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‎LICENSE

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‎README.adoc

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= Perceptron Library for Arduino =
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Arduino library for the Perceptron algorithm.
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== License ==
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Copyright (c) 2020 Arduino SA. All rights reserved.
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This library is free software; you can redistribute it and/or
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modify it under the terms of the GNU Lesser General Public
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License as published by the Free Software Foundation; either
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version 2.1 of the License, or (at your option) any later version.
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This library is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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Lesser General Public License for more details.
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You should have received a copy of the GNU Lesser General Public
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License along with this library; if not, write to the Free Software
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Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA

‎examples/Color_Perceptron/Color_Perceptron.ino

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/*
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Perceptron example
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Hardware: Arduino Nano BLE Sense
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Usage: Follow the prompts in the Serial Monitor and show two objects of different colors to the color sensor onboard the Arduino.
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The sketch will train a perceptron using these examples, and then classify objects you show it in the future.
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*/
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#include <Arduino_APDS9960.h>
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#include <Arduino_Perceptron.h>
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const int NUM_INPUTS = 3; // Classifier input is color sensor data; red, green and blue levels
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const int CLASSES = 2; // The perceptron only has 2 possible classes (-1 and 1)
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const int EXAMPLES = 50; // Number of samples for each object
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const int MAX_EPOCHS = 250; // Maximum training iterations
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const float LEARNING_RATE = 0.001; // Perceptron learning rate
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const int THRESHOLD = 5; // Color sensor light threshold
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float color[NUM_INPUTS];
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String label[CLASSES] = {"object A", "object B"};
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Perceptron perceptron(NUM_INPUTS, LEARNING_RATE);
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void setup() {
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Serial.begin(9600);
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while (!Serial);
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if (!APDS.begin()) {
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Serial.println("Failled to initialized APDS!");
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while (1);
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}
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Serial.println("Arduino perceptron");
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// Get examples for the two possible outputs, -1 and 1
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// ---------------------------------------------------
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for (int output = -1; output < 2; output += 2) {
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Serial.print("Show me ");
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printLabel(output);
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// Wait for the object to move away again
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while (!APDS.proximityAvailable() || APDS.readProximity() == 0) {}
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for (int n = 0; n < EXAMPLES; n++) {
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// Sample object color - perceptron input
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readColor(color);
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// Add example color to the perceptron training set
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perceptron.addExample(color, output);
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}
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}
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// Train the perceptron
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// --------------------
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Serial.println("\nTraining perceptron");
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int epoch = 0;
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float accuracy = 0;
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while (epoch < MAX_EPOCHS && accuracy < 0.99) {
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accuracy = perceptron.train();
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epoch++;
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Serial.print("Accuracy: ");
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Serial.println(accuracy);
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}
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Serial.println("Training complete\n");
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}
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void loop() {
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int output;
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// Wait for the object to move away again
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while (!APDS.proximityAvailable() || APDS.readProximity() == 0) {}
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Serial.println("Let me guess your object");
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// Wait for an object then read its color
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readColor(color);
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output = perceptron.classify(color);
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Serial.print("You showed me ");
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printLabel(output);
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}
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void printLabel(int output) {
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if (output == -1) {
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Serial.println(label[0]);
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} else {
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Serial.println(label[1]);
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}
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Serial.println();
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}
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void readColor(float color[]) {
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int red, green, blue, proximity, colorTotal = 0;
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// Wait until we have a color bright enough
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while (colorTotal < THRESHOLD) {
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// Sample if color is available and object is close
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if (APDS.colorAvailable() && APDS.proximityAvailable() && APDS.readProximity() == 0) {
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// Read color and proximity
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APDS.readColor(red, green, blue);
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colorTotal = (red + green + blue);
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}
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}
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// Normalise the color sample data and put it in the classifier input array
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color[0] = (float)red / colorTotal;
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color[1] = (float)green / colorTotal;
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color[2] = (float)blue / colorTotal;
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// Print the red, green and blue values
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Serial.print(color[0]);
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Serial.print(",");
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Serial.print(color[1]);
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Serial.print(",");
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Serial.println(color[2]);
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}

‎keywords.txt

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#######################################
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# Syntax Coloring Map For Arduino_Perceptron
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#######################################
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# Class
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#######################################
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Arduino_Perceptron KEYWORD1
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Perceptron KEYWORD1
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#######################################
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# Methods and Functions
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#######################################
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addExample KEYWORD2
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classify KEYWORD2
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clearAllClasses KEYWORD2
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#######################################
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# Constants
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#######################################

‎library.properties

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name=Arduino_Perceptron
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version=0.0.0
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author=Arduino
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maintainer=Arduino <info@arduino.cc>
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sentence=[BETA]
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paragraph=
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category=Data Processing
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url=
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architectures=*

‎src/Arduino_Perceptron.h

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/*
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This file is part of the Arduino_Perceptron library.
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Copyright (c) 2020 Arduino SA. All rights reserved.
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This library is free software; you can redistribute it and/or
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modify it under the terms of the GNU Lesser General Public
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License as published by the Free Software Foundation; either
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version 2.1 of the License, or (at your option) any later version.
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This library is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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Lesser General Public License for more details.
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You should have received a copy of the GNU Lesser General Public
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License along with this library; if not, write to the Free Software
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Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
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*/
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#ifndef _ARDUINO_PERCEPTRON_H_
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#define _ARDUINO_PERCEPTRON_H_
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#include "Perceptron.h"
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#endif

‎src/Perceptron.cpp

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/*
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This file is part of the Arduino_Perceptron library.
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Copyright (c) 2020 Arduino SA. All rights reserved.
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This library is free software; you can redistribute it and/or
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modify it under the terms of the GNU Lesser General Public
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License as published by the Free Software Foundation; either
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version 2.1 of the License, or (at your option) any later version.
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This library is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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Lesser General Public License for more details.
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You should have received a copy of the GNU Lesser General Public
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License along with this library; if not, write to the Free Software
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Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
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*/
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#include <float.h>
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#include "Perceptron.h"
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#include "utility/PerceptronNode.h"
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Perceptron::Perceptron(int inputLength, float learningRate) :
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_inputLength(inputLength),
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_learningRate(learningRate),
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_weights(new float[_inputLength]),
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_examples(NULL)
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{
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for (int i = 0; i < _inputLength; i++) {
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_weights[i] = random(-1, 1);
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}
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}
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Perceptron::~Perceptron()
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{
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clearAllClasses();
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}
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void Perceptron::addExample(const float input[], int class_)
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{
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// create new node
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PerceptronNode* newNode = new PerceptronNode(input, _inputLength, class_);
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// add new node to examples list
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if (_examples == NULL) {
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_examples = newNode;
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} else {
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PerceptronNode* node = _examples;
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while (1) {
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PerceptronNode* next = node->next();
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if (next == NULL) {
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node->setNext(newNode);
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break;
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}
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node = next;
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}
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}
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}
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int Perceptron::classify(const float input[])
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{
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float sum = 0;
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for (int i = 0; i < _inputLength; i++) {
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sum += input[i] * _weights[i];
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}
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// Activation function
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if (sum > 0) return 1;
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else return -1;
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}
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float Perceptron::train()
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{
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float count=0, correct=0;
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PerceptronNode* node = _examples;
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while (node != NULL) {
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count++;
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float inputs[_inputLength];
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for (int i = 0; i < _inputLength; i++) {
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inputs[i] = node->input(i);
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}
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int guess = classify(inputs);
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float error = node->class_() - guess;
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if (error==0) {correct++;}
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for (int i = 0; i < _inputLength; i++) {
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_weights[i] += _learningRate * error * inputs[i];
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}
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node = node->next();
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}
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return correct/count;
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}
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void Perceptron::clearAllClasses()
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{
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PerceptronNode* node = _examples;
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while (node != NULL) {
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PerceptronNode* next = node->next();
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delete node;
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node = next;
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}
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_examples = NULL;
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}

‎src/Perceptron.h

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/*
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This file is part of the Arduino_Perceptron library.
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Copyright (c) 2020 Arduino SA. All rights reserved.
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This library is free software; you can redistribute it and/or
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modify it under the terms of the GNU Lesser General Public
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License as published by the Free Software Foundation; either
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version 2.1 of the License, or (at your option) any later version.
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This library is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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Lesser General Public License for more details.
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You should have received a copy of the GNU Lesser General Public
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License along with this library; if not, write to the Free Software
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Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
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*/
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#ifndef _PERCEPTRON_H_
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#define _PERCEPTRON_H_
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#include <Arduino.h>
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class PerceptronNode;
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class Perceptron {
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public:
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Perceptron(int inputLength, float learningRate);
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virtual ~Perceptron();
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void clearAllClasses();
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void addExample(const float input[], int class_);
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int classify(const float input[]);
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float train();
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private:
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int _inputLength;
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float _learningRate;
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float* _weights;
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PerceptronNode* _examples;
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};
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#endif

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