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Collections: |
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- Name: Deformable Convolutional Networks v2 |
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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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- Deformable Convolution |
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Paper: |
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URL: https://arxiv.org/abs/1811.11168 |
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Title: "Deformable ConvNets v2: More Deformable, Better Results" |
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README: configs/dcnv2/README.md |
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Code: |
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URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/ops/dcn/deform_conv.py#L15 |
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Version: v2.0.0 |
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Models: |
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- Name: faster-rcnn_r50_fpn_mdconv_c3-c5_1x_coco |
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In Collection: Deformable Convolutional Networks v2 |
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Config: configs/dcnv2/faster-rcnn_r50-mdconv-c3-c5_fpn_1x_coco.py |
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Metadata: |
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Training Memory (GB): 4.1 |
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inference time (ms/im): |
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- value: 56.82 |
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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: 41.4 |
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Weights: https://download.openmmlab.com/mmdetection/v2.0/dcn/faster_rcnn_r50_fpn_mdconv_c3-c5_1x_coco/faster_rcnn_r50_fpn_mdconv_c3-c5_1x_coco_20200130-d099253b.pth |
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- Name: faster-rcnn_r50_fpn_mdconv_c3-c5_group4_1x_coco |
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In Collection: Deformable Convolutional Networks v2 |
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Config: configs/dcnv2/faster-rcnn_r50-mdconv-group4-c3-c5_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: 57.47 |
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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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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: 41.5 |
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Weights: https://download.openmmlab.com/mmdetection/v2.0/dcn/faster_rcnn_r50_fpn_mdconv_c3-c5_group4_1x_coco/faster_rcnn_r50_fpn_mdconv_c3-c5_group4_1x_coco_20200130-01262257.pth |
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- Name: faster-rcnn_r50_fpn_mdpool_1x_coco |
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In Collection: Deformable Convolutional Networks v2 |
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Config: configs/dcnv2/faster-rcnn_r50_fpn_mdpool_1x_coco.py |
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Metadata: |
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Training Memory (GB): 5.8 |
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inference time (ms/im): |
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- value: 60.24 |
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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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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: 38.7 |
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Weights: https://download.openmmlab.com/mmdetection/v2.0/dcn/faster_rcnn_r50_fpn_mdpool_1x_coco/faster_rcnn_r50_fpn_mdpool_1x_coco_20200307-c0df27ff.pth |
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- Name: mask-rcnn_r50_fpn_mdconv_c3-c5_1x_coco |
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In Collection: Deformable Convolutional Networks v2 |
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Config: configs/dcnv2/mask-rcnn_r50-mdconv-c3-c5_fpn_1x_coco.py |
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Metadata: |
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Training Memory (GB): 4.5 |
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inference time (ms/im): |
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- value: 66.23 |
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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: 41.5 |
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- Task: Instance Segmentation |
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Dataset: COCO |
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Metrics: |
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mask AP: 37.1 |
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Weights: https://download.openmmlab.com/mmdetection/v2.0/dcn/mask_rcnn_r50_fpn_mdconv_c3-c5_1x_coco/mask_rcnn_r50_fpn_mdconv_c3-c5_1x_coco_20200203-ad97591f.pth |
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- Name: mask-rcnn_r50_fpn_fp16_mdconv_c3-c5_1x_coco |
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In Collection: Deformable Convolutional Networks v2 |
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Config: configs/dcnv2/mask-rcnn_r50-mdconv-c3-c5_fpn_amp-1x_coco.py |
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Metadata: |
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Training Memory (GB): 3.1 |
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Training Techniques: |
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- SGD with Momentum |
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- Weight Decay |
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- Mixed Precision Training |
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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: 42.0 |
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- Task: Instance Segmentation |
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Dataset: COCO |
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Metrics: |
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mask AP: 37.6 |
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Weights: https://download.openmmlab.com/mmdetection/v2.0/fp16/mask_rcnn_r50_fpn_fp16_mdconv_c3-c5_1x_coco/mask_rcnn_r50_fpn_fp16_mdconv_c3-c5_1x_coco_20210520_180434-cf8fefa5.pth |
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