This repository contains all code for the TDT4290 project.
For more information on running the different codes, look at the README's inside the different folders.
| Module | Description | Readme link |
|---|---|---|
| Vehicle brand classification | Code to train and predict vehicle brands from images. | README.md |
| Vehicle color classification | Code to train and predict vehicle colors from images. | README.md |
| API | The API for receiving images and classifying them. Also contains the Dockerfile used when deploying the API. | README.md |
| Labeling script | The program to label images with the corresponding brand and color from license plates in images. | README.md |
To be able to run the project you need python 3.6 or higher.
When running the python code, it's recommend to use a virtual environment, but it is not required.
To setup a virtual environment, make sure that you have python3-venv installed.
The virtual environment can be initalized by running the commands:
python -m venv env
source env/bin/activate
To install the required modules, run the command:
pip install -r requirements.txt