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Regarding tweaks:
* EWA smoothing of head ROI. Smoothing strength is a UI setting.
* Adjustible zoom into the detected face. The predicted ROI is scaled by a factor the user can set. There is a sweet spot somewhere near 1.
* Adjustible number of threads
* The ROI is no longer taken as model output directly. This was actually not needed. Perhaps as auxiliary training objective for the network. But the tracker implementation now just uses a square area around the head center according to the predicted head size.
* Add comment and debug notification on face ROI model output
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- Added support for MJPEG compression for neuralnet tracker
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Models were generated with code from
https://github.com/DaWelter/neuralnet-tracker-traincode/releases/tag/v0.1
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