This projects aims to create a program to make images and videos safe to upload under strict data protection laws.
Start the UI by installing the conda environment and executing the module:
conda env create --name NumberPlateRecognition --file=environment.yml
python -m safe_video
Useful examples for working with the package can be found in the Jupyter Notebook test.ipynb
- YOLO standard model: is imported automatically
- License_Plate model: is imported automatically (from
/models/first10ktrain/weights/licensePlate.pt) - face model: best performing model can be imported from
/models/face_recognition/weights/best.pt - text recognition model: best performing model can be imported from
/models/text/weights/text.pt
- Always create a new brach for a new feature. Use the first letter of your name as the start of the branch name (e.g. c-topic)
- Use typing for all functions and classes
All the dependencies for this project are saved in the environment.yml file for a conda environment. Use
conda env create --name NumberPlateRecognition --file=environment.yml
to create the conda environment. Use ctrl+shift+p and search for python:Select Interpreter to select the environment as interpreter in vs code.
When installing new packages create a new file with:
conda env export > environment.yml
To update your conda environment with the new file use:
conda env update --file environment.yml --prune