MemSAM

MemSAM: Taming Segment Anything Model for Echocardiography Video Segmentation, CVPR 2024

Xiaolong Deng^, Huisi Wu*, Runhao Zeng, Jing Qin

Installation

conda create --name memsam python=3.10
conda activate memsam
pip install torch torchvision --index-url https://download.pytorch.org/whl/cu118
pip install requirements.txt

Usage

prepare dataset

First, download the dataset from:

• CAMUS
• EchoNet-Dynamic

Then process the dataset according to utils/preprocess_echonet.py and utils/preprocess_camus.py.

pretrain checkpoint download

ViT-B SAM model

train and test

Use train_video.py and test_video.py to train and test separately.

Acknowledgement

The work is based on SAM, SAMUS and XMem. Thanks for the open source contributions to these efforts!

ref https://github.com/dengxl0520/MemSAM