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Meter Reader with Grove - Vision AI

This tutorial will demonstrate the development process of meter reader 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 meter reading feature is based on the PFLD model, in this step you need a PFLD 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 meter reading, in this step you need to compile and flash the firmware to the Grove - Vision AI modules. Please refer to Grove - Deployment - Compile and Deploy to complete the deployment of the model.

Run Example

After completing the Grove - Deployment Tutorial - Compile and Deploy - Deployment Routines, you need to do a manual calibration in the Grove Vision AI Console to get the correct meter readings, which is mainly divided into three steps:

  1. Set 3 points: center point, start point and end point.

  2. Set the first and last digit of the meter to set the measurement range.

  3. Configure the number of decimal places.

The above steps are graphically indicated in the console, and finally, you can see the real-time meter reading results as shown in the figure below.

PFLD Meter Reader

Released under the MIT License