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- Collections:
- - Name: FP16
- Metadata:
- Training Data: COCO
- Training Techniques:
- - Mixed Precision Training
- Training Resources: 8x V100 GPUs
- Paper:
- URL: https://arxiv.org/abs/1710.03740
- Title: 'Mixed Precision Training'
- README: configs/fp16/README.md
- Code:
- URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/core/fp16/hooks.py#L11
- Version: v2.0.0
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- Models:
- - Name: faster_rcnn_r50_fpn_fp16_1x_coco
- In Collection: FP16
- Config: configs/fp16/faster_rcnn_r50_fpn_fp16_1x_coco.py
- Metadata:
- Training Memory (GB): 3.4
- inference time (ms/im):
- - value: 34.72
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP16
- resolution: (800, 1333)
- Epochs: 12
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 37.5
- Weights: https://download.openmmlab.com/mmdetection/v2.0/fp16/faster_rcnn_r50_fpn_fp16_1x_coco/faster_rcnn_r50_fpn_fp16_1x_coco_20200204-d4dc1471.pth
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- - Name: mask_rcnn_r50_fpn_fp16_1x_coco
- In Collection: FP16
- Config: configs/fp16/mask_rcnn_r50_fpn_fp16_1x_coco.py
- Metadata:
- Training Memory (GB): 3.6
- inference time (ms/im):
- - value: 41.49
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP16
- resolution: (800, 1333)
- Epochs: 12
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 38.1
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 34.7
- Weights: https://download.openmmlab.com/mmdetection/v2.0/fp16/mask_rcnn_r50_fpn_fp16_1x_coco/mask_rcnn_r50_fpn_fp16_1x_coco_20200205-59faf7e4.pth
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- - Name: mask_rcnn_r50_fpn_fp16_dconv_c3-c5_1x_coco
- In Collection: FP16
- Config: configs/fp16/mask_rcnn_r50_fpn_fp16_dconv_c3-c5_1x_coco.py
- Metadata:
- Training Memory (GB): 3.0
- Epochs: 12
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 41.9
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 37.5
- Weights: https://download.openmmlab.com/mmdetection/v2.0/fp16/mask_rcnn_r50_fpn_fp16_dconv_c3-c5_1x_coco/mask_rcnn_r50_fpn_fp16_dconv_c3-c5_1x_coco_20210520_180247-c06429d2.pth
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- - Name: mask_rcnn_r50_fpn_fp16_mdconv_c3-c5_1x_coco
- In Collection: FP16
- Config: configs/fp16/mask_rcnn_r50_fpn_fp16_mdconv_c3-c5_1x_coco.py
- Metadata:
- Training Memory (GB): 3.1
- Epochs: 12
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 42.0
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 37.6
- Weights: https://download.openmmlab.com/mmdetection/v2.0/fp16/mask_rcnn_r50_fpn_fp16_mdconv_c3-c5_1x_coco/mask_rcnn_r50_fpn_fp16_mdconv_c3-c5_1x_coco_20210520_180434-cf8fefa5.pth
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- - Name: retinanet_r50_fpn_fp16_1x_coco
- In Collection: FP16
- Config: configs/fp16/retinanet_r50_fpn_fp16_1x_coco.py
- Metadata:
- Training Memory (GB): 2.8
- inference time (ms/im):
- - value: 31.65
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP16
- resolution: (800, 1333)
- Epochs: 12
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 36.4
- Weights: https://download.openmmlab.com/mmdetection/v2.0/fp16/retinanet_r50_fpn_fp16_1x_coco/retinanet_r50_fpn_fp16_1x_coco_20200702-0dbfb212.pth
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