Hao He, Xiangtai Li, Guangliang Cheng, Yunhai Tong, Lubin Weng
This paper proposes a novel method for high-quality image segmentation of both objects and scenes. Inspired by the dilation and erosion operations in morphological image processing techniques, the pixel-level image segmentation problems are treated as squeezing object boundaries.
Comparison with Point Rend
Our method is built on the codebase of CVPOD.
Install, Training and Testing
# Or, to install it from a local clone: git clone https://github.com/lxtGH/BSSeg cd BSSeg pip install -r requirements.txt python setup.py build develop # Preprare data path ln -s /path/to/your/coco/dataset datasets/coco # Enter a specific experiment dir cd playground/detection/coco/bs_mask/boundary_refine_mask_rcnn_r50_ms_1x_3_subgt_warpping_dice_erode_dilate_gn # Train pods_train --num-gpus 8 # Test pods_test --num-gpus 8 \ MODEL.WEIGHTS /path/to/your/save_dir/ckpt.pth # optional OUTPUT_DIR /path/to/your/save_dir # optional # Multi node training ## sudo apt install net-tools ifconfig pods_train --num-gpus 8 --num-machines N --machine-rank 0/1/.../N-1 --dist-url "tcp://MASTER_IP:port"
If you find this codebase is useful to your research, plese consider cite the paper and original codebase.
@misc{he2021boundarysqueeze, title={BoundarySqueeze: Image Segmentation as Boundary Squeezing}, author={Hao He and Xiangtai Li and Guangliang Cheng and Yunhai Tong and Lubin Weng}, year={2021}, eprint={2105.11668}, archivePrefix={arXiv}, primaryClass={cs.CV} } @misc{zhu2020cvpods, title={cvpods: All-in-one Toolbox for Computer Vision Research}, author={Zhu*, Benjin and Wang*, Feng and Wang, Jianfeng and Yang, Siwei and Chen, Jianhu and Li, Zeming}, year={2020} }
