LGRNet: Local-Global Reciprocal Network for Video Polyp Segmentation Paper | BibTeX | Huggingface(UFUV Dataset)
Huihui Xu, Yijun Yang, Angelica Aviles-Rivero, Guang Yang, Jing Qin, and Lei Zhu
This is the official implmentation of LGRNet (MICCAI'24 Early Accept), which incorporates local Cyclic Neighborhoold Propagation and global Hilbert Selective Scan. Together with the notion of Frame Bottleneck Queries, LGRNet can both efficiently and effectively aggregate the local-global temporal context, which achieves state-of-the-art on the public Video Polyp Segmentation(VPS) benchmark.
Items
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Installation: Please refer to INSTALL.md for more details.
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Data preparation: Please refer to DATA.md for more details.
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Training:
Change PORT_NUM for DDP and make sure the $CURRENT_TASK is 'VIS':
export CURRENT_TASK=VIS
export MASTER_ADDR=127.0.0.1
export MASTER_PORT=PORT_NUM
Make sure the $PT_PATH and $DATASET_PATH are correctly set during installation and preparing data.
The training on SUN-SEG is conducted using 2 4090-24GB GPUs:
CUDA_VISIBLE_DEVICES=0,1 TORCH_NUM_WORKERS=8 python main.py --config_file output/VIS/sunseg/pvt/pvt.py --trainer_mode train_attmpt
- logs, checkpoints, predictions
| Backbone | Dataset | Dice | mIou | log | ckpt | predictions |
|---|---|---|---|---|---|---|
| PVTv2-B2 | SUN-SEG-Train | -- | -- | log | ckpt | -- |
| PVTv2-B2 | SUN-SEG-Hard-Testing | 0.876 | 0.805 | log | ckpt | mask predictions |
| PVTv2-B2 | SUN-SEG-Easy-Testing | 0.875 | 0.810 | log | ckpt | mask predictions |
| PVTv2-B2 | SUN-SEG-Hard-Unseen-Testing | 0.865 | 0.792 | log | ckpt | mask predictions |
| PVTv2-B2 | SUN-SEG-Easy-Unseen-Testing | 0.853 | 0.783 | log | ckpt | mask predictions |
| Res2Net-50 | SUN-SEG-Hard-Testing | 0.841 | 0.765 | log | ||
| Res2Net-50 | SUN-SEG-Easy-Testing | 0.843 | 0.774 | log | ||
| PVTv2-B2 | CVC612V | 0.933 | 0.877 | log | ||
| PVTv2-B2 | CVC300TV | 0.916 | 0.852 | log | ||
| PVTv2-B2 | CVC612T | 0.875 | 0.814 | log |
- Evaluate: Evaluating on SUN-SEG-Easy AND SUN-SEG-Hard using 1 4090-24GPU GPUS (modify the ckpt_path to the absolute path):
CUDA_VISIBLE_DEVICES=0 TORCH_NUM_WORKERS=8 python main.py --config_file output/VIS/sunseg/pvt/pvt.py --trainer_mode eval --eval_path ckpt_path
citing
@article{xu2024lgrnet,
title={LGRNet: Local-Global Reciprocal Network for Uterine Fibroid Segmentation in Ultrasound Videos},
author={Xu, Huihui and Yang, Yijun and Aviles-Rivero, Angelica I and Yang, Guang and Qin, Jing and Zhu, Lei},
journal={arXiv preprint arXiv:2407.05703},
year={2024}
}
Acknowledgments
- Thanks Gilbert for the implementation of Hilbert curve generation.
- Thanks GPT4 for helping me constructing idea of Hilbert Filling Curve v.s. Zigzag curve