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Mask Detection with Grove - Vision AI

This tutorial will demonstrate the development process of mask detection using SSCMA based on Grove - Vision AI module.

TIP

Before starting, we recommend that you should read Grove - Deploy first.

Preparation

Please refer to Grove - Deploy - Prerequisites.

Train Model

The mask detection feature is based on the FOMO model, in this step you need a FOMO model weight with the suffix .pth, you have two ways to get the model weight.

Export Model

Since the trained model is not suitable for running directly on edge computing devices, we need to export it to a TFLite format with a .tflite suffix, and you have two ways to get the exported model (with model weights contained).

Deploy Model

This is the last and most important step to complete the mask detection, in this step you need to compile and flash the firmware to the Grove - Vision AI module. Please refer to Grove - Deployment - Compile and Deploy to complete the deployment of the model.

Released under the MIT License