image-classifier

Image Classifier NodeJS Package

Machine Learning Image Classifier for NodeJS

Installation

Library : npm install image-classifier

CLI : npm install -g image-classifier

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ImageClassifier

Get Started

Create a new ImageClassifier with a dataset path for saving and loading your dataset. You can also specify to autosave to save every time you add a new example

    const ImageClassifier = require('image-classifier');

    const MyClassifier = new ImageClassifier('./mynewdataset.json', false);

Parameter	Description	Type	Mandatory
dataset	Path to dataset	String	True
autosave	Autosave dataset after adding a example (default: True)	Boolean	False

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Load (Async)

Load should always be called before any further implementation. Will attempt to load dataset if the dataset path already exists

    MyClassifier.load().then(async function() {
        /* Add Examples here */
    });

---

Add Example (Async)

Add example data for training a new model

    // Add Toyota Exampless
    await MyClassifier.addExample('Toyota', './toyota0.png');
    await MyClassifier.addExample('Toyota', './toyota1.png');
    await MyClassifier.addExample('Toyota', './toyota2.png');
    /* ...Add more examples */

    // Add Honda Examples
    await MyClassifier.addExample('Honda', './honda0.png');
    await MyClassifier.addExample('Honda', './honda1.png');
    await MyClassifier.addExample('Honda', './honda2.png');
    /* ...Add more examples */

Parameter	Description	Type	Mandatory
label	Category label for what the image is	String	True
image	Path to image to add as an example for label	String	True

---

Predict (Async)

Get a classification prediction of image passed in

    const prediction = await MyClassifier.predict('./toyotaTest0.png');
    /* Prediction 
        {
            "classIndex": <Index of Label>,
            "label": <Label>,
            "confidences": {
                "Toyota": <Percentile>,
                "Honda": <Percentile>
            }
        }
    */

Parameter	Description	Type	Mandatory
image	Path to image for evaluating a prediction with your ImageClassifier	String	True

---

Drop Classifier (Sync)

Remove all examples of specified label

    MyClassifier.dropClassifier('Honda');

Parameter	Description	Type	Mandatory
label	Label for classifier you would like to remove from ImageClassifier. Drops all examples of specified label.	String	True

---

Save (Async)

Save dataset manually to dataset path passed from the constructor

    await MyClassifier.save();

---

train

WARNING: STILL IN BETA v1.0.0

Save

Save a dataset

train -s <someurl|somefile> <title.json>

Export

Export a dataset

train -e <somedataset.json> <newlocation.json>

Delete

Delete a dataset in your saved datasets

train -d <somedataset.json>

List

List all saved datasets

train -l

Identify

Identify an image with a saved dataset

train -i <someimage.png> <somedataset.json>

Help

Help menu will be brought up if none of the above flags are included

    Usage: train [options] <values>
            
    Options:
        -s, --save     : Save a dataset
        -e, --export   : Export a dataset
        -d, --delete   : Delete a dataset
        -l, --list     : List all saved datasets
        -i, --identify : Identify an image with a dataset
        -h, --help     : Open help menu
    
    Examples:
        train -s https://dataset.example.com/dataset.json example-dataset.json
        train -e example-dataset.json ./testing/new-example-dataset.json
        train -i cat.png example-dataset.json
        train -d example-dataset.json

Contributions