This repository contains the implementation of our paper "H2Former: An Efficient Hierarchical Hybrid Transformer for Medical Image Segmentation"
python 3.6
numpy 1.16.4
Pytorch 1.8.1
pillow 7.0.0
opencv-python 4.1.0
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Clone the repository, and download the pre-trained ImaenNet model, put them into ./ folder. The details of the training are in train.py file.
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And then run the code：python train.py Note that the parameters and paths should be set beforehand
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Once the training is complete, you can run the test.py to test your model. Run the code : python test.py.
Code can only be used for ACADEMIC PURPOSES. NO COMERCIAL USE is allowed. Copyright © College of Computer Science, Nankai University. All rights reserved.
数据训练的.txt文件只是文件名，代表的是哪些文件是训练集，哪些是测试集，代码中只是给了一个示例，具体的读取还是通过对数据的标签、图像直接读取。 四种病变的标签是放在同一个mask中，跟普通语义分割一样，四种病变用1,2,3,4代表就行，背景用0代表就可以。