Are you sure you want to delete this task? Once this task is deleted, it cannot be recovered.
zhoupzh 0bd3e1094b | 2 years ago | |
---|---|---|
Model | 2 years ago | |
checkpoint | 2 years ago | |
data | 2 years ago | |
testdata/nii | 2 years ago | |
.gitignore | 2 years ago | |
main.py | 2 years ago | |
npy_nii.py | 2 years ago | |
readme.txt | 2 years ago | |
sets.py | 2 years ago | |
test.py | 2 years ago |
Overview:
The goal of the code is to evaluate automated algorithms for COVID-19
segmented from CT images. The original dataset is from COVID-19 Lung
CT Lesion Segmentation Challenge。
How to use:
Dependencies:
This tutorial depends on the following libraries:
python>=3.0
torch
torchvision
numpy
Run main.py #eg python main.py
You will see the network training process.
Run test.py #eg python test.py
You will see the predicted results of test image in data.
#备注,由于显存限制,训练代码可能会报错内存溢出,测试代码应该正常。
Dear OpenI User
Thank you for your continuous support to the Openl Qizhi Community AI Collaboration Platform. In order to protect your usage rights and ensure network security, we updated the Openl Qizhi Community AI Collaboration Platform Usage Agreement in January 2024. The updated agreement specifies that users are prohibited from using intranet penetration tools. After you click "Agree and continue", you can continue to use our services. Thank you for your cooperation and understanding.
For more agreement content, please refer to the《Openl Qizhi Community AI Collaboration Platform Usage Agreement》