FLLMachineLearning

Source code for recording data to train color detection machine learning models on EV3 and Spike Prime kits

Installation

For EV3

1. Follow the PyBricks installation guide here
2. Install VS Code and the ev3Dev extension
3. Clone this repository in VS Code

For Spike Prime

1. Create a new python Spike Prime project
2. Clone this repository to your computer
3. Copy the contents of main.py to the project

NOTE

The spike prime app console is unable to process much data, so you may need to collect data in smaller increments of ~20 readings (I spent an entire night trying to circumvent this limitation, there is no official solution)

Editing the project

4. Remove the pybricks shebang if you are using spike prime

#!/usr/bin/env pybricks-micropython

5. edit sensorsToCheck to include the ones you use
6. edit trainableColors to include color options

Usage

1. Run the project
2. Check the EV3 screen or Spike Prime console for instructions
3. Place your color sensors on the first color
4. move through the options to select the first color you want to train
5. move your robot around slightly while still staying on the color
6. press the stop button once you've got enough data (~1000 entries per color which can be split over multiple readings at multiple times of day and if possible multiple boards)
7. Copy the stuff in between the square brackets into a file with the format colorname.json ie.

[{"id": "Port.S1", "reflectivity": 13, "truth": "Black", "blue": 10, "classification": "Black", "ambient": -73, "red": 12, "green": 13}, {"id": "Port.S1", "reflectivity": 12, "truth": "Black", "blue": 9, "classification": "Black", "ambient": 1, "red": 11, "green": 12},...]

8. Repeat with all your colors

Machine Learning

Upload all your .json files to a google drive folder and open this Google Colab instance

License

Boost Software License 1.0

You can redistribute, reproduce, modify, and sell this software as long as you also use the BSL license and give some credit