Linux Source Code Deployment

0. It is recommended to use miniconda to install and deploy on Linux, which can avoid many environment problems.

• First install miniconda, open the terminal, and execute the command wget https://repo.anaconda.com/miniconda/Miniconda3-py310_24.5.0-0-Linux-x86_64.sh
• Wait for the download to complete, and then execute bash Miniconda3-py310_24.5.0-0-Linux-x86_64.sh
• Next, some agreements or guides will be displayed, and you need to enter yes or press Enter to continue.
• After waiting for the prompt to complete, it is recommended to add it to the global environment so that you can use the short command conda. The default may be installed under /root/miniconda3. If it is this command, please execute cp /root/miniconda3/bin/conda /usr/bin/conda, if it is in other locations, please replace it yourself
• Close the terminal window and reopen it for the environment to take effect.

1. Create a virtual environment using python3.10, execute the command conda create -n videotrans python=3.10, if prompted to enter, enter yes and press Enter.
2. Activate the virtual environment, execute the command conda activate videotrans
3. Create an empty folder for deploying the source code. Assuming that /data/pyvideo has been created, enter the folder and pull the source code from github, execute the command git clone https://github.com/jianchang512/pyvideotrans .
4. Install dependencies, execute the command pip install -r requirements.txt, wait for the prompt to complete
5. Install ffmpeg, execute yum install ffmpeg under centos, and execute apt-get install ffmpeg under ubuntu
6. If there are no errors, execute python sp.py to open the software, and execute python api.py to run the api service

Possible Errors During Installation

1. Samplerate module installation failed You may encounter an error that includes the word samplerate. This is a pip module that needs to be compiled from source code. It is extremely easy to fail to compile and report an error in different system versions and environments. The error code is similar to the following

-- Build files have been written to: /tmp/pip-install-0355nvxe/samplerate_f6c17d8f7ab94e0b9f8d7e16697c1ab3/build/temp.linux-x86_64-cpython-310/samplerate
  [ 14%] Building C object _deps/libsamplerate-build/src/CMakeFiles/samplerate.dir/samplerate.c.o
  [ 28%] Building C object _deps/libsamplerate-build/src/CMakeFiles/samplerate.dir/src_linear.c.o
  [ 42%] Building C object _deps/libsamplerate-build/src/CMakeFiles/samplerate.dir/src_sinc.c.o
  [ 57%] Building C object _deps/libsamplerate-build/src/CMakeFiles/samplerate.dir/src_zoh.c.o
  [ 71%] Linking C static library libsamplerate.a
  [ 71%] Built target samplerate
  [ 85%] Building CXX object CMakeFiles/python-samplerate.dir/src/samplerate.cpp.o
  c++: error: unrecognized command line option ‘-std=c++14’
  gmake[2]: *** [CMakeFiles/python-samplerate.dir/src/samplerate.cpp.o] Error 1
  gmake[1]: *** [CMakeFiles/python-samplerate.dir/all] Error 2
  gmake: *** [all] Error 2

The error may also be as follows

centos7 ImportError: /lib64/libstdc++.so.6: version `CXXABI_1.3.9' not found (required by /data2/conda/envs/pyvideo/lib/python3.10/site-packages/shiboken6/Shiboken.abi3.so)

This situation indicates that the c++/cmake version is too low and needs to be upgraded. Execute the following commands. For the centos series, execute the following separately

yum updateyum clean allyum remove devtoolset-8yum update libstdc++yum install devtoolset-8 devtoolset-9-libstdc++-devel scl-utils

After the execution is complete, continue to execute

export CFLAGS="-fPIC"export CXXFLAGS="-fPIC"

Then re-execute pip install -r requirements.txt

2. Pip mirror source problem

If the pip installation is very slow, you can consider switching to the Alibaba Cloud mirror source to speed up the installation. Execute the following 2 commands to switch the pip mirror to the Alibaba mirror, and then reinstall

pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/
pip config set install.trusted-host mirrors.aliyun.com

The Alibaba Cloud mirror source may lack versions of some modules. If you encounter this problem and want to switch back to the official default source, execute cd ~/.config/pip, open the pip.conf file, delete the contents inside, and you can restore the official source

3. To use CUDA acceleration, execute separately

pip uninstall -y torch torchaudio

pip install torch==2.2.0 torchaudio==2.2.0 --index-url https://download.pytorch.org/whl/cu118

pip install nvidia-cublas-cu11 nvidia-cudnn-cu11