adds simple classification example

ml5js · Oct 2, 2019 · 387b470 · 387b470 · shiffman · Oct 2, 2019
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diff --git a/p5js/NeuralNetwork/NeuralNetwork_Simple-Classification/index.html b/p5js/NeuralNetwork/NeuralNetwork_Simple-Classification/index.html
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+<html>
+
+<head>
+  <meta charset="UTF-8">
+  <title>Neural Network</title>
+
+  <script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/0.8.0/p5.min.js"></script>
+  <script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/0.8.0/addons/p5.dom.min.js"></script>
+  <script src="http://localhost:8080/ml5.js" type="text/javascript"></script>
+</head>
+
+<body>
+  <h1>Neural Network Classification</h1>
+  <label for="avatar">Load Model:</label>
+  <input type="file" id="load" multiple />
+  <script src="sketch.js"></script>
+</body>
+
+</html>
diff --git a/p5js/NeuralNetwork/NeuralNetwork_Simple-Classification/sketch.js b/p5js/NeuralNetwork/NeuralNetwork_Simple-Classification/sketch.js
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+// Copyright (c) 2018 ml5
+//
+// This software is released under the MIT License.
+// https://opensource.org/licenses/MIT
+
+/* ===
+ml5 Example
+Image classification using MobileNet and p5.js
+This example uses a callback pattern to create the classifier
+=== */
+let nn;
+
+const options = {
+  inputs: 1,
+  outputs: 2,
+  task: 'classification',
+  debug: true
+}
+
+function setup(){
+  createCanvas(400, 400);
+  nn = ml5.neuralNetwork(options);
+
+
+  console.log(nn)
+  createTrainingData();
+  nn.normalize();
+
+  const trainingOptions={
+    batchSize: 24,
+    epochs: 32
+  }
+
+  nn.train(trainingOptions,finishedTraining); // if you want to change the training options
+  // nn.train(finishedTraining); // use the default training options
+}
+
+function finishedTraining(){
+
+  nn.classify([300], function(err, result){
+    console.log(result.output);
+  })
+
+}
+
+function createTrainingData(){
+    for(let i = 0; i < 400; i++){
+      if(i%2 === 0){
+        const x = random(0, width/2);
+        nn.addData( [x],  ['left'])
+      } else {
+        const x = random(width/2, width);
+        nn.addData( [x],  ['right'])
+      }
+    }
+}