Decoupling Configuration from Code with YAML

 With the core performance issues addressed, I’ve shifted my focus to improving the pipeline's usability and maintainability. This week, I moved all the configuration parameters—such as cutout sizes, normalization methods, model paths, and detection thresholds—out of the Python code and into external YAML files.

This change allows researchers to easily experiment with different settings without having to modify the source code. It also makes the pipeline far more flexible and adaptable to different scientific use cases. It’s a crucial step in transforming the project from a custom script into a reusable and configurable scientific tool.