VCF [2] is a Python [1] application1 that implements a collection of algorithms used in image and video compression. VCF is hosted at GitHub and developed with the help of the students of Sistemas Multimedia.
VCF modules should run on any machine with a Python interpreter installed. Said that, it is recommended to use Linux or a UNIX-based OS (such as Apple OS). However, with some configuration effort (for example, after installing Python), VCF should run also in Windows.
Running VCF natively is the preferred solution. However, notice that in Windows the Windows Subsystem for Linux (WSL) is also available.
The second most convinient option in terms of computational requirements and speed is to run Linux in a container, such as the provided by Docker ( example for Ubuntu) or LXD. Notice, however, that you will need to run graphical applications (such as ImageMagick and Firefox) in your container.
VCF works also in any Linux installed in a virtual machine (VM) , such as Virtual Box, VMware and Parallels. The only drawback of this option is that you will require some extra memory and CPU power, compared to the previous solutions.
In this category also fall cloud notebook services, such as Google Colaboratory, Binder, and Kaggle, that allow to install Python packages and run shell scripts.
The most convenient way of developping a Python application is using a Python environment:
python3 -m venv VCF source VCF/bin/activate # In Linux and OSX # VCF\Scripts\activate.bat # In Windows using cmd.exe # VCF\\Scripts\Activate.ps1 # In Windows using PowerShell
VCF is hosted by GitHub throughout Git [3].
See the VFC’s README.md file.
[1] The Python Foundation. The Python Website.
[2] V. González-Ruiz. Visual Coding Framework.
[3] V. González-Ruiz. Using GitHub.
1In fact, VCF is a collection of Python modules running as scripts.