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_fp16_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_mstrain-poly_2x_coco In Collection: Mask R-CNN Config: configs/mask_rcnn/mask_rcnn_r50_caffe_fpn_mstrain-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_mstrain-poly_3x_coco In Collection: Mask R-CNN Config: configs/mask_rcnn/mask_rcnn_r50_caffe_fpn_mstrain-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_mstrain-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_mstrain-poly_3x_coco In Collection: Mask R-CNN Config: configs/mask_rcnn/mask_rcnn_r101_fpn_mstrain-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_mstrain-poly_3x_coco In Collection: Mask R-CNN Config: configs/mask_rcnn/mask_rcnn_r101_caffe_fpn_mstrain-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_mstrain-poly_3x_coco In Collection: Mask R-CNN Config: configs/mask_rcnn/mask_rcnn_x101_32x4d_fpn_mstrain-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_mstrain-poly_1x_coco In Collection: Mask R-CNN Config: configs/mask_rcnn/mask_rcnn_x101_32x8d_fpn_mstrain-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_mstrain-poly_3x_coco In Collection: Mask R-CNN Config: configs/mask_rcnn/mask_rcnn_x101_32x8d_fpn_mstrain-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_mstrain-poly_3x_coco In Collection: Mask R-CNN Config: configs/mask_rcnn/mask_rcnn_x101_64x4d_fpn_mstrain-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