972 lines
32 KiB
YAML
972 lines
32 KiB
YAML
Models:
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- Name: faster_rcnn_hrnetv2p_w18_1x_coco
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In Collection: Faster R-CNN
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Config: configs/hrnet/faster_rcnn_hrnetv2p_w18_1x_coco.py
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Metadata:
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Training Memory (GB): 6.6
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inference time (ms/im):
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- value: 74.63
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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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Training Data: COCO
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Training Techniques:
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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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- HRNet
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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: 36.9
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Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/faster_rcnn_hrnetv2p_w18_1x_coco/faster_rcnn_hrnetv2p_w18_1x_coco_20200130-56651a6d.pth
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Paper:
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URL: https://arxiv.org/abs/1904.04514
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Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
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README: configs/hrnet/README.md
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Code:
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URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
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Version: v2.0.0
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- Name: faster_rcnn_hrnetv2p_w18_2x_coco
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In Collection: Faster R-CNN
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Config: configs/hrnet/faster_rcnn_hrnetv2p_w18_2x_coco.py
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Metadata:
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Training Memory (GB): 6.6
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inference time (ms/im):
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- value: 74.63
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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: 24
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Training Data: COCO
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Training Techniques:
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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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- HRNet
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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: 38.9
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Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/faster_rcnn_hrnetv2p_w18_2x_coco/faster_rcnn_hrnetv2p_w18_2x_coco_20200702_085731-a4ec0611.pth
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Paper:
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URL: https://arxiv.org/abs/1904.04514
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Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
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README: configs/hrnet/README.md
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Code:
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URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
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Version: v2.0.0
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- Name: faster_rcnn_hrnetv2p_w32_1x_coco
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In Collection: Faster R-CNN
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Config: configs/hrnet/faster_rcnn_hrnetv2p_w32_1x_coco.py
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Metadata:
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Training Memory (GB): 9.0
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inference time (ms/im):
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- value: 80.65
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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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Training Data: COCO
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Training Techniques:
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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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- HRNet
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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: 40.2
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Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/faster_rcnn_hrnetv2p_w32_1x_coco/faster_rcnn_hrnetv2p_w32_1x_coco_20200130-6e286425.pth
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Paper:
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URL: https://arxiv.org/abs/1904.04514
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Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
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README: configs/hrnet/README.md
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Code:
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URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
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Version: v2.0.0
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- Name: faster_rcnn_hrnetv2p_w32_2x_coco
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In Collection: Faster R-CNN
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Config: configs/hrnet/faster_rcnn_hrnetv2p_w32_2x_coco.py
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Metadata:
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Training Memory (GB): 9.0
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inference time (ms/im):
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- value: 80.65
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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: 24
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Training Data: COCO
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Training Techniques:
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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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- HRNet
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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: 41.4
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Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/faster_rcnn_hrnetv2p_w32_2x_coco/faster_rcnn_hrnetv2p_w32_2x_coco_20200529_015927-976a9c15.pth
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Paper:
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URL: https://arxiv.org/abs/1904.04514
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Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
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README: configs/hrnet/README.md
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Code:
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URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
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Version: v2.0.0
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- Name: faster_rcnn_hrnetv2p_w40_1x_coco
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In Collection: Faster R-CNN
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Config: configs/hrnet/faster_rcnn_hrnetv2p_w40_1x_coco.py
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Metadata:
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Training Memory (GB): 10.4
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inference time (ms/im):
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- value: 95.24
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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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Training Data: COCO
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Training Techniques:
|
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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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- HRNet
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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: 41.2
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Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/faster_rcnn_hrnetv2p_w40_1x_coco/faster_rcnn_hrnetv2p_w40_1x_coco_20200210-95c1f5ce.pth
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Paper:
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URL: https://arxiv.org/abs/1904.04514
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Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
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README: configs/hrnet/README.md
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Code:
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URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
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Version: v2.0.0
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- Name: faster_rcnn_hrnetv2p_w40_2x_coco
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In Collection: Faster R-CNN
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Config: configs/hrnet/faster_rcnn_hrnetv2p_w40_2x_coco.py
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Metadata:
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Training Memory (GB): 10.4
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inference time (ms/im):
|
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- value: 95.24
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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: 24
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Training Data: COCO
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Training Techniques:
|
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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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- HRNet
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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: 42.1
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Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/faster_rcnn_hrnetv2p_w40_2x_coco/faster_rcnn_hrnetv2p_w40_2x_coco_20200512_161033-0f236ef4.pth
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Paper:
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URL: https://arxiv.org/abs/1904.04514
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Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
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README: configs/hrnet/README.md
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Code:
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URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
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Version: v2.0.0
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- Name: mask_rcnn_hrnetv2p_w18_1x_coco
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In Collection: Mask R-CNN
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Config: configs/hrnet/mask_rcnn_hrnetv2p_w18_1x_coco.py
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Metadata:
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Training Memory (GB): 7.0
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inference time (ms/im):
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- value: 85.47
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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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Training Data: COCO
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Training Techniques:
|
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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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- HRNet
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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: 37.7
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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 34.2
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Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/mask_rcnn_hrnetv2p_w18_1x_coco/mask_rcnn_hrnetv2p_w18_1x_coco_20200205-1c3d78ed.pth
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Paper:
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URL: https://arxiv.org/abs/1904.04514
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Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
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README: configs/hrnet/README.md
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Code:
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URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
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Version: v2.0.0
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- Name: mask_rcnn_hrnetv2p_w18_2x_coco
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In Collection: Mask R-CNN
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Config: configs/hrnet/mask_rcnn_hrnetv2p_w18_2x_coco.py
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Metadata:
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Training Memory (GB): 7.0
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inference time (ms/im):
|
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- value: 85.47
|
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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: 24
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|
Training Data: COCO
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|
Training Techniques:
|
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- SGD with Momentum
|
|
- Weight Decay
|
|
Training Resources: 8x V100 GPUs
|
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Architecture:
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- HRNet
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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: 39.8
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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 36.0
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Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/mask_rcnn_hrnetv2p_w18_2x_coco/mask_rcnn_hrnetv2p_w18_2x_coco_20200212-b3c825b1.pth
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Paper:
|
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URL: https://arxiv.org/abs/1904.04514
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Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
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README: configs/hrnet/README.md
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|
Code:
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URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
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Version: v2.0.0
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- Name: mask_rcnn_hrnetv2p_w32_1x_coco
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In Collection: Mask R-CNN
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Config: configs/hrnet/mask_rcnn_hrnetv2p_w32_1x_coco.py
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Metadata:
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Training Memory (GB): 9.4
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inference time (ms/im):
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- value: 88.5
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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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Training Data: COCO
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Training Techniques:
|
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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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- HRNet
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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: 41.2
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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 37.1
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Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/mask_rcnn_hrnetv2p_w32_1x_coco/mask_rcnn_hrnetv2p_w32_1x_coco_20200207-b29f616e.pth
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Paper:
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URL: https://arxiv.org/abs/1904.04514
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Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
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README: configs/hrnet/README.md
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|
Code:
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URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
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Version: v2.0.0
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- Name: mask_rcnn_hrnetv2p_w32_2x_coco
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In Collection: Mask R-CNN
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Config: configs/hrnet/mask_rcnn_hrnetv2p_w32_2x_coco.py
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Metadata:
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Training Memory (GB): 9.4
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inference time (ms/im):
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- value: 88.5
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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: 24
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|
Training Data: COCO
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Training Techniques:
|
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- SGD with Momentum
|
|
- Weight Decay
|
|
Training Resources: 8x V100 GPUs
|
|
Architecture:
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- HRNet
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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: 42.5
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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 37.8
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Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/mask_rcnn_hrnetv2p_w32_2x_coco/mask_rcnn_hrnetv2p_w32_2x_coco_20200213-45b75b4d.pth
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Paper:
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URL: https://arxiv.org/abs/1904.04514
|
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Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
|
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README: configs/hrnet/README.md
|
|
Code:
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URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
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Version: v2.0.0
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|
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- Name: mask_rcnn_hrnetv2p_w40_1x_coco
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In Collection: Mask R-CNN
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Config: configs/hrnet/mask_rcnn_hrnetv2p_w40_1x_coco.py
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Metadata:
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Training Memory (GB): 10.9
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Epochs: 12
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Training Data: COCO
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Training Techniques:
|
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- SGD with Momentum
|
|
- Weight Decay
|
|
Training Resources: 8x V100 GPUs
|
|
Architecture:
|
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- HRNet
|
|
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: 42.1
|
|
- Task: Instance Segmentation
|
|
Dataset: COCO
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|
Metrics:
|
|
mask AP: 37.5
|
|
Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/mask_rcnn_hrnetv2p_w40_1x_coco/mask_rcnn_hrnetv2p_w40_1x_coco_20200511_015646-66738b35.pth
|
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Paper:
|
|
URL: https://arxiv.org/abs/1904.04514
|
|
Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
|
|
README: configs/hrnet/README.md
|
|
Code:
|
|
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
|
|
Version: v2.0.0
|
|
|
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- Name: mask_rcnn_hrnetv2p_w40_2x_coco
|
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In Collection: Mask R-CNN
|
|
Config: configs/hrnet/mask_rcnn_hrnetv2p_w40_2x_coco.py
|
|
Metadata:
|
|
Training Memory (GB): 10.9
|
|
Epochs: 24
|
|
Training Data: COCO
|
|
Training Techniques:
|
|
- SGD with Momentum
|
|
- Weight Decay
|
|
Training Resources: 8x V100 GPUs
|
|
Architecture:
|
|
- HRNet
|
|
Results:
|
|
- Task: Object Detection
|
|
Dataset: COCO
|
|
Metrics:
|
|
box AP: 42.8
|
|
- Task: Instance Segmentation
|
|
Dataset: COCO
|
|
Metrics:
|
|
mask AP: 38.2
|
|
Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/mask_rcnn_hrnetv2p_w40_2x_coco/mask_rcnn_hrnetv2p_w40_2x_coco_20200512_163732-aed5e4ab.pth
|
|
Paper:
|
|
URL: https://arxiv.org/abs/1904.04514
|
|
Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
|
|
README: configs/hrnet/README.md
|
|
Code:
|
|
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
|
|
Version: v2.0.0
|
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|
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- Name: cascade_rcnn_hrnetv2p_w18_20e_coco
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In Collection: Cascade R-CNN
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Config: configs/hrnet/cascade_rcnn_hrnetv2p_w18_20e_coco.py
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Metadata:
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Training Memory (GB): 7.0
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inference time (ms/im):
|
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- value: 90.91
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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)
|
|
Epochs: 20
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|
Training Data: COCO
|
|
Training Techniques:
|
|
- SGD with Momentum
|
|
- Weight Decay
|
|
Training Resources: 8x V100 GPUs
|
|
Architecture:
|
|
- HRNet
|
|
Results:
|
|
- Task: Object Detection
|
|
Dataset: COCO
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Metrics:
|
|
box AP: 41.2
|
|
Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/cascade_rcnn_hrnetv2p_w18_20e_coco/cascade_rcnn_hrnetv2p_w18_20e_coco_20200210-434be9d7.pth
|
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Paper:
|
|
URL: https://arxiv.org/abs/1904.04514
|
|
Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
|
|
README: configs/hrnet/README.md
|
|
Code:
|
|
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
|
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Version: v2.0.0
|
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|
|
- Name: cascade_rcnn_hrnetv2p_w32_20e_coco
|
|
In Collection: Cascade R-CNN
|
|
Config: configs/hrnet/cascade_rcnn_hrnetv2p_w32_20e_coco.py
|
|
Metadata:
|
|
Training Memory (GB): 9.4
|
|
inference time (ms/im):
|
|
- value: 90.91
|
|
hardware: V100
|
|
backend: PyTorch
|
|
batch size: 1
|
|
mode: FP32
|
|
resolution: (800, 1333)
|
|
Epochs: 20
|
|
Training Data: COCO
|
|
Training Techniques:
|
|
- SGD with Momentum
|
|
- Weight Decay
|
|
Training Resources: 8x V100 GPUs
|
|
Architecture:
|
|
- HRNet
|
|
Results:
|
|
- Task: Object Detection
|
|
Dataset: COCO
|
|
Metrics:
|
|
box AP: 43.3
|
|
Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/cascade_rcnn_hrnetv2p_w32_20e_coco/cascade_rcnn_hrnetv2p_w32_20e_coco_20200208-928455a4.pth
|
|
Paper:
|
|
URL: https://arxiv.org/abs/1904.04514
|
|
Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
|
|
README: configs/hrnet/README.md
|
|
Code:
|
|
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
|
|
Version: v2.0.0
|
|
|
|
- Name: cascade_rcnn_hrnetv2p_w40_20e_coco
|
|
In Collection: Cascade R-CNN
|
|
Config: configs/hrnet/cascade_rcnn_hrnetv2p_w40_20e_coco.py
|
|
Metadata:
|
|
Training Memory (GB): 10.8
|
|
Epochs: 20
|
|
Training Data: COCO
|
|
Training Techniques:
|
|
- SGD with Momentum
|
|
- Weight Decay
|
|
Training Resources: 8x V100 GPUs
|
|
Architecture:
|
|
- HRNet
|
|
Results:
|
|
- Task: Object Detection
|
|
Dataset: COCO
|
|
Metrics:
|
|
box AP: 43.8
|
|
Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/cascade_rcnn_hrnetv2p_w40_20e_coco/cascade_rcnn_hrnetv2p_w40_20e_coco_20200512_161112-75e47b04.pth
|
|
Paper:
|
|
URL: https://arxiv.org/abs/1904.04514
|
|
Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
|
|
README: configs/hrnet/README.md
|
|
Code:
|
|
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
|
|
Version: v2.0.0
|
|
|
|
- Name: cascade_mask_rcnn_hrnetv2p_w18_20e_coco
|
|
In Collection: Cascade R-CNN
|
|
Config: configs/hrnet/cascade_mask_rcnn_hrnetv2p_w18_20e_coco.py
|
|
Metadata:
|
|
Training Memory (GB): 8.5
|
|
inference time (ms/im):
|
|
- value: 117.65
|
|
hardware: V100
|
|
backend: PyTorch
|
|
batch size: 1
|
|
mode: FP32
|
|
resolution: (800, 1333)
|
|
Epochs: 20
|
|
Training Data: COCO
|
|
Training Techniques:
|
|
- SGD with Momentum
|
|
- Weight Decay
|
|
Training Resources: 8x V100 GPUs
|
|
Architecture:
|
|
- HRNet
|
|
Results:
|
|
- Task: Object Detection
|
|
Dataset: COCO
|
|
Metrics:
|
|
box AP: 41.6
|
|
- Task: Instance Segmentation
|
|
Dataset: COCO
|
|
Metrics:
|
|
mask AP: 36.4
|
|
Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/cascade_mask_rcnn_hrnetv2p_w18_20e_coco/cascade_mask_rcnn_hrnetv2p_w18_20e_coco_20200210-b543cd2b.pth
|
|
Paper:
|
|
URL: https://arxiv.org/abs/1904.04514
|
|
Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
|
|
README: configs/hrnet/README.md
|
|
Code:
|
|
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
|
|
Version: v2.0.0
|
|
|
|
- Name: cascade_mask_rcnn_hrnetv2p_w32_20e_coco
|
|
In Collection: Cascade R-CNN
|
|
Config: configs/hrnet/cascade_mask_rcnn_hrnetv2p_w32_20e_coco.py
|
|
Metadata:
|
|
inference time (ms/im):
|
|
- value: 120.48
|
|
hardware: V100
|
|
backend: PyTorch
|
|
batch size: 1
|
|
mode: FP32
|
|
resolution: (800, 1333)
|
|
Epochs: 20
|
|
Training Data: COCO
|
|
Training Techniques:
|
|
- SGD with Momentum
|
|
- Weight Decay
|
|
Training Resources: 8x V100 GPUs
|
|
Architecture:
|
|
- HRNet
|
|
Results:
|
|
- Task: Object Detection
|
|
Dataset: COCO
|
|
Metrics:
|
|
box AP: 44.3
|
|
- Task: Instance Segmentation
|
|
Dataset: COCO
|
|
Metrics:
|
|
mask AP: 38.6
|
|
Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/cascade_mask_rcnn_hrnetv2p_w32_20e_coco/cascade_mask_rcnn_hrnetv2p_w32_20e_coco_20200512_154043-39d9cf7b.pth
|
|
Paper:
|
|
URL: https://arxiv.org/abs/1904.04514
|
|
Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
|
|
README: configs/hrnet/README.md
|
|
Code:
|
|
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
|
|
Version: v2.0.0
|
|
|
|
- Name: cascade_mask_rcnn_hrnetv2p_w40_20e_coco
|
|
In Collection: Cascade R-CNN
|
|
Config: configs/hrnet/cascade_mask_rcnn_hrnetv2p_w40_20e_coco.py
|
|
Metadata:
|
|
Training Memory (GB): 12.5
|
|
Epochs: 20
|
|
Training Data: COCO
|
|
Training Techniques:
|
|
- SGD with Momentum
|
|
- Weight Decay
|
|
Training Resources: 8x V100 GPUs
|
|
Architecture:
|
|
- HRNet
|
|
Results:
|
|
- Task: Object Detection
|
|
Dataset: COCO
|
|
Metrics:
|
|
box AP: 45.1
|
|
- Task: Instance Segmentation
|
|
Dataset: COCO
|
|
Metrics:
|
|
mask AP: 39.3
|
|
Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/cascade_mask_rcnn_hrnetv2p_w40_20e_coco/cascade_mask_rcnn_hrnetv2p_w40_20e_coco_20200527_204922-969c4610.pth
|
|
Paper:
|
|
URL: https://arxiv.org/abs/1904.04514
|
|
Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
|
|
README: configs/hrnet/README.md
|
|
Code:
|
|
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
|
|
Version: v2.0.0
|
|
|
|
- Name: htc_hrnetv2p_w18_20e_coco
|
|
In Collection: HTC
|
|
Config: configs/hrnet/htc_hrnetv2p_w18_20e_coco.py
|
|
Metadata:
|
|
Training Memory (GB): 10.8
|
|
inference time (ms/im):
|
|
- value: 212.77
|
|
hardware: V100
|
|
backend: PyTorch
|
|
batch size: 1
|
|
mode: FP32
|
|
resolution: (800, 1333)
|
|
Epochs: 20
|
|
Training Data: COCO
|
|
Training Techniques:
|
|
- SGD with Momentum
|
|
- Weight Decay
|
|
Training Resources: 8x V100 GPUs
|
|
Architecture:
|
|
- HRNet
|
|
Results:
|
|
- Task: Object Detection
|
|
Dataset: COCO
|
|
Metrics:
|
|
box AP: 42.8
|
|
- Task: Instance Segmentation
|
|
Dataset: COCO
|
|
Metrics:
|
|
mask AP: 37.9
|
|
Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/htc_hrnetv2p_w18_20e_coco/htc_hrnetv2p_w18_20e_coco_20200210-b266988c.pth
|
|
Paper:
|
|
URL: https://arxiv.org/abs/1904.04514
|
|
Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
|
|
README: configs/hrnet/README.md
|
|
Code:
|
|
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
|
|
Version: v2.0.0
|
|
|
|
- Name: htc_hrnetv2p_w32_20e_coco
|
|
In Collection: HTC
|
|
Config: configs/hrnet/htc_hrnetv2p_w32_20e_coco.py
|
|
Metadata:
|
|
Training Memory (GB): 13.1
|
|
inference time (ms/im):
|
|
- value: 204.08
|
|
hardware: V100
|
|
backend: PyTorch
|
|
batch size: 1
|
|
mode: FP32
|
|
resolution: (800, 1333)
|
|
Epochs: 20
|
|
Training Data: COCO
|
|
Training Techniques:
|
|
- SGD with Momentum
|
|
- Weight Decay
|
|
Training Resources: 8x V100 GPUs
|
|
Architecture:
|
|
- HRNet
|
|
Results:
|
|
- Task: Object Detection
|
|
Dataset: COCO
|
|
Metrics:
|
|
box AP: 45.4
|
|
- Task: Instance Segmentation
|
|
Dataset: COCO
|
|
Metrics:
|
|
mask AP: 39.9
|
|
Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/htc_hrnetv2p_w32_20e_coco/htc_hrnetv2p_w32_20e_coco_20200207-7639fa12.pth
|
|
Paper:
|
|
URL: https://arxiv.org/abs/1904.04514
|
|
Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
|
|
README: configs/hrnet/README.md
|
|
Code:
|
|
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
|
|
Version: v2.0.0
|
|
|
|
- Name: htc_hrnetv2p_w40_20e_coco
|
|
In Collection: HTC
|
|
Config: configs/hrnet/htc_hrnetv2p_w40_20e_coco.py
|
|
Metadata:
|
|
Training Memory (GB): 14.6
|
|
Epochs: 20
|
|
Training Data: COCO
|
|
Training Techniques:
|
|
- SGD with Momentum
|
|
- Weight Decay
|
|
Training Resources: 8x V100 GPUs
|
|
Architecture:
|
|
- HRNet
|
|
Results:
|
|
- Task: Object Detection
|
|
Dataset: COCO
|
|
Metrics:
|
|
box AP: 46.4
|
|
- Task: Instance Segmentation
|
|
Dataset: COCO
|
|
Metrics:
|
|
mask AP: 40.8
|
|
Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/htc_hrnetv2p_w40_20e_coco/htc_hrnetv2p_w40_20e_coco_20200529_183411-417c4d5b.pth
|
|
Paper:
|
|
URL: https://arxiv.org/abs/1904.04514
|
|
Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
|
|
README: configs/hrnet/README.md
|
|
Code:
|
|
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
|
|
Version: v2.0.0
|
|
|
|
- Name: fcos_hrnetv2p_w18_gn-head_4x4_1x_coco
|
|
In Collection: FCOS
|
|
Config: configs/hrnet/fcos_hrnetv2p_w18_gn-head_4x4_1x_coco.py
|
|
Metadata:
|
|
Training Resources: 4x V100 GPUs
|
|
Batch Size: 16
|
|
Training Memory (GB): 13.0
|
|
inference time (ms/im):
|
|
- value: 77.52
|
|
hardware: V100
|
|
backend: PyTorch
|
|
batch size: 1
|
|
mode: FP32
|
|
resolution: (800, 1333)
|
|
Epochs: 12
|
|
Training Data: COCO
|
|
Training Techniques:
|
|
- SGD with Momentum
|
|
- Weight Decay
|
|
Architecture:
|
|
- HRNet
|
|
Results:
|
|
- Task: Object Detection
|
|
Dataset: COCO
|
|
Metrics:
|
|
box AP: 35.3
|
|
Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/fcos_hrnetv2p_w18_gn-head_4x4_1x_coco/fcos_hrnetv2p_w18_gn-head_4x4_1x_coco_20201212_100710-4ad151de.pth
|
|
Paper:
|
|
URL: https://arxiv.org/abs/1904.04514
|
|
Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
|
|
README: configs/hrnet/README.md
|
|
Code:
|
|
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
|
|
Version: v2.0.0
|
|
|
|
- Name: fcos_hrnetv2p_w18_gn-head_4x4_2x_coco
|
|
In Collection: FCOS
|
|
Config: configs/hrnet/fcos_hrnetv2p_w18_gn-head_4x4_2x_coco.py
|
|
Metadata:
|
|
Training Resources: 4x V100 GPUs
|
|
Batch Size: 16
|
|
Training Memory (GB): 13.0
|
|
inference time (ms/im):
|
|
- value: 77.52
|
|
hardware: V100
|
|
backend: PyTorch
|
|
batch size: 1
|
|
mode: FP32
|
|
resolution: (800, 1333)
|
|
Epochs: 24
|
|
Training Data: COCO
|
|
Training Techniques:
|
|
- SGD with Momentum
|
|
- Weight Decay
|
|
Architecture:
|
|
- HRNet
|
|
Results:
|
|
- Task: Object Detection
|
|
Dataset: COCO
|
|
Metrics:
|
|
box AP: 38.2
|
|
Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/fcos_hrnetv2p_w18_gn-head_4x4_2x_coco/fcos_hrnetv2p_w18_gn-head_4x4_2x_coco_20201212_101110-5c575fa5.pth
|
|
Paper:
|
|
URL: https://arxiv.org/abs/1904.04514
|
|
Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
|
|
README: configs/hrnet/README.md
|
|
Code:
|
|
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
|
|
Version: v2.0.0
|
|
|
|
- Name: fcos_hrnetv2p_w32_gn-head_4x4_1x_coco
|
|
In Collection: FCOS
|
|
Config: configs/hrnet/fcos_hrnetv2p_w32_gn-head_4x4_1x_coco.py
|
|
Metadata:
|
|
Training Resources: 4x V100 GPUs
|
|
Batch Size: 16
|
|
Training Memory (GB): 17.5
|
|
inference time (ms/im):
|
|
- value: 77.52
|
|
hardware: V100
|
|
backend: PyTorch
|
|
batch size: 1
|
|
mode: FP32
|
|
resolution: (800, 1333)
|
|
Epochs: 12
|
|
Training Data: COCO
|
|
Training Techniques:
|
|
- SGD with Momentum
|
|
- Weight Decay
|
|
Architecture:
|
|
- HRNet
|
|
Results:
|
|
- Task: Object Detection
|
|
Dataset: COCO
|
|
Metrics:
|
|
box AP: 39.5
|
|
Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/fcos_hrnetv2p_w32_gn-head_4x4_1x_coco/fcos_hrnetv2p_w32_gn-head_4x4_1x_coco_20201211_134730-cb8055c0.pth
|
|
Paper:
|
|
URL: https://arxiv.org/abs/1904.04514
|
|
Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
|
|
README: configs/hrnet/README.md
|
|
Code:
|
|
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
|
|
Version: v2.0.0
|
|
|
|
- Name: fcos_hrnetv2p_w32_gn-head_4x4_2x_coco
|
|
In Collection: FCOS
|
|
Config: configs/hrnet/fcos_hrnetv2p_w32_gn-head_4x4_2x_coco.py
|
|
Metadata:
|
|
Training Resources: 4x V100 GPUs
|
|
Batch Size: 16
|
|
Training Memory (GB): 17.5
|
|
inference time (ms/im):
|
|
- value: 77.52
|
|
hardware: V100
|
|
backend: PyTorch
|
|
batch size: 1
|
|
mode: FP32
|
|
resolution: (800, 1333)
|
|
Epochs: 24
|
|
Training Data: COCO
|
|
Training Techniques:
|
|
- SGD with Momentum
|
|
- Weight Decay
|
|
Architecture:
|
|
- HRNet
|
|
Results:
|
|
- Task: Object Detection
|
|
Dataset: COCO
|
|
Metrics:
|
|
box AP: 40.8
|
|
Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/fcos_hrnetv2p_w32_gn-head_4x4_2x_coco/fcos_hrnetv2p_w32_gn-head_4x4_2x_coco_20201212_112133-77b6b9bb.pth
|
|
Paper:
|
|
URL: https://arxiv.org/abs/1904.04514
|
|
Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
|
|
README: configs/hrnet/README.md
|
|
Code:
|
|
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
|
|
Version: v2.0.0
|
|
|
|
- Name: fcos_hrnetv2p_w18_gn-head_mstrain_640-800_4x4_2x_coco
|
|
In Collection: FCOS
|
|
Config: configs/hrnet/fcos_hrnetv2p_w18_gn-head_mstrain_640-800_4x4_2x_coco.py
|
|
Metadata:
|
|
Training Resources: 4x V100 GPUs
|
|
Batch Size: 16
|
|
Training Memory (GB): 13.0
|
|
inference time (ms/im):
|
|
- value: 77.52
|
|
hardware: V100
|
|
backend: PyTorch
|
|
batch size: 1
|
|
mode: FP32
|
|
resolution: (800, 1333)
|
|
Epochs: 24
|
|
Training Data: COCO
|
|
Training Techniques:
|
|
- SGD with Momentum
|
|
- Weight Decay
|
|
Architecture:
|
|
- HRNet
|
|
Results:
|
|
- Task: Object Detection
|
|
Dataset: COCO
|
|
Metrics:
|
|
box AP: 38.3
|
|
Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/fcos_hrnetv2p_w18_gn-head_mstrain_640-800_4x4_2x_coco/fcos_hrnetv2p_w18_gn-head_mstrain_640-800_4x4_2x_coco_20201212_111651-441e9d9f.pth
|
|
Paper:
|
|
URL: https://arxiv.org/abs/1904.04514
|
|
Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
|
|
README: configs/hrnet/README.md
|
|
Code:
|
|
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
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Version: v2.0.0
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- Name: fcos_hrnetv2p_w32_gn-head_mstrain_640-800_4x4_2x_coco
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In Collection: FCOS
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Config: configs/hrnet/fcos_hrnetv2p_w32_gn-head_mstrain_640-800_4x4_2x_coco.py
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Metadata:
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Training Resources: 4x V100 GPUs
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Batch Size: 16
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Training Memory (GB): 17.5
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inference time (ms/im):
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- value: 80.65
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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: 24
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Training Data: COCO
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Training Techniques:
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- SGD with Momentum
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- Weight Decay
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Architecture:
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- HRNet
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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: 41.9
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Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/fcos_hrnetv2p_w32_gn-head_mstrain_640-800_4x4_2x_coco/fcos_hrnetv2p_w32_gn-head_mstrain_640-800_4x4_2x_coco_20201212_090846-b6f2b49f.pth
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Paper:
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URL: https://arxiv.org/abs/1904.04514
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Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
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README: configs/hrnet/README.md
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Code:
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URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
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Version: v2.0.0
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- Name: fcos_hrnetv2p_w40_gn-head_mstrain_640-800_4x4_2x_coco
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In Collection: FCOS
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Config: configs/hrnet/fcos_hrnetv2p_w40_gn-head_mstrain_640-800_4x4_2x_coco.py
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Metadata:
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Training Resources: 4x V100 GPUs
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Batch Size: 16
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Training Memory (GB): 20.3
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inference time (ms/im):
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- value: 92.59
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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: 24
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Training Data: COCO
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Training Techniques:
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- SGD with Momentum
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- Weight Decay
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Architecture:
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- HRNet
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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/hrnet/fcos_hrnetv2p_w40_gn-head_mstrain_640-800_4x4_2x_coco/fcos_hrnetv2p_w40_gn-head_mstrain_640-800_4x4_2x_coco_20201212_124752-f22d2ce5.pth
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Paper:
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URL: https://arxiv.org/abs/1904.04514
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Title: 'Deep High-Resolution Representation Learning for Visual Recognition'
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README: configs/hrnet/README.md
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Code:
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URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195
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Version: v2.0.0
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