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@@ -80,69 +80,61 @@ conda activate videoEnv
<details>
<summary>Linux用户</summary>
<h5>(1) 下载CUDA 11.7</h5>
<pre><code>wget https://developer.download.nvidia.com/compute/cuda/11.7.0/local_installers/cuda_11.7.0_515.43.04_linux.run</code></pre>
<h5>(2) 安装CUDA 11.7</h5>
<pre><code>sudo sh cuda_11.7.0_515.43.04_linux.run</code></pre>
<h5>(1) 下载CUDA 11.8</h5>
<pre><code>wget https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda_11.8.0_520.61.05_linux.run</code></pre>
<h5>(2) 安装CUDA 11.8</h5>
<pre><code>sudo sh cuda_11.8.0_520.61.05_linux.run</code></pre>
<p>1. 输入accept</p>
<img src="https://i.328888.xyz/2023/03/31/iwVoeH.png" width="500" alt="">
<p>2. 选中CUDA Toolkit 11.7（如果你没有安装nvidia驱动则选中Driver，如果你已经安装了nvidia驱动请不要选中driver），之后选中install，回车</p>
<p>2. 选中CUDA Toolkit 11.8（如果你没有安装nvidia驱动则选中Driver，如果你已经安装了nvidia驱动请不要选中driver），之后选中install，回车</p>
<img src="https://i.328888.xyz/2023/03/31/iwVThJ.png" width="500" alt="">
<p>3. 添加环境变量</p>
<p>在 ~/.bashrc 加入以下内容</p>
<pre><code># CUDA
export PATH=/usr/local/cuda-11.7/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-11.7/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}</code></pre>
export PATH=/usr/local/cuda-11.8/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-11.8/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}</code></pre>
<p>使其生效</p>
<pre><code>source ~/.bashrc</code></pre>
<h5>(3) 下载cuDNN 8.4.1</h5>
<p>国内：<a href="https://pan.baidu.com/s/1Gd_pSVzWfX1G7zCuqz6YYA">cudnn-linux-x86_64-8.4.1.50_cuda11.6-archive.tar.xz</a> 提取码：57mg</p>
<p>国外：<a href="https://github.com/YaoFANGUK/video-subtitle-extractor/releases/download/1.0.0/cudnn-linux-x86_64-8.4.1.50_cuda11.6-archive.tar.xz">cudnn-linux-x86_64-8.4.1.50_cuda11.6-archive.tar.xz</a></p>
<h5>(4) 安装cuDNN 8.4.1</h5>
<pre><code> tar -xf cudnn-linux-x86_64-8.4.1.50_cuda11.6-archive.tar.xz
mv cudnn-linux-x86_64-8.4.1.50_cuda11.6-archive cuda
sudo cp ./cuda/include/* /usr/local/cuda-11.7/include/
sudo cp ./cuda/lib/* /usr/local/cuda-11.7/lib64/
sudo chmod a+r /usr/local/cuda-11.7/lib64/*
sudo chmod a+r /usr/local/cuda-11.7/include/*</code></pre>
<h5>(3) 下载cuDNN 8.6.0</h5>
<p>国内：<a href="https://pan.baidu.com/s/1Gd_pSVzWfX1G7zCuqz6YYA">cudnn-linux-x86_64-8.6.0.163_cuda11-archive.tar.xz</a> 提取码：57mg</p>
<p>国外：<a href="https://github.com/YaoFANGUK/video-subtitle-remover/releases/download/1.0.0/cudnn-linux-x86_64-8.6.0.163_cuda11-archive.tar.xz">cudnn-linux-x86_64-8.6.0.163_cuda11-archive.tar.xz</a></p>
<h5>(4) 安装cuDNN 8.6.0</h5>
<pre><code> tar -xf cudnn-linux-x86_64-8.6.0.163_cuda11-archive.tar.xz
mv cudnn-linux-x86_64-8.6.0.163_cuda11-archive cuda
sudo cp ./cuda/include/* /usr/local/cuda-11.8/include/
sudo cp ./cuda/lib/* /usr/local/cuda-11.8/lib64/
sudo chmod a+r /usr/local/cuda-11.8/lib64/*
sudo chmod a+r /usr/local/cuda-11.8/include/*</code></pre>
</details>
<details>
<summary>Windows用户</summary>
<h5>(1) 下载CUDA 11.7</h5>
<a href="https://developer.download.nvidia.com/compute/cuda/11.7.0/local_installers/cuda_11.7.0_516.01_windows.exe">cuda_11.7.0_516.01_windows.exe</a>
<h5>(2) 安装CUDA 11.7</h5>
<h5>(3) 下载cuDNN 8.2.4</h5>
<p><a href="https://github.com/YaoFANGUK/video-subtitle-extractor/releases/download/1.0.0/cudnn-windows-x64-v8.2.4.15.zip">cudnn-windows-x64-v8.2.4.15.zip</a></p>
<h5>(4) 安装cuDNN 8.2.4</h5>
<h5>(1) 下载CUDA 11.8</h5>
<a href="https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda_11.8.0_522.06_windows.exe">cuda_11.8.0_522.06_windows.exe</a>
<h5>(2) 安装CUDA 11.8</h5>
<h5>(3) 下载cuDNN 8.6.0</h5>
<p><a href="https://github.com/YaoFANGUK/video-subtitle-remover/releases/download/1.0.0/cudnn-windows-x86_64-8.6.0.163_cuda11-archive.zip">cudnn-windows-x86_64-8.6.0.163_cuda11-archive.zip</a></p>
<h5>(4) 安装cuDNN 8.6.0</h5>
<p>
将cuDNN解压后的cuda文件夹中的bin, include, lib目录下的文件复制到C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\对应目录下
将cuDNN解压后的cuda文件夹中的bin, include, lib目录下的文件复制到C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\对应目录下
</p>
</details>
- 安装GPU版本Paddlepaddle:
- windows:
```shell
python -m pip install paddlepaddle-gpu==2.4.2.post117 -f https://www.paddlepaddle.org.cn/whl/windows/mkl/avx/stable.html
```
- Linux:
```shell
python -m pip install paddlepaddle-gpu==2.4.2.post117 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html
```
```shell
python -m pip install paddlepaddle-gpu==2.6.1 -i https://pypi.tuna.tsinghua.edu.cn/simple
```
- 安装GPU版本Pytorch:
```shell
conda install pytorch==2.0.1 torchvision==0.16.0 pytorch-cuda=11.8 -c pytorch -c nvidia
conda install pytorch==2.0.1 torchvision==0.15.2 pytorch-cuda=11.8 -c pytorch -c nvidia
```
或者使用
```shell
pip install torch==2.0.1 torchvision==0.16.0 --index-url https://download.pytorch.org/whl/cu118
pip install torch==2.0.1 torchvision==0.15.2 --index-url https://download.pytorch.org/whl/cu118
```
- 安装其他依赖: