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129 lines
5.1 KiB
Markdown
Executable File
129 lines
5.1 KiB
Markdown
Executable File
## 项目简介
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Video-subtitle-remover (vsr) 是一款基于AI技术，将视频中的硬字幕去除的软件。
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## 演示
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<p style="text-align:center;"><img src="https://github.com/YaoFANGUK/video-subtitle-remover/raw/main/design/demo.gif" alt="demo.gif"/></p>
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## 源码使用说明
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#### 1. 下载安装Miniconda
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- Windows: <a href="https://repo.anaconda.com/miniconda/Miniconda3-py38_4.11.0-Windows-x86_64.exe">Miniconda3-py38_4.11.0-Windows-x86_64.exe</a>
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- MacOS：<a href="https://repo.anaconda.com/miniconda/Miniconda3-py38_4.11.0-MacOSX-x86_64.pkg">Miniconda3-py38_4.11.0-MacOSX-x86_64.pkg</a>
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- Linux: <a href="https://repo.anaconda.com/miniconda/Miniconda3-py38_4.11.0-Linux-x86_64.sh">Miniconda3-py38_4.11.0-Linux-x86_64.sh</a>
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#### 2. 创建并激活虚机环境
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（1）切换到源码所在目录：
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```shell
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cd <源码所在目录>
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```
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> 例如：如果你的源代码放在D盘的tools文件下，并且源代码的文件夹名为video-subtitle-remover，就输入 ```cd D:/tools/video-subtitle-remover-main```
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（2）创建激活conda环境
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```shell
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conda create -n videoEnv python=3.8
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```
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```shell
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conda activate videoEnv
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```
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#### 3. 安装依赖文件
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请确保你已经安装 python 3.8+，使用conda创建项目虚拟环境并激活环境 (建议创建虚拟环境运行，以免后续出现问题)
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- GPU用户(有N卡)：
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- 安装CUDA和cuDNN
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<details>
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<summary>Linux用户</summary>
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<h5>(1) 下载CUDA 11.7</h5>
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<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>
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<h5>(2) 安装CUDA 11.7</h5>
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<pre><code>sudo sh cuda_11.7.0_515.43.04_linux.run</code></pre>
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<p>1. 输入accept</p>
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<img src="https://i.328888.xyz/2023/03/31/iwVoeH.png" width="500" alt="">
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<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>
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<img src="https://i.328888.xyz/2023/03/31/iwVThJ.png" width="500" alt="">
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<p>3. 添加环境变量</p>
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<p>在 ~/.bashrc 加入以下内容</p>
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<pre><code># CUDA
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export PATH=/usr/local/cuda-11.7/bin${PATH:+:${PATH}}
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export LD_LIBRARY_PATH=/usr/local/cuda-11.7/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}</code></pre>
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<p>使其生效</p>
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<pre><code>source ~/.bashrc</code></pre>
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<h5>(3) 下载cuDNN 8.4.1</h5>
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<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>
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<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>
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<h5>(4) 安装cuDNN 8.4.1</h5>
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<pre><code> tar -xf cudnn-linux-x86_64-8.4.1.50_cuda11.6-archive.tar.xz
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mv cudnn-linux-x86_64-8.4.1.50_cuda11.6-archive cuda
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sudo cp ./cuda/include/* /usr/local/cuda-11.7/include/
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sudo cp ./cuda/lib/* /usr/local/cuda-11.7/lib64/
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sudo chmod a+r /usr/local/cuda-11.7/lib64/*
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sudo chmod a+r /usr/local/cuda-11.7/include/*</code></pre>
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</details>
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<details>
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<summary>Windows用户</summary>
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<h5>(1) 下载CUDA 11.7</h5>
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<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>
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<h5>(2) 安装CUDA 11.7</h5>
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<h5>(3) 下载cuDNN 8.2.4</h5>
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<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>
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<h5>(4) 安装cuDNN 8.2.4</h5>
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<p>
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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
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</p>
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</details>
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- 安装paddlepaddle:
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- windows:
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```shell
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python -m pip install paddlepaddle-gpu==2.4.2.post117 -f https://www.paddlepaddle.org.cn/whl/windows/mkl/avx/stable.html
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```
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- Linux:
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```shell
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python -m pip install paddlepaddle-gpu==2.4.2.post117 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html
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```
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> 如果安装cuda 10.2，请对应安装7.6.5的cuDNN，并使用对应cuda版本的paddlepaddle，**请不要使用cuDNN v8.x 和 cuda 10.2的组合**
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> 如果安装cuda 11.2，请对应安装8.1.1的cuDNN，并使用对应cuda版本的paddlepaddle，**30系列以上的显卡驱动可能不支持 cuda 11.2及以下版本的安装**
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- 安装其他依赖:
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```shell
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pip install -r requirements.txt
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```
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#### 4. 运行程序
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- 运行命令行版本(CLI)
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```shell
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python ./backend/main.py
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```
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