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本来根据原文的readme,应该是可以一行代码配置环境的,但是我在配置时出现了一些问题,比如cuda版本不匹配等,由于我之前就在电脑上安装了cuda11.8,但是根据他的要求,torch1.x.x之支持最高cuda11.7的版本。
gaussian-splattinghttps://github.com/graphdeco-inria/gaussian-splatting看issue发现有一些安装cuda11.7解决了问题的,但是这个方法我需要重新安装cuda。
后来在readme中,发现这样一段话。
If you can afford the disk space, we recommend using our environment files for setting up a training environment identical to ours. If you want to make modifications, please note that major version changes might affect the results of our method. However, our (limited) experiments suggest that the codebase works just fine inside a more up-to-date environment (Python 3.8, PyTorch 2.0.0, CUDA 12). Make sure to create an environment where PyTorch and its CUDA runtime version match and the installed CUDA SDK has no major version difference with PyTorch's CUDA version.
于是,打算试一下安装最新版的torch,安装下面安装即可:
先下载源码:
- git clone https://github.com/graphdeco-inria/gaussian-splatting.git
-
- cd gaussian-splatting
然后配置环境:
- conda create --name gaussian_splatting
-
- conda activate gaussian_splatting
conda install pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia
conda install tqdm
pip install plyfile==0.8.1
conda install cudatoolkit=11.8
pip install submodules/diff-gaussian-rasterization
pip install submodules/simple-knn
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