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Project Introduction

Video-subtitle-remover (VSR) is an AI-based software that removes hardcoded subtitles from videos. It mainly implements the following functionalities:

• Lossless resolution: Removes hardcoded subtitles from videos and generates files without subtitles.
• Fills in the removed subtitle text area using a powerful AI algorithm model (non-adjacent pixel filling and mosaic removal).
• Supports custom subtitle positions by only removing subtitles in the defined location (input position).
• Supports automatic removal of all text throughout the entire video (without inputting a position).

Download the .7z package directly, extract, and run it. If it cannot run, follow the tutorial below to try installing the conda environment and running the source code.

Download Links:

Windows GPU Version v1.0.0 (GPU):

• Baidu Cloud Disk: vsr_windows_gpu_v1.0.0.7z Extraction Code: vsr1

• Google Drive: vsr_windows_gpu_v1.0.0.7z

For use only by users with Nvidia graphics cards (AMD graphics cards are not supported).

Demonstration

• GUI:

• Click to view demo video👇

Source Code Usage Instructions

Do not use this project without an Nvidia graphics card. The minimum requirements are:

GPU: GTX 1060 or higher graphics card

CPU: Supports AVX instruction set

1. Download and install Miniconda

• Windows: Miniconda3-py38_4.11.0-Windows-x86_64.exe

• Linux: Miniconda3-py38_4.11.0-Linux-x86_64.sh

2. Create and activate a virtual environment

(1) Switch to the source code directory:

cd <source_code_directory>

For example, if your source code is in the tools folder on drive D, and the source code folder name is video-subtitle-remover, enter cd D:/tools/video-subtitle-remover-main.

(2) Create and activate the conda environment:

conda create -n videoEnv python=3.8

conda activate videoEnv

3. Install dependencies

Please make sure you have already installed Python 3.8+, use conda to create a project virtual environment and activate the environment (it is recommended to create a virtual environment to run to avoid subsequent problems).

• Install CUDA and cuDNN

  Linux

  (1) Download CUDA 11.7

  wget https://developer.download.nvidia.com/compute/cuda/11.7.0/local_installers/cuda_11.7.0_515.43.04_linux.run

  (2) Install CUDA 11.7

  sudo sh cuda_11.7.0_515.43.04_linux.run

  1. Input accept

  

  2. make sure CUDA Toolkit 11.7 is chosen (If you have already installed driver, do not select Driver)

  

  3. Add environment variables

  add the following content in ~/.bashrc

  # 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}}

  Make sure it works

  source ~/.bashrc

  (3) Download cuDNN 8.4.1

  cudnn-linux-x86_64-8.4.1.50_cuda11.6-archive.tar.xz

  (4) Install cuDNN 8.4.1

   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/*

  Windows

  (1) Download CUDA 11.7

  cuda_11.7.0_516.01_windows.exe

  (2) Install CUDA 11.7

  (3) Download cuDNN 8.2.4

  cudnn-windows-x64-v8.2.4.15.zip

  (4) Install cuDNN 8.2.4

  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\

• Install GPU version of Paddlepaddle:

  • windows:

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

  • Linux:

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

• Install GPU version of Pytorch:

  conda install pytorch==2.0.1 torchvision==0.15.2 pytorch-cuda=11.7 -c pytorch -c nvidia
  

  or use

  pip install torch==2.0.1 torchvision==0.15.2 --index-url https://download.pytorch.org/whl/cu117
  

• Install other dependencies:

  pip install -r requirements.txt
  

4. Run the program

• Run the graphical interface

python gui.py

• Run the command line version (CLI)

python ./backend/main.py

Common Issues

1. CondaHTTPError

Place the .condarc file from the project in the user directory (C:/Users/<your_username>). If the file already exists in the user directory, overwrite it.

Solution: https://zhuanlan.zhihu.com/p/260034241

2. 7z file extraction error

Solution: Upgrade the 7-zip extraction program to the latest version.