116 lines
3.3 KiB
YAML
116 lines
3.3 KiB
YAML
Collections:
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- Name: SOLO
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Metadata:
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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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- FPN
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- Convolution
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- ResNet
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Paper: https://arxiv.org/abs/1912.04488
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README: configs/solo/README.md
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Models:
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- Name: decoupled_solo_r50_fpn_1x_coco
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In Collection: SOLO
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Config: configs/solo/decoupled_solo_r50_fpn_1x_coco.py
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Metadata:
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Training Memory (GB): 7.8
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Epochs: 12
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inference time (ms/im):
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- value: 116.4
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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: (1333, 800)
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Results:
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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 33.9
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Weights: https://download.openmmlab.com/mmdetection/v2.0/solo/decoupled_solo_r50_fpn_1x_coco/decoupled_solo_r50_fpn_1x_coco_20210820_233348-6337c589.pth
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- Name: decoupled_solo_r50_fpn_3x_coco
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In Collection: SOLO
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Config: configs/solo/decoupled_solo_r50_fpn_3x_coco.py
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Metadata:
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Training Memory (GB): 7.9
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Epochs: 36
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inference time (ms/im):
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- value: 117.2
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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: (1333, 800)
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Results:
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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 36.7
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Weights: https://download.openmmlab.com/mmdetection/v2.0/solo/decoupled_solo_r50_fpn_3x_coco/decoupled_solo_r50_fpn_3x_coco_20210821_042504-7b3301ec.pth
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- Name: decoupled_solo_light_r50_fpn_3x_coco
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In Collection: SOLO
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Config: configs/solo/decoupled_solo_light_r50_fpn_3x_coco.py
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Metadata:
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Training Memory (GB): 2.2
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Epochs: 36
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inference time (ms/im):
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- value: 35.0
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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: (852, 512)
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Results:
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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 32.9
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Weights: https://download.openmmlab.com/mmdetection/v2.0/solo/decoupled_solo_light_r50_fpn_3x_coco/decoupled_solo_light_r50_fpn_3x_coco_20210906_142703-e70e226f.pth
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- Name: solo_r50_fpn_3x_coco
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In Collection: SOLO
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Config: configs/solo/solo_r50_fpn_3x_coco.py
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Metadata:
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Training Memory (GB): 7.4
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Epochs: 36
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inference time (ms/im):
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- value: 94.2
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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: (1333, 800)
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Results:
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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 35.9
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Weights: https://download.openmmlab.com/mmdetection/v2.0/solo/solo_r50_fpn_3x_coco/solo_r50_fpn_3x_coco_20210901_012353-11d224d7.pth
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- Name: solo_r50_fpn_1x_coco
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In Collection: SOLO
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Config: configs/solo/solo_r50_fpn_1x_coco.py
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Metadata:
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Training Memory (GB): 8.0
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Epochs: 12
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inference time (ms/im):
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- value: 95.1
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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: (1333, 800)
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Results:
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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 33.1
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Weights: https://download.openmmlab.com/mmdetection/v2.0/solo/solo_r50_fpn_1x_coco/solo_r50_fpn_1x_coco_20210821_035055-2290a6b8.pth
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