Calibration

This project contains components to calibrate these types of sensor data:

• camera

• line profile (planned)

... and these types of actors:

• delta robot (planned)

How the project is configured

The calib-project was developed in Visual Studio Code. It is integrated in the KERNEL.ai-project. To open the calib project open Visual Studio Code using calib as base folder. This project uses an own environment based on Python 3.8 (64-bit). Therefore, an environment can be set up using the following command:

~\AppData\Local\Programs\Python\Python38\python.exe -m venv .venv

Activate your virtual Environment:

.\.venv\Scripts\Activate.ps1

All the needed python packages are listed in the requirements.txt-file. The packages can be install using this command:

pip install -r .\requirements.txt

Run the testcases

The testcases are written using unittest. The test-run is preconfigured in visual studio code by using the preinstalled testing extension. Just get sure, it is correctly enabled in the file .vscode/settings.json.

Run Linting

The linting has been enabled by installing the python module pycodestyle and is set in the file .vscode/settings.json. It is run each time a python file is stored.

Run Code Coverage

The code coverage is enabled by

• installing the python module coverage

• installing the extension ryanluker.vscode-coverage-gutters in VS Code

To watch the code coverage run the following code in the terminal:

coverage run -m unittest discover -s .\test\ -p 'unittests_*.py'
coverage xml -o coverage.xml -i

Executing the first command executes all the written test-cases in the test-folder and creates the .coverage-file. To use this analysis within Coverage Gutters it needs to be parsed into an xml-file by the second command.

Used resources

for camera calibration

The calibration module was built according to the tutorial provided via openCV:

OpenCV: Camera Calibration

The targets used for camera calibration can be created according to this tutorial:

OpenCV: Create calibration pattern

This tutorial explains the homography matrix: OpenCV: Basic concepts of the homography explained with code