Pointly-Supervised Instance Segmentation

Bowen Cheng, Omkar Parkhi, Alexander Kirillov

[arXiv] [Project] [BibTeX]

Data preparation

Please follow these steps to prepare your datasets:

1. Follow official Detectron2 instruction to prepare COCO dataset. Set up DETECTRON2_DATASETS environment variable to the location of your Detectron2 dataset.
2. Generate 10-points annotations for COCO by running: python tools/prepare_coco_point_annotations_without_masks.py 10

Training

To train a model with 8 GPUs run:

python train_net.py --config-file configs/mask_rcnn_R_50_FPN_3x_point_sup_point_aug_coco.yaml --num-gpus 8

Evaluation

Model evaluation can be done similarly:

python train_net.py --config-file configs/mask_rcnn_R_50_FPN_3x_point_sup_point_aug_coco.yaml --eval-only MODEL.WEIGHTS /path/to/model_checkpoint

<a name="CitingPointSup"></a>Citing Pointly-Supervised Instance Segmentation

If you use PointSup, please use the following BibTeX entry.

@article{cheng2021pointly,
  title={Pointly-Supervised Instance Segmentation},
  author={Bowen Cheng and Omkar Parkhi and Alexander Kirillov},
  journal={arXiv},
  year={2021}
}