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Welcome to you if you're coming from Instructables!

MSc Project repo for computer vision star identification and satellite orientation project (CURRENTLY ACTIVE)

Please see a short explanatory video on YouTube.

Additionally, this tutorial is a really useful beginner's guide to OpenCV classifier training.

Contents so far:

  • Stellarium scripts used to capture thousands of images from Stellarium in order to be processed into negative image datasets for machine learning training.
  • Zipped folders containing negative image datasets, as well as bg.txt files, and python programs used to create these.
  • Python programs used to create the positive images used for cascade training.
  • Image files of the fiducial markers applied to starfields, to identify the patterns of bright stars that the machine learning relies upon for the identification.
  • A sample set of 31 trained cascades for the northern celestial hemisphere.
  • Python programs used to test the trained cascades against a supplied starfield image.

What next?:

19/08/19, I have finished working on this project as part of my University course. I hope to be able to spend further time on it as a hobby in order to keep developing the system, there are lots of improvements and additions I would like to have time to make. I hope that this repository may be of use to someone, and if you have questions please contact me, I will continue to monitor and work on this project. The best source of reference here is my MSc Thesis itself, which can be found above.

25/05/20, I've been putting more thought into the potential improvement and applications of this project. I hope that the Instructables writeup will help other people find this repo, and hopefully we can work together to develop this further!


MSc Project repo for computer vision star identification and satellite orientation project.







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