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Because all the other solutions I have used are either unreliable or not user-friendly.
OpenCV is used for actually processing the videos. Avalonia is used to build the front end UI.
Right now, SharpEyes just finds the pupil. The saved eyetracking data is the same format as that ussd by the PupilFinder class in the Eyetracking repo. You can instantiate a SharpEyesCalibrator class in python, and then read the pupil location and timestamps files in. Then you can continue the analyses in python.
When, not if. This is a work in progress. Open an issue and describe the issue.
It targets .NET core 3.1. On Windows the program should run straight out of the box. On linux you will need to install a bunch of libraries including OpenCV and Tesseract. SharpEyes will tell you what's missing.
I built this on VS2022 and Jetbrains Rider
Everything runs on CPU and it frankly feels fast enough. The bottleneck here is the human checking the output. The code does make use of multithreading on CPU when it can.