README.md

Arduino TinyML Digits Recognition

Arduino TinyML project that uses a machine learning model to recognize digits in the camera feed, the model was trained using the MNIST dataset.

Link to the Edge Impulse project

Demo

Tested Devices

The project has been tested on the following devices:

• Arduino Nano 33 BLE Sense with OV7675 camera

How to Run

Download the project in ZIP format and add it to Arduino IDE using Sketch -> Include Library -> Add .ZIP Library....
Once the library has been added, go to File -> Examples. You should see an entry within the list named martishin-mnist_inferencing. Select it and click nano_ble33_sense -> nano_ble33_sense_camera to load the project.

Use the Arduino IDE to build and upload the project. Once it is running, you can see inference results using Serial Monitor:

Starting inferencing in 2 seconds...
Taking photo...
Predictions (DSP: 15 ms., Classification: 744 ms., Anomaly: 0 ms.): 
Predictions:
  0: 0.03906
  1: 0.03125
  2: 0.00391
  3: 0.00000
  4: 0.03125
  5: 0.02344
  6: 0.02734
  7: 0.83594
  8: 0.00391
  9: 0.00391

In this case, digit 7 was shown on the phone to the connected camera, the number after each digit is its score (confidence).