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