Clone this repository to your local computer.

git clone https://github.com/joelmwaka/CameraCalibration.git

Install requirements from the provided .txt files.

cd CameraCalibration
pip install -r requirements.txt

To execute the calibrator, ensure you have calibration images captured from the camera you intend to calibrate. Each calibration image must have a checkerboard in it.

Note: You can create your own checkerboard using this resource.

Execute the tool as follows:

python3 calibrator.py --path_to_images <PATH_TO_CALIBRATION_IMAGES> --path_to_results <PATH_TO_FOLDER_TO_SAVE_RESULTS> --pattern_shape <RxC> --square_size <SQUARE_SIZE>

The calibration results will be saved in a JSON file named calibration_results.json. This file will be saved in the folder you provided with the argument --path_to_results.

The JSON file contains the following results from the calibration:

• Root Mean Square Error (RMSE), rmse: a metric used to evaluate the accuracy of the calibration process.
• Intrinsic Camera Matrix, camera_matrix: the camera calibration with information about the focal length, principal point, and skew.
• Distortion Coefficients, distortion_coefficients: parameters for correction of camera lens distortion.

Note: Explanation of the intrinsic camera calibration and the distortion coefficients can be found on the OpenCV camera calibration page.