This is a pipeline for HSL's LOST image generation project. Our objective is to build a pipeline that can be used for testing how suboptimal image conditions (motion blur, noise, random obstruction, etc.) affect the accuracy of our star tracker. At a high level, this pipeline:
- Calls LOST to determine attitude of an initial image
- Applies an image transformation on initial image
- Calls LOST to determine attitude of transformed image
- Compares determined attitudes to see if filtered image has been successfully identified within a percent error of the unfiltered image
Make sure you have run git clone for the LOST directory somewhere on your device. git clone this repository. Make sure the calls to make_clean_make() and generate_database in main.py's main method are not commented out during your first run (you can comment them out in later runs for efficiency), and run python3 main.py.