Guidance Needed to Train/Extend BlazeFace for Additional Classes in STM32N6 Face Landmark Pipeline
Hello ST Community,
We are currently using the x-cube-n6-ai-face-landmarks pipeline on the STM32N6570-DK.
We now want to extend the BlazeFace stage so that it can detect additional DMS-related classes along with face detection.
The classes we are interested in are:
Phone, Seatbelt, Smoking, Face, Drinking.
At present, the BlazeFace model used in the ST face-landmark project is a single-class face detector, and we could not find a public ST training pipeline for retraining or extending this specific BlazeFace model.
Is there any ST example or reference repository for training BlazeFace on:
- WIDER FACE,
- custom datasets,
- or custom multi-class datasets?
Our goal is ideally to reduce the number of separate detection models while keeping the existing face-landmark pipeline functional on STM32N6570-DK.
Any guidance on the recommended training flow, supported model architecture, or available reference code would be very helpful.
