Introduction

The odd-image-classifier library is an image classifier built on top of brain.js. It allows you to train a neural network to recognize images based on a set of output labels.

Usage

To use the odd-image-classifier, you can import the Classifier class and create a new instance of it. You can then configure the neural network using the configure method. The following example shows how to create a classifier for recognizing numbers:

``javascript
import { Classifier } from "odd-image-classifier";

const classifier = new Classifier("Numbers");

classifier.configure("brain", {
hiddenLayers: [8, 16],
});
`

You can also configure the training options for the classifier by passing in an options object to the configure method.

`javascript
const OUTPUT_LABELS = [ ["1", ["7", "9"]],
["2", ["7", "3"]],
["3", ["2", "5"]],
["4", ["9", "7"]],
["5", ["6", "8"]],
["6", ["5", "8"]],
["7", ["1", "9"]],
["8", ["6", "5"]],
["9", ["7", "1"]],
]

classifier.configure("training", {
iterations: 20000,
output_labels: OUTPUT_LABELS,
logPeriod: 100,
layers: [12, 24],
learningRate: 0.1,
imageSize: {
width: 32,
height: 32,
},
});

`

After configuring the classifier, you can start training it by calling the train method.

`javascript
classifier.train();
`

API


The odd-image-classifier` library exposes the following classes and methods:

- Classifier: The main class for creating and configuring a new image classifier.
- configure(type, options): Configure the classifier. The type parameter can be either "brain" or "training". The options parameter is an object with the options for the classifier.
- train(): Start training the classifier.
-