Merge pull request #437 from microbit-foundation/430-make-a-knnmodel-…

…and-a-knnmodeltrainer

Added a KNN model and KNN model trainer

package.json

@@ -45,6 +45,7 @@
   },
   "dependencies": {
     "@microsoft/applicationinsights-web": "^3.0.0",
+    "@tensorflow-models/knn-classifier": "^1.2.6",
     "@tensorflow/tfjs": "^4.4.0",
     "bowser": "^2.11.0",
     "browser-lang": "^0.2.1",

src/components/playground/EngineInteractionButtons.svelte

@@ -4,30 +4,19 @@
   SPDX-License-Identifier: MIT
  -->
 <script lang="ts">
-  import StaticConfiguration from '../../StaticConfiguration';
   import Gesture from '../../script/domain/Gesture';
-  import Model from '../../script/domain/Model';
   import AccelerometerClassifierInput from '../../script/mlmodels/AccelerometerClassifierInput';
-  import LayersModelTrainer from '../../script/mlmodels/LayersModelTrainer';
   import { classifier, engine, gestures } from '../../script/stores/Stores';
   import playgroundContext from './PlaygroundContext';
+  import TrainKnnModelButton from './TrainKNNModelButton.svelte';
+  import TrainLayersModelButton from './TrainLayersModelButton.svelte';
 
   const getRandomGesture = (): Gesture => {
     return gestures.getGestures()[
       Math.floor(Math.random() * gestures.getNumberOfGestures())
     ];
   };
 
-  const model: Model = classifier.getModel();
-  const trainModelButtonClicked = () => {
-    playgroundContext.addMessage('training model...');
-    model
-      .train(new LayersModelTrainer(StaticConfiguration.layersModelTrainingSettings))
-      .then(() => {
-        playgroundContext.addMessage('Finished training!');
-      });
-  };
-
   const predictButtonClicked = () => {
     const randGesture = getRandomGesture();
     playgroundContext.addMessage(
@@ -43,7 +32,8 @@
   };
 </script>
 
-<button class="border-1 p-2 m-1" on:click={trainModelButtonClicked}>train model!</button>
+<TrainLayersModelButton />
+<TrainKnnModelButton />
 <button class="border-1 p-2 m-1" on:click={predictButtonClicked}
   >Predict random gesture!</button>
 <button

src/components/playground/TrainKNNModelButton.svelte

@@ -0,0 +1,24 @@
+<!--
+  (c) 2023, Center for Computational Thinking and Design at Aarhus University and contributors
+ 
+  SPDX-License-Identifier: MIT
+ -->
+<script lang="ts">
+  import Model from '../../script/domain/Model';
+  import KNNModelTrainer from '../../script/mlmodels/KNNModelTrainer';
+  import { classifier } from '../../script/stores/Stores';
+  import playgroundContext from './PlaygroundContext';
+
+  const model: Model = classifier.getModel();
+  const trainModelButtonClicked = () => {
+    playgroundContext.addMessage('training model...');
+    const k = 10;
+    model.train(new KNNModelTrainer(k)).then(() => {
+      playgroundContext.addMessage('Finished training a KNN model (k=10)!');
+    });
+  };
+</script>
+
+<button class="border-1 p-2 m-1" on:click={trainModelButtonClicked}>
+  train KNN model!
+</button>

src/components/playground/TrainLayersModelButton.svelte

@@ -0,0 +1,25 @@
+<!--
+  (c) 2023, Center for Computational Thinking and Design at Aarhus University and contributors
+ 
+  SPDX-License-Identifier: MIT
+ -->
+<script lang="ts">
+  import StaticConfiguration from '../../StaticConfiguration';
+  import Model from '../../script/domain/Model';
+  import LayersModelTrainer from '../../script/mlmodels/LayersModelTrainer';
+  import { classifier } from '../../script/stores/Stores';
+  import playgroundContext from './PlaygroundContext';
+
+  const model: Model = classifier.getModel();
+  const trainModelButtonClicked = () => {
+    playgroundContext.addMessage('training model...');
+    model
+      .train(new LayersModelTrainer(StaticConfiguration.layersModelTrainingSettings))
+      .then(() => {
+        playgroundContext.addMessage('Finished training!');
+      });
+  };
+</script>
+
+<button class="border-1 p-2 m-1" on:click={trainModelButtonClicked}
+  >train layers model!</button>

src/components/playground/inputSynthesizer/AccelerometerDataSynthesizer.ts

@@ -33,9 +33,8 @@ class AccelerometerSynthesizer implements Readable<AccelerometerSynthesizerData>
       xSpeed: this.getInitialSineSpeed(),
       ySpeed: this.getInitialSineSpeed() + 1 / 1000,
       zSpeed: this.getInitialSineSpeed() + 2 / 1000,
-      isActive: true,
+      isActive: false,
     });
-    this.updateInterval();
   }
 
   public subscribe(

src/script/mlmodels/KNNMLModel.ts

@@ -0,0 +1,40 @@
+/**
+ * (c) 2023, Center for Computational Thinking and Design at Aarhus University and contributors
+ *
+ * SPDX-License-Identifier: MIT
+ */
+import { tensor } from '@tensorflow/tfjs';
+import MLModel from '../domain/MLModel';
+import * as knnClassifier from '@tensorflow-models/knn-classifier';
+
+class KNNMLModel implements MLModel {
+  constructor(
+    private model: knnClassifier.KNNClassifier,
+    private k: number,
+  ) {}
+  public async predict(filteredData: number[]): Promise<number[]> {
+    const inputTensor = tensor([filteredData]);
+
+    try {
+      // eslint-disable-next-line @typescript-eslint/no-unsafe-assignment, @typescript-eslint/no-unsafe-member-access, @typescript-eslint/no-unsafe-call
+      const prediction = await this.model.predictClass(inputTensor, this.k);
+      // eslint-disable-next-line @typescript-eslint/no-unsafe-member-access
+      const classes = Object.getOwnPropertyNames(prediction.confidences);
+      const confidences: number[] = [];
+
+      for (let i = 0; i < classes.length; i++) {
+        const clazz = classes[i];
+        // eslint-disable-next-line @typescript-eslint/no-unsafe-assignment, @typescript-eslint/no-unsafe-member-access
+        const confidence = prediction.confidences[clazz];
+        confidences.push(confidence as number);
+      }
+
+      return Promise.resolve(confidences);
+    } catch (err) {
+      console.error('Prediction error: ', err);
+      return Promise.reject(err);
+    }
+  }
+}
+
+export default KNNMLModel;

src/script/mlmodels/KNNModelTrainer.ts

@@ -0,0 +1,32 @@
+/**
+ * (c) 2023, Center for Computational Thinking and Design at Aarhus University and contributors
+ *
+ * SPDX-License-Identifier: MIT
+ */
+import ModelTrainer, { TrainingData } from '../domain/ModelTrainer';
+import KNNMLModel from './KNNMLModel';
+import * as tf from '@tensorflow/tfjs';
+import * as knnClassifier from '@tensorflow-models/knn-classifier';
+
+/**
+ * Trains a K-Nearest Neighbour model
+ */
+class KNNModelTrainer implements ModelTrainer<KNNMLModel> {
+  constructor(private k: number) {}
+  public trainModel(trainingData: TrainingData): Promise<KNNMLModel> {
+    // eslint-disable-next-line @typescript-eslint/no-unsafe-assignment, @typescript-eslint/no-unsafe-member-access, @typescript-eslint/no-unsafe-call
+    const knn: knnClassifier.KNNClassifier = knnClassifier.create();
+
+    trainingData.classes.forEach((gestureClass, index) => {
+      gestureClass.samples.forEach(sample => {
+        const example = tf.tensor([sample.value]);
+        // eslint-disable-next-line @typescript-eslint/no-unsafe-member-access, @typescript-eslint/no-unsafe-call
+        knn.addExample(example, index);
+      });
+    });
+
+    return Promise.resolve(new KNNMLModel(knn, this.k));
+  }
+}
+
+export default KNNModelTrainer;