graph_classification:我的实验涉及使用Graph Neural Networks对超像素进行图分类和图像分类 源码
图分类实验 描述 它能做什么 怎么跑 一,安装依赖 # clone project git clone https://github.com/YourGithubName/your-repo-name cd your-repo-name # optionally create conda environment conda update conda conda env create -f conda_env.yaml -n your_env_name conda activate your_env_name # install requirements pip install -r requirements.txt pip install hydra-core --upgrade --pre 接下来,按照以下说明安装pytorch geometric: 现在,您可以使用默认配置训练模
文件列表
graph_classification-main.zip
(预估有个63文件)
graph_classification-main
project
logs
.gitkeep
0B
train.py
2KB
notebooks
.gitkeep
0B
superpixels_graph_visualisation.ipynb
580KB
superpixels_dataset_generation.ipynb
16KB
configs
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