper:
Title: Masked-attention Mask Transformer for Universal Image Segmentation
URL: https://arxiv.org/abs/2112.01527
Code: https://github.com/open-mmlab/mmdetection/blob/3.x/mmdet/models/dense_heads/mask2former_head.py
Framework: PyTorch
- Name: mask2former_r50_8xb2-160k_ade20k-512x512
In Collection: Mask2Former
Results:
Task: Semantic Segmentation
Dataset: ADE20K
Metrics:
mIoU: 47.87
Config: configs/mask2former/mask2former_r50_8xb2-160k_ade20k-512x512.py
Metadata:
Training Data: ADE20K
Batch Size: 16
Architecture:
- R-50-D32
- Mask2Former
Training Resources: 8x A100 GPUS
Memory (GB): 3.31
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_r50_8xb2-160k_ade20k-512x512/mask2former_r50_8xb2-160k_ade20k-512x512_20221204_000055-2d1f55f1.pth
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_r50_8xb2-160k_ade20k-512x512/mask2former_r50_8xb2-160k_ade20k-512x512_20221204_000055.json
Paper:
Title: Masked-attention Mask Transformer for Universal Image Segmentation
URL: https://arxiv.org/abs/2112.01527
Code: https://github.com/open-mmlab/mmdetection/blob/3.x/mmdet/models/dense_heads/mask2former_head.py
Framework: PyTorch
- Name: mask2former_r101_8xb2-160k_ade20k-512x512
In Collection: Mask2Former
Results:
Task: Semantic Segmentation
Dataset: ADE20K
Metrics:
mIoU: 48.6
Config: configs/mask2former/mask2former_r101_8xb2-160k_ade20k-512x512.py
Metadata:
Training Data: ADE20K
Batch Size: 16
Architecture:
- R-101-D32
- Mask2Former
Training Resources: 8x A100 GPUS
Memory (GB): 4.09
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_r101_8xb2-160k_ade20k-512x512/mask2former_r101_8xb2-160k_ade20k-512x512_20221203_233905-b7135890.pth
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_r101_8xb2-160k_ade20k-512x512/mask2former_r101_8xb2-160k_ade20k-512x512_20221203_233905.json
Paper:
Title: Masked-attention Mask Transformer for Universal Image Segmentation
URL: https://arxiv.org/abs/2112.01527
Code: https://github.com/open-mmlab/mmdetection/blob/3.x/mmdet/models/dense_heads/mask2former_head.py
Framework: PyTorch
- Name: mask2former_swin-t_8xb2-160k_ade20k-512x512
In Collection: Mask2Former
Results:
Task: Semantic Segmentation
Dataset: ADE20K
Metrics:
mIoU: 48.66
Config: configs/mask2former/mask2former_swin-t_8xb2-160k_ade20k-512x512.py
Metadata:
Training Data: ADE20K
Batch Size: 16
Architecture:
- Swin-T
- Mask2Former
Training Resources: 8x A100 GPUS
Memory (GB): 3826.0
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_swin-t_8xb2-160k_ade20k-512x512/mask2former_swin-t_8xb2-160k_ade20k-512x512_20221203_234230-7d64e5dd.pth
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_swin-t_8xb2-160k_ade20k-512x512/mask2former_swin-t_8xb2-160k_ade20k-512x512_20221203_234230.json
Paper:
Title: Masked-attention Mask Transformer for Universal Image Segmentation
URL: https://arxiv.org/abs/2112.01527
Code: https://github.com/open-mmlab/mmdetection/blob/3.x/mmdet/models/dense_heads/mask2former_head.py
Framework: PyTorch
- Name: mask2former_swin-s_8xb2-160k_ade20k-512x512
In Collection: Mask2Former
Results:
Task: Semantic Segmentation
Dataset: ADE20K
Metrics:
mIoU: 51.24
Config: configs/mask2former/mask2former_swin-s_8xb2-160k_ade20k-512x512.py
Metadata:
Training Data: ADE20K
Batch Size: 16
Architecture:
- Swin-S
- Mask2Former
Training Resources: 8x A100 GPUS
Memory (GB): 3.74
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_swin-s_8xb2-160k_ade20k-512x512/mask2former_swin-s_8xb2-160k_ade20k-512x512_20221204_143905-e715144e.pth
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_swin-s_8xb2-160k_ade20k-512x512/mask2former_swin-s_8xb2-160k_ade20k-512x512_20221204_143905.json
Paper:
Title: Masked-attention Mask Transformer for Universal Image Segmentation
URL: https://arxiv.org/abs/2112.01527
Code: https://github.com/open-mmlab/mmdetection/blob/3.x/mmdet/models/dense_heads/mask2former_head.py
Framework: PyTorch
- Name: mask2former_swin-b-in1k-384x384-pre_8xb2-160k_ade20k-640x640
In Collection: Mask2Former
Results:
Task: Semantic Segmentation
Dataset: ADE20K
Metrics:
mIoU: 52.44
Config: configs/mask2former/mask2former_swin-b-in1k-384x384-pre_8xb2-160k_ade20k-640x640.py
Metadata:
Training Data: ADE20K
Batch Size: 16
Architecture:
- Swin-B
- Mask2Former
Training Resources: 8x A100 GPUS
Memory (GB): 5.66
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_swin-b-in1k-384x384-pre_8xb2-160k_ade20k-640x640/mask2former_swin-b-in1k-384x384-pre_8xb2-160k_ade20k-640x640_20221129_125118-a4a086d2.pth
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_swin-b-in1k-384x384-pre_8xb2-160k_ade20k-640x640/mask2former_swin-b-in1k-384x384-pre_8xb2-160k_ade20k-640x640_20221129_125118.json
Paper:
Title: Masked-attention Mask Transformer for Universal Image Segmentation
URL: https://arxiv.org/abs/2112.01527
Code: https://github.com/open-mmlab/mmdetection/blob/3.x/mmdet/models/dense_heads/mask2former_head.py
Framework: PyTorch
- Name: mask2former_swin-b-in22k-384x384-pre_8xb2-160k_ade20k-640x640
In Collection: Mask2Former
Results:
Task: Semantic Segmentation
Dataset: ADE20K
Metrics:
mIoU: 53.9
Config: configs/mask2former/mask2former_swin-b-in22k-384x384-pre_8xb2-160k_ade20k-640x640.py
Metadata:
Training Data: ADE20K
Batch Size: 16
Architecture:
- Swin-B
- Mask2Former
Training Resources: 8x A100 GPUS
Memory (GB): 5.66
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_swin-b-in22k-384x384-pre_8xb2-160k_ade20k-640x640/mask2former_swin-b-in22k-384x384-pre_8xb2-160k_ade20k-640x640_20221203_235230-7ec0f569.pth
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_swin-b-in22k-384x384-pre_8xb2-160k_ade20k-640x640/mask2former_swin-b-in22k-384x384-pre_8xb2-160k_ade20k-640x640_20221203_235230.json
Paper:
Title: Masked-attention Mask Transformer for Universal Image Segmentation
URL: https://arxiv.org/abs/2112.01527
Code: https://github.com/open-mmlab/mmdetection/blob/3.x/mmdet/models/dense_heads/mask2former_head.py
Framework: PyTorch
- Name: mask2former_swin-l-in22k-384x384-pre_8xb2-160k_ade20k-640x640
In Collection: Mask2Former
Results:
Task: Semantic Segmentation
Dataset: ADE20K
Metrics:
mIoU: 56.01
Config: configs/mask2former/mask2former_swin-l-in22k-384x384-pre_8xb2-160k_ade20k-640x640.py
Metadata:
Training Data: ADE20K
Batch Size: 16
Architecture:
- Swin-L
- Mask2Former
Training Resources: 8x A100 GPUS
Memory (GB): 8.86
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_swin-l-in22k-384x384-pre_8xb2-160k_ade20k-640x640/mask2former_swin-l-in22k-384x384-pre_8xb2-160k_ade20k-640x640_20221203_235933-7120c214.pth
Training log: https://download.openmmlab.com/mmsegmentation/v0.5/mask2former/mask2former_swin-l-in22k-384x384-pre_8xb2-160k_ade20k-640x640/mask2former_swin-l-in22k-384x384-pre_8xb2-160k_ade20k-640x640_20221203_235933.json
Paper:
Title: Masked-attention Mask Transformer for Universal Image Segmentation
URL: https://arxiv.org/abs/2112.01527
Code: https://github.com/open-mmlab/mmdetection/blob/3.x/mmdet/models/dense_heads/mask2former_head.py
Framework: PyTorch
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