复现VILG

（Ubuntu20.04  显卡驱动对应的cuda=12.0） （使用的cuda=11.0）

1.git clone https://github.com/xukechun/Vision-Language-Grasping.git

2.cd Vision-Language-Grasping

3.conda create -n vilg python=3.8

4.conda activate vilg

5.pip install -r requirements.txt

报错1：

× python setup.py egg_info did not run successfully.
│ exit code: 1
╰─> [18 lines of output]
The 'sklearn' PyPI package is deprecated, use 'scikit-learn'
rather than 'sklearn' for pip commands.

解决方法1：

export SKLEARN_ALLOW_DEPRECATED_SKLEARN_PACKAGE_INSTALL=True

报错2：

      ......
      gcc: error: ../common/maskApi.c: No such file or directory
      error: command '/usr/bin/gcc' failed with exit code 1
      [end of output]
  
  note: This error originates from a subprocess, and is likely not a problem with pip.
  ERROR: Failed building wheel for pycocotools
  Running setup.py clean for pycocotools
Failed to build pycocotools
ERROR: Could not build wheels for pycocotools, which is required to install pyproject.toml-based projects

解决方法2：

pip install cython==0.29.36

6.python setup.py develop

7.cd models/graspnet/pointnet2

8.python setup.py install

9.cd ../knn

10.python setup.py install

11.在下面网址下载assets文件夹；https://drive.google.com/drive/folders/1WxKDFXJktoqiP0jmkDZrMCcNNBx5u-YM?usp=drive_link

12.将整理为。
13.将这两个文件放在 Vision-Language-Grasping/assets/下面。

14.在下面网址下载模型预训练权重；

https://drive.google.com/drive/folders/1LCuoXX92X8L9wqJTbVqvskjRhTJrDDay

15.运行train.py 或  test.py即可。