metafile.yml
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Collections:
- Name: Libra R-CNN
Metadata:
Training Data: COCO
Training Techniques:
- IoU-Balanced Sampling
- SGD with Momentum
- Weight Decay
Training Resources: 8x V100 GPUs
Architecture:
- Balanced Feature Pyramid
Paper:
URL: https://arxiv.org/abs/1904.02701
Title: 'Libra R-CNN: Towards Balanced Learning for Object Detection'
README: configs/libra_rcnn/README.md
Code:
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/necks/bfp.py#L10
Version: v2.0.0
Models:
- Name: libra_faster_rcnn_r50_fpn_1x_coco
In Collection: Libra R-CNN
Config: configs/libra_rcnn/libra_faster_rcnn_r50_fpn_1x_coco.py
Metadata:
Training Memory (GB): 4.6
inference time (ms/im):
- value: 52.63
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 38.3
Weights: https://download.openmmlab.com/mmdetection/v2.0/libra_rcnn/libra_faster_rcnn_r50_fpn_1x_coco/libra_faster_rcnn_r50_fpn_1x_coco_20200130-3afee3a9.pth
- Name: libra_faster_rcnn_r101_fpn_1x_coco
In Collection: Libra R-CNN
Config: configs/libra_rcnn/libra_faster_rcnn_r101_fpn_1x_coco.py
Metadata:
Training Memory (GB): 6.5
inference time (ms/im):
- value: 69.44
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 40.1
Weights: https://download.openmmlab.com/mmdetection/v2.0/libra_rcnn/libra_faster_rcnn_r101_fpn_1x_coco/libra_faster_rcnn_r101_fpn_1x_coco_20200203-8dba6a5a.pth
- Name: libra_faster_rcnn_x101_64x4d_fpn_1x_coco
In Collection: Libra R-CNN
Config: configs/libra_rcnn/libra_faster_rcnn_x101_64x4d_fpn_1x_coco.py
Metadata:
Training Memory (GB): 10.8
inference time (ms/im):
- value: 117.65
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 42.7
Weights: https://download.openmmlab.com/mmdetection/v2.0/libra_rcnn/libra_faster_rcnn_x101_64x4d_fpn_1x_coco/libra_faster_rcnn_x101_64x4d_fpn_1x_coco_20200315-3a7d0488.pth
- Name: libra_retinanet_r50_fpn_1x_coco
In Collection: Libra R-CNN
Config: configs/libra_rcnn/libra_retinanet_r50_fpn_1x_coco.py
Metadata:
Training Memory (GB): 4.2
inference time (ms/im):
- value: 56.5
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 37.6
Weights: https://download.openmmlab.com/mmdetection/v2.0/libra_rcnn/libra_retinanet_r50_fpn_1x_coco/libra_retinanet_r50_fpn_1x_coco_20200205-804d94ce.pth