1. Repository

After successfully installing kitcar-machine-learning. You are now confronted with our repository. Before going into any details, we will now take a step back and look at the repository’s structure.

1.1. Root

When opening the repository in a file browser you will see the following files and directories:

.
├── data
├── docker
├── docs
├── gitlab-ci
├── init
├── kitcar_ml
├── README.rst
└── pyproject.toml

6 directories, 2 files

1.2. Docs

The docs/ directory contains our documentation. We use Sphinx and better-apidoc to easily create a nice documentation.

Tip

The Onboarding is also part of our documentation. You can be find the source code of this page at docs/content/onboarding/repository.rst.

1.3. Init

The init/ directory contains files and scripts to install and setup this repository. You’ve already used the init/init.sh when following our installation guide.

1.4. Machine Learning

Interesting things happen in kitcar_ml/. Here, we write our machine learning code. Let’s take a closer look:

kitcar_ml
├── onboarding
│   ├── test
│   ├── __init__.py
│   ├── model.py
│   ├── script.py
│   └── setup.py
├── traffic_sign_detection
│   ├── configs
│   ├── fasterrcnn
│   ├── ssd
│   ├── yolov5
│   ├── __init__.py
│   └── detection_model.py
├── utils
│   ├── data
│   ├── data_generation
│   ├── evaluation
│   ├── models
│   ├── pre_processing
│   ├── test
│   ├── __init__.py
│   ├── benchmark.py
│   ├── bounding_box.py
│   └── visualization.py
└── __init__.py

14 directories, 11 files

1.4.1. Models

We have subdirectories in kitcar_ml/ for each problem we want to solve with machine learning.

For example there is a folder kitcar_ml/traffic_sign_detection which contains our models for solving the traffic sign detection.

Within kitcar_ml/traffic_sign_detection there is a folder foreach model we have to solve the traffic sign detection.

1.4.2. Utils

Utils packages are located in kitcar_ml/utils.

1.4.3. Onboarding

Onboarding files and scripts are located in kitcar_ml/onboarding.