Skip to content

Commit

Permalink
更新依赖至python3.12
Browse files Browse the repository at this point in the history
  • Loading branch information
@YaoFANGUK
YaoFANGUK committed Sep 29, 2024
1 parent e366e97 commit 5e1c816
Show file tree
Hide file tree
Showing 100 changed files with 31,317 additions and 216 deletions.
132 changes: 62 additions & 70 deletions README.md
View file
Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,7 @@
## 项目简介

![License](https://img.shields.io/badge/License-Apache%202-red.svg)
![python version](https://img.shields.io/badge/Python-3.8+-blue.svg)
![python version](https://img.shields.io/badge/Python-3.12+-blue.svg)
![support os](https://img.shields.io/badge/OS-Windows/macOS/Linux-green.svg)

Video-subtitle-extractor (VSE) 是一款将视频中的硬字幕提取为外挂字幕文件(srt格式)的软件。
Expand Down Expand Up @@ -111,13 +111,13 @@ Video-subtitle-extractor (VSE) 是一款将视频中的硬字幕提取为外挂

#### 1. 下载安装Miniconda

- 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>
- Windows: <a href="https://repo.anaconda.com/miniconda/Miniconda3-py312_24.7.1-0-Windows-x86_64.exe">Miniconda3-py312_24.7.1-0-Windows-x86_64.exe</a>


- 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>
- MacOS：<a href="https://repo.anaconda.com/miniconda/Miniconda3-py312_24.7.1-0-MacOSX-x86_64.pkg">Miniconda3-py312_24.7.1-0-MacOSX-x86_64.pkg</a>


- 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>
- Linux: <a href="https://repo.anaconda.com/miniconda/Miniconda3-py312_24.7.1-0-Linux-x86_64.sh">Miniconda3-py312_24.7.1-0-Linux-x86_64.sh</a>

#### 2. 创建并激活虚机环境

Expand All @@ -129,7 +129,7 @@ cd <源码所在目录>
（2）创建激活conda环境
```shell
conda create -n videoEnv python=3.8
conda create -n videoEnv python=3.12
```

```shell
Expand All @@ -138,86 +138,78 @@ conda activate videoEnv

#### 3. 安装依赖文件

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)

- CPU用户 (Mac用户) :

- 安装依赖：
```shell
pip install -r requirements.txt
```

- GPU用户(有N卡)： **要达到高精度的识别率请使用GPU版**
请确保你已经安装 python 3.12+，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)

- 安装其他依赖:

```shell
pip install -r requirements.txt
```

- 安装CUDA和cuDNN

<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>
<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>
<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>
<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>
</details>

- 安装CUDA和cuDNN

<details>
<summary>Linux用户</summary>
<details>
<summary>Windows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>
<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>
<pre><code>sudo sh cuda_11.7.0_515.43.04_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>
<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>
<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 8.2.4</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>
<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
</p>
</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>
<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
</p>
</details>


- 安装paddlepaddle:
- 安装paddlepaddle:

- windows:
- windows:

```shell
python -m pip install paddlepaddle-gpu==2.4.2.post117 -f https://www.paddlepaddle.org.cn/whl/windows/mkl/avx/stable.html
```
```shell
python -m pip install paddlepaddle-gpu==2.6.1.post117 -f https://www.paddlepaddle.org.cn/whl/windows/mkl/avx/stable.html
```

- Linux:
- 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.post117 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html
```

> 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**

> 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**


- 安装其他依赖:

```shell
pip install -r requirements_gpu.txt
```



#### 4. 运行程序
Expand Down
130 changes: 61 additions & 69 deletions README_en.md
View file
Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,7 @@
## Introduction

![License](https://img.shields.io/badge/License-Apache%202-red.svg)
![python version](https://img.shields.io/badge/Python-3.8+-blue.svg)
![python version](https://img.shields.io/badge/Python-3.12+-blue.svg)
![support os](https://img.shields.io/badge/OS-Windows/macOS/Linux-green.svg)

**Video-subtitle-extractor** (VSE) is a free, open-source tool which can help you rip the hard-coded subtitles from videos and automatically generate corresponding **srt** files for each video. It includes the following implementations:
Expand Down Expand Up @@ -92,11 +92,14 @@

#### 1. Download and Install Miniconda

- 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>

- 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>
- Windows: <a href="https://repo.anaconda.com/miniconda/Miniconda3-py312_24.7.1-0-Windows-x86_64.exe">Miniconda3-py312_24.7.1-0-Windows-x86_64.exe</a>

- 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>

- MacOS：<a href="https://repo.anaconda.com/miniconda/Miniconda3-py312_24.7.1-0-MacOSX-x86_64.pkg">Miniconda3-py312_24.7.1-0-MacOSX-x86_64.pkg</a>


- Linux: <a href="https://repo.anaconda.com/miniconda/Miniconda3-py312_24.7.1-0-Linux-x86_64.sh">Miniconda3-py312_24.7.1-0-Linux-x86_64.sh</a>


#### 2. Activate Vitrual Environment
Expand All @@ -108,7 +111,7 @@ cd <your source code path>

(2) create and activate conda environment
```shell
conda create -n videoEnv python=3.8 pip
conda create -n videoEnv python=3.12 pip
```

```shell
Expand All @@ -120,86 +123,75 @@ conda activate videoEnv

Before you install dependencies, make sure your python 3.8+ has installed as well as conda virtual environment has created and activated.

- For users who have CPU only (including Mac users):

- Install dependencies：

```shell
pip install -r requirements.txt
```


- For users who have **NVIDIA** graphic card： **GPU version can achieve better accuracy**

- Install **CUDA** and **cuDNN**

<details>
<summary>Linux</summary>
<h5>(1) Download 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) Install CUDA 11.7</h5>
<pre><code>sudo sh cuda_11.7.0_515.43.04_linux.run</code></pre>
<p>1. Input accept</p>
<img src="https://i.328888.xyz/2023/03/31/iwVoeH.png" width="500" alt="">
<p>2. make sure CUDA Toolkit 11.7 is chosen (If you have already installed driver, do not select Driver)</p>
<img src="https://i.328888.xyz/2023/03/31/iwVThJ.png" width="500" alt="">
<p>3. Add environment variables</p>
<p>add the following content in <strong>~/.bashrc</strong></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>
<p>Make sure it works</p>
<pre><code>source ~/.bashrc</code></pre>
<h5>(3) Download cuDNN 8.4.1</h5>
<p><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) Install 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>
</details>

<details>
<summary>Windows</summary>
<h5>(1) Download 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) Install CUDA 11.7</h5>
<h5>(3) Download 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) Install cuDNN 8.2.4</h5>
<p>
unzip "cudnn-windows-x64-v8.2.4.15.zip", then move all files in "bin, include, lib" in cuda
directory to C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\
</p>
</details>
- Install dependencies：

```shell
pip install -r requirements.txt
```

- Install **CUDA** and **cuDNN**
> make sure that you have **NVIDIA** graphic card before doing this step
<details>
<summary>Linux</summary>
<h5>(1) Download 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) Install CUDA 11.7</h5>
<pre><code>sudo sh cuda_11.7.0_515.43.04_linux.run</code></pre>
<p>1. Input accept</p>
<img src="https://i.328888.xyz/2023/03/31/iwVoeH.png" width="500" alt="">
<p>2. make sure CUDA Toolkit 11.7 is chosen (If you have already installed driver, do not select Driver)</p>
<img src="https://i.328888.xyz/2023/03/31/iwVThJ.png" width="500" alt="">
<p>3. Add environment variables</p>
<p>add the following content in <strong>~/.bashrc</strong></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>
<p>Make sure it works</p>
<pre><code>source ~/.bashrc</code></pre>
<h5>(3) Download cuDNN 8.4.1</h5>
<p><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) Install 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>
</details>

<details>
<summary>Windows</summary>
<h5>(1) Download 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) Install CUDA 11.7</h5>
<h5>(3) Download 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) Install cuDNN 8.2.4</h5>
<p>
unzip "cudnn-windows-x64-v8.2.4.15.zip", then move all files in "bin, include, lib" in cuda
directory to C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7\
</p>
</details>


- Install 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
python -m pip install paddlepaddle-gpu==2.6.1.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
python -m pip install paddlepaddle-gpu==2.6.1.post117 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html
```

> If you installed cuda 10.2，please install cuDNN 7.6.5 instead of cuDNN v8.x

> If you installed cuda 11.2, please install cuDNN 8.1.1. However, RTX 30xx might be incompatible with cuda 11.2

- Install other dependencies:

```shell
pip install -r requirements_gpu.txt
```




#### 3. Running the program

Expand Down
6 changes: 3 additions & 3 deletions backend/config.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,7 @@
import time
from pathlib import Path
from fsplit.filesplit import Filesplit
from paddle import fluid
import paddle
from tools.constant import *


Expand Down Expand Up @@ -71,9 +71,9 @@
# 是否使用GPU
USE_GPU = False
# 如果paddlepaddle编译了gpu的版本
if fluid.is_compiled_with_cuda():
if paddle.is_compiled_with_cuda():
# 查看是否有可用的gpu
if len(fluid.cuda_places()) > 0:
if len(paddle.static.cuda_places()) > 0:
# 如果有GPU则使用GPU
USE_GPU = True
# ×××××××××××××××××××× [不要改]判断是否使用GPU start ××××××××××××××××××××
Expand Down
1 change: 1 addition & 0 deletions backend/ppocr/ext_op/__init__.py
View file
Original file line number Diff line number Diff line change
@@ -0,0 +1 @@
from .roi_align_rotated.roi_align_rotated import RoIAlignRotated
Loading

0 comments on commit 5e1c816

Please sign in to comment.