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- Collections:
- - Name: Mask R-CNN
- Metadata:
- Training Data: COCO
- Training Techniques:
- - SGD with Momentum
- - Weight Decay
- Training Resources: 8x V100 GPUs
- Architecture:
- - Softmax
- - RPN
- - Convolution
- - Dense Connections
- - FPN
- - ResNet
- - RoIAlign
- Paper:
- URL: https://arxiv.org/abs/1703.06870v3
- Title: "Mask R-CNN"
- README: configs/mask_rcnn/README.md
- Code:
- URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/detectors/mask_rcnn.py#L6
- Version: v2.0.0
- Models:
- - Name: mask-rcnn_r50-caffe_fpn_1x_coco
- In Collection: Mask R-CNN
- Config: configs/mask_rcnn/mask-rcnn_r50-caffe_fpn_1x_coco.py
- Metadata:
- Training Memory (GB): 4.3
- Epochs: 12
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 38.0
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 34.4
- 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
- - Name: mask-rcnn_r50_fpn_1x_coco
- In Collection: Mask R-CNN
- Config: configs/mask_rcnn/mask-rcnn_r50_fpn_1x_coco.py
- Metadata:
- Training Memory (GB): 4.4
- inference time (ms/im):
- - value: 62.11
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 12
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 38.2
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 34.7
- 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
- - Name: mask-rcnn_r50_fpn_fp16_1x_coco
- In Collection: Mask R-CNN
- Config: configs/mask_rcnn/mask-rcnn_r50_fpn_amp-1x_coco.py
- Metadata:
- Training Memory (GB): 3.6
- Training Techniques:
- - SGD with Momentum
- - Weight Decay
- - Mixed Precision Training
- inference time (ms/im):
- - value: 41.49
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP16
- resolution: (800, 1333)
- Epochs: 12
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 38.1
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 34.7
- 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
- - Name: mask-rcnn_r50_fpn_2x_coco
- In Collection: Mask R-CNN
- Config: configs/mask_rcnn/mask-rcnn_r50_fpn_2x_coco.py
- Metadata:
- Training Memory (GB): 4.4
- inference time (ms/im):
- - value: 62.11
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 24
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 39.2
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 35.4
- 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
- - Name: mask-rcnn_r101-caffe_fpn_1x_coco
- In Collection: Mask R-CNN
- Config: configs/mask_rcnn/mask-rcnn_r101-caffe_fpn_1x_coco.py
- Metadata:
- Epochs: 12
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 40.4
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 36.4
- 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
- - Name: mask-rcnn_r101_fpn_1x_coco
- In Collection: Mask R-CNN
- Config: configs/mask_rcnn/mask-rcnn_r101_fpn_1x_coco.py
- Metadata:
- Training Memory (GB): 6.4
- inference time (ms/im):
- - value: 74.07
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 12
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 40.0
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 36.1
- 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
- - Name: mask-rcnn_r101_fpn_2x_coco
- In Collection: Mask R-CNN
- Config: configs/mask_rcnn/mask-rcnn_r101_fpn_2x_coco.py
- Metadata:
- Training Memory (GB): 6.4
- inference time (ms/im):
- - value: 74.07
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 24
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 40.8
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 36.6
- 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
- - Name: mask-rcnn_x101-32x4d_fpn_1x_coco
- In Collection: Mask R-CNN
- Config: configs/mask_rcnn/mask-rcnn_x101-32x4d_fpn_1x_coco.py
- Metadata:
- Training Memory (GB): 7.6
- inference time (ms/im):
- - value: 88.5
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 12
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 41.9
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 37.5
- 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
- - Name: mask-rcnn_x101-32x4d_fpn_2x_coco
- In Collection: Mask R-CNN
- Config: configs/mask_rcnn/mask-rcnn_x101-32x4d_fpn_2x_coco.py
- Metadata:
- Training Memory (GB): 7.6
- inference time (ms/im):
- - value: 88.5
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 24
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 42.2
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 37.8
- 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
- - Name: mask-rcnn_x101-64x4d_fpn_1x_coco
- In Collection: Mask R-CNN
- Config: configs/mask_rcnn/mask-rcnn_x101-64x4d_fpn_1x_coco.py
- Metadata:
- Training Memory (GB): 10.7
- inference time (ms/im):
- - value: 125
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 12
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 42.8
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 38.4
- 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
- - Name: mask-rcnn_x101-64x4d_fpn_2x_coco
- In Collection: Mask R-CNN
- Config: configs/mask_rcnn/mask-rcnn_x101-64x4d_fpn_2x_coco.py
- Metadata:
- Training Memory (GB): 10.7
- inference time (ms/im):
- - value: 125
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (800, 1333)
- Epochs: 24
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 42.7
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 38.1
- 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
- - Name: mask-rcnn_x101-32x8d_fpn_1x_coco
- In Collection: Mask R-CNN
- Config: configs/mask_rcnn/mask-rcnn_x101-32x8d_fpn_1x_coco.py
- Metadata:
- Training Memory (GB): 10.6
- Epochs: 12
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 42.8
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 38.3
- Weights: https://download.openmmlab.com/mmdetection/v2.0/mask_rcnn/mask_rcnn_x101_32x8d_fpn_1x_coco/mask_rcnn_x101_32x8d_fpn_1x_coco_20220630_173841-0aaf329e.pth
- - Name: mask-rcnn_r50-caffe_fpn_ms-poly-2x_coco
- In Collection: Mask R-CNN
- Config: configs/mask_rcnn/mask-rcnn_r50-caffe_fpn_ms-poly-2x_coco.py
- Metadata:
- Training Memory (GB): 4.3
- Epochs: 24
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 40.3
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 36.5
- 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
- - Name: mask-rcnn_r50-caffe_fpn_ms-poly-3x_coco
- In Collection: Mask R-CNN
- Config: configs/mask_rcnn/mask-rcnn_r50-caffe_fpn_ms-poly-3x_coco.py
- Metadata:
- Training Memory (GB): 4.3
- Epochs: 36
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 40.8
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 37.0
- 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
- - Name: mask-rcnn_r50_fpn_mstrain-poly_3x_coco
- In Collection: Mask R-CNN
- Config: configs/mask_rcnn/mask-rcnn_r50_fpn_ms-poly-3x_coco.py
- Metadata:
- Training Memory (GB): 4.1
- Epochs: 36
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 40.9
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 37.1
- 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
- - Name: mask-rcnn_r101_fpn_ms-poly-3x_coco
- In Collection: Mask R-CNN
- Config: configs/mask_rcnn/mask-rcnn_r101_fpn_ms-poly-3x_coco.py
- Metadata:
- Training Memory (GB): 6.1
- Epochs: 36
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 42.7
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 38.5
- 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
- - Name: mask-rcnn_r101-caffe_fpn_ms-poly-3x_coco
- In Collection: Mask R-CNN
- Config: configs/mask_rcnn/mask-rcnn_r101-caffe_fpn_ms-poly-3x_coco.py
- Metadata:
- Training Memory (GB): 5.9
- Epochs: 36
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 42.9
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 38.5
- 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
- - Name: mask-rcnn_x101-32x4d_fpn_ms-poly-3x_coco
- In Collection: Mask R-CNN
- Config: configs/mask_rcnn/mask-rcnn_x101-32x4d_fpn_ms-poly-3x_coco.py
- Metadata:
- Training Memory (GB): 7.3
- Epochs: 36
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 43.6
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 39.0
- 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
- - Name: mask-rcnn_x101-32x8d_fpn_ms-poly-1x_coco
- In Collection: Mask R-CNN
- Config: configs/mask_rcnn/mask-rcnn_x101-32x8d_fpn_ms-poly-1x_coco.py
- Metadata:
- Training Memory (GB): 10.4
- Epochs: 12
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 43.4
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 39.0
- Weights: https://download.openmmlab.com/mmdetection/v2.0/mask_rcnn/mask_rcnn_x101_32x8d_fpn_mstrain-poly_1x_coco/mask_rcnn_x101_32x8d_fpn_mstrain-poly_1x_coco_20220630_170346-b4637974.pth
- - Name: mask-rcnn_x101-32x8d_fpn_ms-poly-3x_coco
- In Collection: Mask R-CNN
- Config: configs/mask_rcnn/mask-rcnn_x101-32x8d_fpn_ms-poly-3x_coco.py
- Metadata:
- Training Memory (GB): 10.3
- Epochs: 36
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 44.3
- 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
- - Name: mask-rcnn_x101-64x4d_fpn_ms-poly_3x_coco
- In Collection: Mask R-CNN
- Config: configs/mask_rcnn/mask-rcnn_x101-64x4d_fpn_ms-poly_3x_coco.py
- Metadata:
- Epochs: 36
- Training Memory (GB): 10.4
- Results:
- - Task: Object Detection
- Dataset: COCO
- Metrics:
- box AP: 44.5
- - Task: Instance Segmentation
- Dataset: COCO
- Metrics:
- mask AP: 39.7
- 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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