Linux Source Code Deployment

0. It is recommended to use miniconda for installation and deployment on Linux to avoid many environment issues.

   • 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, 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.
   • Once the installation is complete, it's recommended to add it to the global environment so you can use the short command conda. By default, it might be installed in /root/miniconda3. If so, execute cp /root/miniconda3/bin/conda /usr/bin/conda. If it's in a different location, please adjust the path accordingly.
   • Close and reopen the terminal window for the changes to take effect.

1. Create a virtual environment with python3.10 by executing the command conda create -n videotrans python=3.10. If prompted, enter yes and press Enter.

2. Activate the virtual environment by executing the command conda activate videotrans

3. Create an empty folder for deploying the source code. Assuming /data/pyvideo has been created, navigate into the folder and clone the source code from GitHub. Execute the command git clone https://github.com/jianchang512/pyvideotrans .

4. Install the dependencies by executing the command pip install -r requirements.txt, and wait for it to complete.

5. Install ffmpeg. On CentOS, execute yum install ffmpeg. On Ubuntu, execute apt-get install ffmpeg

6. If there were no errors, execute python sp.py to launch the application or python api.py to run the API service.

Possible Errors During Installation

1. samplerate module installation failed

You may encounter an error containing the word samplerate. This is a pip module that requires compilation from source code. Compilation can easily fail on different system versions and environments, leading to errors. The error message will be 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 might also look like this:

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. Execute the following commands. If you are on a CentOS-based system, execute the following commands one by one:

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

After running the commands above, execute the following:

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

Then, re-run pip install -r requirements.txt.

2. Using 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