An annotation tool for race swimming videos (using one or multiple static cameras).
- Create a virtual environment:
python -m venv venv- Activate the environment:
- On macOS/Linux:
source venv/bin/activate- On Windows:
venv\Scripts\activate- Install the module:
pip install --upgrade pip
pip install -r requirements.txtYou need to run 2 servers:
1/ A server to deliver the files:
python local.py 2/ Another server that hosts the web application:
python -m http.serverThen you can open your browser at http://localhost:8000
It is also possible to generate the site as an application with a simple command like this:
npm run build:<your_operating_system>
which allows you to use the site without a network connection.
To use the site locally, you need to pull the branch and go offline with competitions present in the courses_natation_local folder. (Start the folders with a 2 so they are detected, and keep the correct number of underscores _ to avoid display issues in the dropdown menus.)
Aquanote uses a specific data structure to store the annotations. It is based on a CSV file for each video, with samples provided in the course_demo folder. Another repository is dedicated to the analysis of such data: Aquanalysis.
All documentation can be viewed by launching the index file in the html folder, in particular the documentation for the main code located in /assets/js. This opens a page in your browser with sorted information about the code.
This documentation was automatically generated via Doxygen (the doxyfile contains its settings). It is not as effective for JavaScript as it is for other languages, so it relies heavily on comments (and their spelling mistakes).
This file is updated with every push, provided your branch is listed in the ci.yml file (./.github/workflows/ci.yml). After that, you just need to pull the branch.
Some folders are not visible in VS Code because they are hidden in .vscode/settings.json. This is meant to declutter the visible files, but feel free to modify this file.
