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metafile.yml
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Models:
- Name: mask_rcnn_swin-s-p4-w7_fpn_fp16_ms-crop-3x_coco
In Collection: Mask R-CNN
Config: configs/swin/mask_rcnn_swin-s-p4-w7_fpn_fp16_ms-crop-3x_coco.py
Metadata:
Training Memory (GB): 11.9
Epochs: 36
Training Data: COCO
Training Techniques:
- AdamW
Training Resources: 8x V100 GPUs
Architecture:
- Swin Transformer
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 48.2
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 43.2
Weights: https://download.openmmlab.com/mmdetection/v2.0/swin/mask_rcnn_swin-s-p4-w7_fpn_fp16_ms-crop-3x_coco/mask_rcnn_swin-s-p4-w7_fpn_fp16_ms-crop-3x_coco_20210903_104808-b92c91f1.pth
Paper:
URL: https://arxiv.org/abs/2107.08430
Title: 'Swin Transformer: Hierarchical Vision Transformer using Shifted Windows'
README: configs/swin/README.md
Code:
URL: https://github.com/open-mmlab/mmdetection/blob/v2.16.0/mmdet/models/backbones/swin.py#L465
Version: v2.16.0
- Name: mask_rcnn_swin-t-p4-w7_fpn_ms-crop-3x_coco
In Collection: Mask R-CNN
Config: configs/swin/mask_rcnn_swin-t-p4-w7_fpn_ms-crop-3x_coco.py
Metadata:
Training Memory (GB): 10.2
Epochs: 36
Training Data: COCO
Training Techniques:
- AdamW
Training Resources: 8x V100 GPUs
Architecture:
- Swin Transformer
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 46.0
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 41.6
Weights: https://download.openmmlab.com/mmdetection/v2.0/swin/mask_rcnn_swin-t-p4-w7_fpn_ms-crop-3x_coco/mask_rcnn_swin-t-p4-w7_fpn_ms-crop-3x_coco_20210906_131725-bacf6f7b.pth
Paper:
URL: https://arxiv.org/abs/2107.08430
Title: 'Swin Transformer: Hierarchical Vision Transformer using Shifted Windows'
README: configs/swin/README.md
Code:
URL: https://github.com/open-mmlab/mmdetection/blob/v2.16.0/mmdet/models/backbones/swin.py#L465
Version: v2.16.0
- Name: mask_rcnn_swin-t-p4-w7_fpn_1x_coco
In Collection: Mask R-CNN
Config: configs/swin/mask_rcnn_swin-t-p4-w7_fpn_1x_coco.py
Metadata:
Training Memory (GB): 7.6
Epochs: 12
Training Data: COCO
Training Techniques:
- AdamW
Training Resources: 8x V100 GPUs
Architecture:
- Swin Transformer
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 42.7
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 39.3
Weights: https://download.openmmlab.com/mmdetection/v2.0/swin/mask_rcnn_swin-t-p4-w7_fpn_1x_coco/mask_rcnn_swin-t-p4-w7_fpn_1x_coco_20210902_120937-9d6b7cfa.pth
Paper:
URL: https://arxiv.org/abs/2107.08430
Title: 'Swin Transformer: Hierarchical Vision Transformer using Shifted Windows'
README: configs/swin/README.md
Code:
URL: https://github.com/open-mmlab/mmdetection/blob/v2.16.0/mmdet/models/backbones/swin.py#L465
Version: v2.16.0
- Name: mask_rcnn_swin-t-p4-w7_fpn_fp16_ms-crop-3x_coco
In Collection: Mask R-CNN
Config: configs/swin/mask_rcnn_swin-t-p4-w7_fpn_fp16_ms-crop-3x_coco.py
Metadata:
Training Memory (GB): 7.8
Epochs: 36
Training Data: COCO
Training Techniques:
- AdamW
Training Resources: 8x V100 GPUs
Architecture:
- Swin Transformer
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 46.0
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 41.7
Weights: https://download.openmmlab.com/mmdetection/v2.0/swin/mask_rcnn_swin-t-p4-w7_fpn_fp16_ms-crop-3x_coco/mask_rcnn_swin-t-p4-w7_fpn_fp16_ms-crop-3x_coco_20210908_165006-90a4008c.pth
Paper:
URL: https://arxiv.org/abs/2107.08430
Title: 'Swin Transformer: Hierarchical Vision Transformer using Shifted Windows'
README: configs/swin/README.md
Code:
URL: https://github.com/open-mmlab/mmdetection/blob/v2.16.0/mmdet/models/backbones/swin.py#L465
Version: v2.16.0