448 lines
14 KiB
YAML
448 lines
14 KiB
YAML
Collections:
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- Name: Mask R-CNN
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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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- Softmax
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- RPN
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- Convolution
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- Dense Connections
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- FPN
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- ResNet
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- RoIAlign
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Paper:
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URL: https://arxiv.org/abs/1703.06870v3
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Title: "Mask R-CNN"
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README: configs/mask_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/detectors/mask_rcnn.py#L6
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Version: v2.0.0
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Models:
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- Name: mask_rcnn_r50_caffe_fpn_1x_coco
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In Collection: Mask R-CNN
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Config: configs/mask_rcnn/mask_rcnn_r50_caffe_fpn_1x_coco.py
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Metadata:
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Training Memory (GB): 4.3
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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: 38.0
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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 34.4
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Weights: https://download.openmmlab.com/mmdetection/v2.0/mask_rcnn/mask_rcnn_r50_caffe_fpn_1x_coco/mask_rcnn_r50_caffe_fpn_1x_coco_bbox_mAP-0.38__segm_mAP-0.344_20200504_231812-0ebd1859.pth
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- Name: mask_rcnn_r50_fpn_1x_coco
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In Collection: Mask R-CNN
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Config: configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py
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Metadata:
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Training Memory (GB): 4.4
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inference time (ms/im):
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- value: 62.11
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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: 38.2
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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 34.7
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Weights: https://download.openmmlab.com/mmdetection/v2.0/mask_rcnn/mask_rcnn_r50_fpn_1x_coco/mask_rcnn_r50_fpn_1x_coco_20200205-d4b0c5d6.pth
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- Name: mask_rcnn_r50_fpn_fp16_1x_coco
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In Collection: Mask R-CNN
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Config: configs/mask_rcnn/mask_rcnn_r50_fpn_fp16_1x_coco.py
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Metadata:
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Training Memory (GB): 3.6
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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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inference time (ms/im):
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- value: 41.49
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hardware: V100
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backend: PyTorch
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batch size: 1
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mode: FP16
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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: 38.1
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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 34.7
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Weights: https://download.openmmlab.com/mmdetection/v2.0/fp16/mask_rcnn_r50_fpn_fp16_1x_coco/mask_rcnn_r50_fpn_fp16_1x_coco_20200205-59faf7e4.pth
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- Name: mask_rcnn_r50_fpn_2x_coco
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In Collection: Mask R-CNN
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Config: configs/mask_rcnn/mask_rcnn_r50_fpn_2x_coco.py
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Metadata:
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Training Memory (GB): 4.4
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inference time (ms/im):
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- value: 62.11
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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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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: 39.2
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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 35.4
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Weights: https://download.openmmlab.com/mmdetection/v2.0/mask_rcnn/mask_rcnn_r50_fpn_2x_coco/mask_rcnn_r50_fpn_2x_coco_bbox_mAP-0.392__segm_mAP-0.354_20200505_003907-3e542a40.pth
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- Name: mask_rcnn_r101_caffe_fpn_1x_coco
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In Collection: Mask R-CNN
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Config: configs/mask_rcnn/mask_rcnn_r101_caffe_fpn_1x_coco.py
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Metadata:
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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: 40.4
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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 36.4
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Weights: https://download.openmmlab.com/mmdetection/v2.0/mask_rcnn/mask_rcnn_r101_caffe_fpn_1x_coco/mask_rcnn_r101_caffe_fpn_1x_coco_20200601_095758-805e06c1.pth
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- Name: mask_rcnn_r101_fpn_1x_coco
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In Collection: Mask R-CNN
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Config: configs/mask_rcnn/mask_rcnn_r101_fpn_1x_coco.py
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Metadata:
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Training Memory (GB): 6.4
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inference time (ms/im):
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- value: 74.07
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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: 40.0
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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 36.1
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Weights: https://download.openmmlab.com/mmdetection/v2.0/mask_rcnn/mask_rcnn_r101_fpn_1x_coco/mask_rcnn_r101_fpn_1x_coco_20200204-1efe0ed5.pth
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- Name: mask_rcnn_r101_fpn_2x_coco
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In Collection: Mask R-CNN
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Config: configs/mask_rcnn/mask_rcnn_r101_fpn_2x_coco.py
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Metadata:
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Training Memory (GB): 6.4
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inference time (ms/im):
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- value: 74.07
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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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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: 40.8
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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 36.6
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Weights: https://download.openmmlab.com/mmdetection/v2.0/mask_rcnn/mask_rcnn_r101_fpn_2x_coco/mask_rcnn_r101_fpn_2x_coco_bbox_mAP-0.408__segm_mAP-0.366_20200505_071027-14b391c7.pth
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- Name: mask_rcnn_x101_32x4d_fpn_1x_coco
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In Collection: Mask R-CNN
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Config: configs/mask_rcnn/mask_rcnn_x101_32x4d_fpn_1x_coco.py
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Metadata:
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Training Memory (GB): 7.6
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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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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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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 37.5
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Weights: https://download.openmmlab.com/mmdetection/v2.0/mask_rcnn/mask_rcnn_x101_32x4d_fpn_1x_coco/mask_rcnn_x101_32x4d_fpn_1x_coco_20200205-478d0b67.pth
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- Name: mask_rcnn_x101_32x4d_fpn_2x_coco
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In Collection: Mask R-CNN
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Config: configs/mask_rcnn/mask_rcnn_x101_32x4d_fpn_2x_coco.py
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Metadata:
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Training Memory (GB): 7.6
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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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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: 42.2
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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 37.8
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Weights: https://download.openmmlab.com/mmdetection/v2.0/mask_rcnn/mask_rcnn_x101_32x4d_fpn_2x_coco/mask_rcnn_x101_32x4d_fpn_2x_coco_bbox_mAP-0.422__segm_mAP-0.378_20200506_004702-faef898c.pth
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- Name: mask_rcnn_x101_64x4d_fpn_1x_coco
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In Collection: Mask R-CNN
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Config: configs/mask_rcnn/mask_rcnn_x101_64x4d_fpn_1x_coco.py
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Metadata:
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Training Memory (GB): 10.7
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inference time (ms/im):
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- value: 125
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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: 42.8
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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 38.4
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Weights: https://download.openmmlab.com/mmdetection/v2.0/mask_rcnn/mask_rcnn_x101_64x4d_fpn_1x_coco/mask_rcnn_x101_64x4d_fpn_1x_coco_20200201-9352eb0d.pth
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- Name: mask_rcnn_x101_64x4d_fpn_2x_coco
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In Collection: Mask R-CNN
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Config: configs/mask_rcnn/mask_rcnn_x101_64x4d_fpn_2x_coco.py
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Metadata:
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Training Memory (GB): 10.7
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inference time (ms/im):
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- value: 125
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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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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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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 38.1
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Weights: https://download.openmmlab.com/mmdetection/v2.0/mask_rcnn/mask_rcnn_x101_64x4d_fpn_2x_coco/mask_rcnn_x101_64x4d_fpn_2x_coco_20200509_224208-39d6f70c.pth
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- Name: mask_rcnn_x101_32x8d_fpn_1x_coco
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In Collection: Mask R-CNN
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Config: configs/mask_rcnn/mask_rcnn_x101_32x8d_fpn_1x_coco.py
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Metadata:
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Training Memory (GB): 10.7
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inference time (ms/im):
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- value: 125
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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: 42.8
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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 38.3
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- Name: mask_rcnn_r50_caffe_fpn_mstrain-poly_2x_coco
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In Collection: Mask R-CNN
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Config: configs/mask_rcnn/mask_rcnn_r50_caffe_fpn_mstrain-poly_2x_coco.py
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Metadata:
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Training Memory (GB): 4.3
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Epochs: 24
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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: 40.3
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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 36.5
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Weights: https://download.openmmlab.com/mmdetection/v2.0/mask_rcnn/mask_rcnn_r50_caffe_fpn_mstrain-poly_2x_coco/mask_rcnn_r50_caffe_fpn_mstrain-poly_2x_coco_bbox_mAP-0.403__segm_mAP-0.365_20200504_231822-a75c98ce.pth
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- Name: mask_rcnn_r50_caffe_fpn_mstrain-poly_3x_coco
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In Collection: Mask R-CNN
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Config: configs/mask_rcnn/mask_rcnn_r50_caffe_fpn_mstrain-poly_3x_coco.py
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Metadata:
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Training Memory (GB): 4.3
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Epochs: 36
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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: 40.8
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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 37.0
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Weights: https://download.openmmlab.com/mmdetection/v2.0/mask_rcnn/mask_rcnn_r50_caffe_fpn_mstrain-poly_3x_coco/mask_rcnn_r50_caffe_fpn_mstrain-poly_3x_coco_bbox_mAP-0.408__segm_mAP-0.37_20200504_163245-42aa3d00.pth
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- Name: mask_rcnn_r50_fpn_mstrain-poly_3x_coco
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In Collection: Mask R-CNN
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Config: configs/mask_rcnn/mask_rcnn_r50_fpn_mstrain-poly_3x_coco.py
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Metadata:
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Training Memory (GB): 4.1
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Epochs: 36
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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: 40.9
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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/mask_rcnn/mask_rcnn_r50_fpn_mstrain-poly_3x_coco/mask_rcnn_r50_fpn_mstrain-poly_3x_coco_20210524_201154-21b550bb.pth
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- Name: mask_rcnn_r101_fpn_mstrain-poly_3x_coco
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In Collection: Mask R-CNN
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Config: configs/mask_rcnn/mask_rcnn_r101_fpn_mstrain-poly_3x_coco.py
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Metadata:
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Training Memory (GB): 6.1
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Epochs: 36
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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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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 38.5
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Weights: https://download.openmmlab.com/mmdetection/v2.0/mask_rcnn/mask_rcnn_r101_fpn_mstrain-poly_3x_coco/mask_rcnn_r101_fpn_mstrain-poly_3x_coco_20210524_200244-5675c317.pth
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- Name: mask_rcnn_r101_caffe_fpn_mstrain-poly_3x_coco
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In Collection: Mask R-CNN
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Config: configs/mask_rcnn/mask_rcnn_r101_caffe_fpn_mstrain-poly_3x_coco.py
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Metadata:
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Training Memory (GB): 5.9
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Epochs: 36
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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: 42.9
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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 38.5
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Weights: https://download.openmmlab.com/mmdetection/v2.0/mask_rcnn/mask_rcnn_r101_caffe_fpn_mstrain-poly_3x_coco/mask_rcnn_r101_caffe_fpn_mstrain-poly_3x_coco_20210526_132339-3c33ce02.pth
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- Name: mask_rcnn_x101_32x4d_fpn_mstrain-poly_3x_coco
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In Collection: Mask R-CNN
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Config: configs/mask_rcnn/mask_rcnn_x101_32x4d_fpn_mstrain-poly_3x_coco.py
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Metadata:
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Training Memory (GB): 7.3
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Epochs: 36
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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: 43.6
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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 39.0
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Weights: https://download.openmmlab.com/mmdetection/v2.0/mask_rcnn/mask_rcnn_x101_32x4d_fpn_mstrain-poly_3x_coco/mask_rcnn_x101_32x4d_fpn_mstrain-poly_3x_coco_20210524_201410-abcd7859.pth
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- Name: mask_rcnn_x101_32x8d_fpn_mstrain-poly_1x_coco
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In Collection: Mask R-CNN
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Config: configs/mask_rcnn/mask_rcnn_x101_32x8d_fpn_mstrain-poly_1x_coco.py
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Metadata:
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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: 43.6
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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 39.0
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- Name: mask_rcnn_x101_32x8d_fpn_mstrain-poly_3x_coco
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In Collection: Mask R-CNN
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Config: configs/mask_rcnn/mask_rcnn_x101_32x8d_fpn_mstrain-poly_3x_coco
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Metadata:
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Training Memory (GB): 10.3
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Epochs: 36
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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: 44.3
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Weights: https://download.openmmlab.com/mmdetection/v2.0/mask_rcnn/mask_rcnn_x101_32x8d_fpn_mstrain-poly_3x_coco/mask_rcnn_x101_32x8d_fpn_mstrain-poly_3x_coco_20210607_161042-8bd2c639.pth
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- Name: mask_rcnn_x101_64x4d_fpn_mstrain-poly_3x_coco
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In Collection: Mask R-CNN
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Config: configs/mask_rcnn/mask_rcnn_x101_64x4d_fpn_mstrain-poly_3x_coco.py
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Metadata:
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Epochs: 36
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Training Memory (GB): 10.4
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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: 44.5
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- Task: Instance Segmentation
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Dataset: COCO
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Metrics:
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mask AP: 39.7
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Weights: https://download.openmmlab.com/mmdetection/v2.0/mask_rcnn/mask_rcnn_x101_64x4d_fpn_mstrain-poly_3x_coco/mask_rcnn_x101_64x4d_fpn_mstrain-poly_3x_coco_20210526_120447-c376f129.pth
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