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metafile.yml
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Collections:
- Name: Weight Standardization
Metadata:
Training Data: COCO
Training Techniques:
- SGD with Momentum
- Weight Decay
Training Resources: 8x V100 GPUs
Architecture:
- Group Normalization
- Weight Standardization
Paper:
URL: https://arxiv.org/abs/1903.10520
Title: 'Weight Standardization'
README: configs/gn+ws/README.md
Code:
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/configs/gn%2Bws/mask-rcnn_r50_fpn_gn-ws-all_2x_coco.py
Version: v2.0.0
Models:
- Name: faster-rcnn_r50_fpn_gn_ws-all_1x_coco
In Collection: Weight Standardization
Config: configs/gn%2Bws/faster-rcnn_r50_fpn_gn-ws-all_1x_coco.py
Metadata:
Training Memory (GB): 5.9
inference time (ms/im):
- value: 85.47
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 39.7
Weights: https://download.openmmlab.com/mmdetection/v2.0/gn%2Bws/faster_rcnn_r50_fpn_gn_ws-all_1x_coco/faster_rcnn_r50_fpn_gn_ws-all_1x_coco_20200130-613d9fe2.pth
- Name: faster-rcnn_r101_fpn_gn-ws-all_1x_coco
In Collection: Weight Standardization
Config: configs/gn%2Bws/faster-rcnn_r101_fpn_gn-ws-all_1x_coco.py
Metadata:
Training Memory (GB): 8.9
inference time (ms/im):
- value: 111.11
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 41.7
Weights: https://download.openmmlab.com/mmdetection/v2.0/gn%2Bws/faster_rcnn_r101_fpn_gn_ws-all_1x_coco/faster_rcnn_r101_fpn_gn_ws-all_1x_coco_20200205-a93b0d75.pth
- Name: faster-rcnn_x50-32x4d_fpn_gn-ws-all_1x_coco
In Collection: Weight Standardization
Config: configs/gn%2Bws/faster-rcnn_x50-32x4d_fpn_gn-ws-all_1x_coco.py
Metadata:
Training Memory (GB): 7.0
inference time (ms/im):
- value: 97.09
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 40.7
Weights: https://download.openmmlab.com/mmdetection/v2.0/gn%2Bws/faster_rcnn_x50_32x4d_fpn_gn_ws-all_1x_coco/faster_rcnn_x50_32x4d_fpn_gn_ws-all_1x_coco_20200203-839c5d9d.pth
- Name: faster-rcnn_x101-32x4d_fpn_gn-ws-all_1x_coco
In Collection: Weight Standardization
Config: configs/gn%2Bws/faster-rcnn_x101-32x4d_fpn_gn-ws-all_1x_coco.py
Metadata:
Training Memory (GB): 10.8
inference time (ms/im):
- value: 131.58
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 42.1
Weights: https://download.openmmlab.com/mmdetection/v2.0/gn%2Bws/faster_rcnn_x101_32x4d_fpn_gn_ws-all_1x_coco/faster_rcnn_x101_32x4d_fpn_gn_ws-all_1x_coco_20200212-27da1bc2.pth
- Name: mask-rcnn_r50_fpn_gn_ws-all_2x_coco
In Collection: Weight Standardization
Config: configs/gn%2Bws/mask-rcnn_r50_fpn_gn-ws-all_2x_coco.py
Metadata:
Training Memory (GB): 7.3
inference time (ms/im):
- value: 95.24
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 24
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 40.6
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 36.6
Weights: https://download.openmmlab.com/mmdetection/v2.0/gn%2Bws/mask_rcnn_r50_fpn_gn_ws-all_2x_coco/mask_rcnn_r50_fpn_gn_ws-all_2x_coco_20200226-16acb762.pth
- Name: mask-rcnn_r101_fpn_gn-ws-all_2x_coco
In Collection: Weight Standardization
Config: configs/gn%2Bws/mask-rcnn_r101_fpn_gn-ws-all_2x_coco.py
Metadata:
Training Memory (GB): 10.3
inference time (ms/im):
- value: 116.28
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 24
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 42.0
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 37.7
Weights: https://download.openmmlab.com/mmdetection/v2.0/gn%2Bws/mask_rcnn_r101_fpn_gn_ws-all_2x_coco/mask_rcnn_r101_fpn_gn_ws-all_2x_coco_20200212-ea357cd9.pth
- Name: mask-rcnn_x50-32x4d_fpn_gn-ws-all_2x_coco
In Collection: Weight Standardization
Config: configs/gn%2Bws/mask-rcnn_x50-32x4d_fpn_gn-ws-all_2x_coco.py
Metadata:
Training Memory (GB): 8.4
inference time (ms/im):
- value: 107.53
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 24
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 41.1
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 37.0
Weights: https://download.openmmlab.com/mmdetection/v2.0/gn%2Bws/mask_rcnn_x50_32x4d_fpn_gn_ws-all_2x_coco/mask_rcnn_x50_32x4d_fpn_gn_ws-all_2x_coco_20200216-649fdb6f.pth
- Name: mask-rcnn_x101-32x4d_fpn_gn-ws-all_2x_coco
In Collection: Weight Standardization
Config: configs/gn%2Bws/mask-rcnn_x101-32x4d_fpn_gn-ws-all_2x_coco.py
Metadata:
Training Memory (GB): 12.2
inference time (ms/im):
- value: 140.85
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 24
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 42.1
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 37.9
Weights: https://download.openmmlab.com/mmdetection/v2.0/gn%2Bws/mask_rcnn_x101_32x4d_fpn_gn_ws-all_2x_coco/mask_rcnn_x101_32x4d_fpn_gn_ws-all_2x_coco_20200319-33fb95b5.pth
- Name: mask-rcnn_r50_fpn_gn_ws-all_20_23_24e_coco
In Collection: Weight Standardization
Config: configs/gn%2Bws/mask-rcnn_r50_fpn_gn-ws-all_20-23-24e_coco.py
Metadata:
Training Memory (GB): 7.3
Epochs: 24
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 41.1
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 37.1
Weights: https://download.openmmlab.com/mmdetection/v2.0/gn%2Bws/mask_rcnn_r50_fpn_gn_ws-all_20_23_24e_coco/mask_rcnn_r50_fpn_gn_ws-all_20_23_24e_coco_20200213-487d1283.pth
- Name: mask-rcnn_r101_fpn_gn-ws-all_20-23-24e_coco
In Collection: Weight Standardization
Config: configs/gn%2Bws/mask-rcnn_r101_fpn_gn-ws-all_20-23-24e_coco.py
Metadata:
Training Memory (GB): 10.3
Epochs: 24
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 43.1
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 38.6
Weights: https://download.openmmlab.com/mmdetection/v2.0/gn%2Bws/mask_rcnn_r101_fpn_gn_ws-all_20_23_24e_coco/mask_rcnn_r101_fpn_gn_ws-all_20_23_24e_coco_20200213-57b5a50f.pth
- Name: mask-rcnn_x50-32x4d_fpn_gn-ws-all_20-23-24e_coco
In Collection: Weight Standardization
Config: configs/gn%2Bws/mask-rcnn_x50-32x4d_fpn_gn-ws-all_20-23-24e_coco.py
Metadata:
Training Memory (GB): 8.4
Epochs: 24
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 42.1
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 38.0
Weights: https://download.openmmlab.com/mmdetection/v2.0/gn%2Bws/mask_rcnn_x50_32x4d_fpn_gn_ws-all_20_23_24e_coco/mask_rcnn_x50_32x4d_fpn_gn_ws-all_20_23_24e_coco_20200226-969bcb2c.pth
- Name: mask-rcnn_x101-32x4d_fpn_gn-ws-all_20-23-24e_coco
In Collection: Weight Standardization
Config: configs/gn%2Bws/mask-rcnn_x101-32x4d_fpn_gn-ws-all_20-23-24e_coco.py
Metadata:
Training Memory (GB): 12.2
Epochs: 24
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 42.7
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 38.5
Weights: https://download.openmmlab.com/mmdetection/v2.0/gn%2Bws/mask_rcnn_x101_32x4d_fpn_gn_ws-all_20_23_24e_coco/mask_rcnn_x101_32x4d_fpn_gn_ws-all_20_23_24e_coco_20200316-e6cd35ef.pth