Linux Source Code Deployment

0. It is recommended to use miniconda on Linux for source code deployment to 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
   • After the download is complete, continue to execute: bash Miniconda3-py310_24.5.0-0-Linux-x86_64.sh
   • Next, some agreements or guides will be displayed. You need to enter yes or press Enter to continue.
   • After the prompt is completed, 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 another location, 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, enter yes and then press Enter.

2. Activate the virtual environment. Execute the command conda activate videotrans

3. Create an empty folder for deploying the source code. Assuming you have created /data/pyvideo, 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 and wait for the prompt to complete.

5. Install ffmpeg. Execute yum install ffmpeg under CentOS, and 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 including the word samplerate. This is a pip module that needs to be installed by compiling the source code. It is very easy to fail during compilation and cause 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 indicates that the `c++/cmake` version is too low and needs to be upgraded. Next, execute the following commands. If it is a `centos` series, execute the following respectively:

yum update
yum clean all
yum remove devtoolset-8
yum 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 pip installation is very slow, consider switching to the Aliyun 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 Aliyun mirror source may be missing some module versions. 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 content inside, and the official source will be restored.

3. Use CUDA Acceleration, Execute Separately

Example

pip3 uninstall -y torch torchaudio

pip3 install torch torchaudio --index-url https://download.pytorch.org/whl/cu126

pip3 install nvidia-cublas-cu12 nvidia-cudnn-cu12