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Identification of handwritten digit from images taken by a  OV7670 camera module connected to a Raspberry Pi Pico and a 120x160 TFT LCD display. The Pi Pico running CircuitPython handles everything from image acquisition to post-processing and inference. This code is somewhat experimental, but it is fun to play with. For more information, please…

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Handwritten digit classification using Raspberry Pi Pico and ML

Handwritten digit classification using Pi Pico and ML

A project using Raspberry Pi Pico, an OV7670 camera module, a 120x160 TFT LCD display and machine learning to build a portable handwritten digit classification system. This code is highly experimental. Even after you follow all the recommended steps in this article, some tinkering will still be necessary to get it to work.

Link to video demo of project: https://youtu.be/beKvz8K6b_4

To run the code

You will need following files on your CircuitPython board:

  • code.py
  • svm_min.py
  • Required libraries in lib folder. List of all library files you need for the project is present lib_folder_contents.txt
  • You will also need the Helvetica-Bold-16.bdf font file for running the code.

To setup hardware and wiring

For details about setting up the hardware and wiring, please visit: https://ashishware.com/2022/09/03/pipico_digit_classification/

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Identification of handwritten digit from images taken by a  OV7670 camera module connected to a Raspberry Pi Pico and a 120x160 TFT LCD display. The Pi Pico running CircuitPython handles everything from image acquisition to post-processing and inference. This code is somewhat experimental, but it is fun to play with. For more information, please…

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