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- Collections:
- - Name: Generalized Focal Loss
- Metadata:
- Training Data: COCO
- Training Techniques:
- - SGD with Momentum
- - Weight Decay
- Training Resources: 8x V100 GPUs
- Architecture:
- - Generalized Focal Loss
- - FPN
- - ResNet
- Paper:
- URL: https://arxiv.org/abs/2006.04388
- Title: 'Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection'
- README: configs/gfl/README.md
- Code:
- URL: https://github.com/open-mmlab/mmdetection/blob/v2.2.0/mmdet/models/detectors/gfl.py#L6
- Version: v2.2.0
- Models:
- - Name: gfl_r50_fpn_1x_coco
- In Collection: Generalized Focal Loss
- Config: configs/gfl/gfl_r50_fpn_1x_coco.py
- Metadata:
- inference time (ms/im):
- - value: 51.28
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 12
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 40.2
- Weights: https://download.openmmlab.com/mmdetection/v2.0/gfl/gfl_r50_fpn_1x_coco/gfl_r50_fpn_1x_coco_20200629_121244-25944287.pth
- - Name: gfl_r50_fpn_ms-2x_coco
- In Collection: Generalized Focal Loss
- Config: configs/gfl/gfl_r50_fpn_ms-2x_coco.py
- Metadata:
- inference time (ms/im):
- - value: 51.28
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 24
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 42.9
- Weights: https://download.openmmlab.com/mmdetection/v2.0/gfl/gfl_r50_fpn_mstrain_2x_coco/gfl_r50_fpn_mstrain_2x_coco_20200629_213802-37bb1edc.pth
- - Name: gfl_r101_fpn_ms-2x_coco
- In Collection: Generalized Focal Loss
- Config: configs/gfl/gfl_r101_fpn_ms-2x_coco.py
- Metadata:
- inference time (ms/im):
- - value: 68.03
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 24
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 44.7
- Weights: https://download.openmmlab.com/mmdetection/v2.0/gfl/gfl_r101_fpn_mstrain_2x_coco/gfl_r101_fpn_mstrain_2x_coco_20200629_200126-dd12f847.pth
- - Name: gfl_r101-dconv-c3-c5_fpn_ms-2x_coco
- In Collection: Generalized Focal Loss
- Config: configs/gfl/gfl_r101-dconv-c3-c5_fpn_ms-2x_coco.py
- Metadata:
- inference time (ms/im):
- - value: 77.52
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 24
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 47.1
- Weights: https://download.openmmlab.com/mmdetection/v2.0/gfl/gfl_r101_fpn_dconv_c3-c5_mstrain_2x_coco/gfl_r101_fpn_dconv_c3-c5_mstrain_2x_coco_20200630_102002-134b07df.pth
- - Name: gfl_x101-32x4d_fpn_ms-2x_coco
- In Collection: Generalized Focal Loss
- Config: configs/gfl/gfl_x101-32x4d_fpn_ms-2x_coco.py
- Metadata:
- inference time (ms/im):
- - value: 82.64
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 24
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 45.9
- Weights: https://download.openmmlab.com/mmdetection/v2.0/gfl/gfl_x101_32x4d_fpn_mstrain_2x_coco/gfl_x101_32x4d_fpn_mstrain_2x_coco_20200630_102002-50c1ffdb.pth
- - Name: gfl_x101-32x4d-dconv-c4-c5_fpn_ms-2x_coco
- In Collection: Generalized Focal Loss
- Config: configs/gfl/gfl_x101-32x4d-dconv-c4-c5_fpn_ms-2x_coco.py
- Metadata:
- inference time (ms/im):
- - value: 93.46
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 24
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 48.1
- Weights: https://download.openmmlab.com/mmdetection/v2.0/gfl/gfl_x101_32x4d_fpn_dconv_c4-c5_mstrain_2x_coco/gfl_x101_32x4d_fpn_dconv_c4-c5_mstrain_2x_coco_20200630_102002-14a2bf25.pth
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