https://github.com/axegon/sklite-dart

Transpile scikit-learn models to Flutter
https://github.com/axegon/sklite-dart

dart flutter scikit-learn

Last synced: about 1 month ago
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Transpile scikit-learn models to Flutter

• Host: GitHub
• URL: https://github.com/axegon/sklite-dart
• Owner: axegon
• License: mit
• Created: 2019-09-02T13:39:30.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2023-02-24T20:25:09.000Z (almost 2 years ago)
• Last Synced: 2023-08-20T23:08:24.986Z (over 1 year ago)
• Topics: dart, flutter, scikit-learn
• Language: Dart
• Size: 46.9 KB
• Stars: 34
• Watchers: 4
• Forks: 13
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • License: LICENSE

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README

        
# SkLite-dart

[![SkLite Demo App](http://img.youtube.com/vi/K5D1T1VJBR8/0.jpg)](http://www.youtube.com/watch?v=K5D1T1VJBR8 "SkLite-dart demo")

* Porting Scikit-Learn models to Flutter *

## Getting Started

The library uses pre-trained models using scikit-learn and [sklite](https://github.com/axegon/SkLite) for python. Once built and exported, the models can be used in Flutter with ease. You need to load them inside your application and use them accordingly to your case:

You need to setup a local static directory where you can store the generated JSON file using [sklite](https://github.com/axegon/SkLite).

Put sklite in your pubspec.yaml file, import whichever model it is you intend to use and use the `predict` method as you would in scikit-learn. Use the

`loadModel` in utils/dart.io for your application, the other functions are for development and testing only.

## Supported models

| IMPLEMENTATION                     | STATUS |

|------------------------------------|--------|

| KNeighborsClassifier               | ✓      |

| SVC                                | ✓      |

| GaussianProcessClassifier          |        |

| DecisionTreeClassifier             | ✓      |

| RandomForestClassifier             | ✓      |

| MLPClassifier                      | ✓      |

| AdaBoostClassifier                 |        |

| GaussianNB                         | ✓      |

| QuadraticDiscriminantAnalysis      |        |

| BernoulliNB                        | ✓      |

| LinearSVC                          | ✓      |

## Usage

You first need to add the library to your project's pubspec.yaml. For the time being the library hasn't been published to pub.dev (should be soon enough though).

```

dependencies:

  sklite: ^0.0.1

```

Add a static assets directory inside your Flutter project:

```

flutter:

  uses-material-design: true

  assets:

    - assets/

```

Put the generated model using [sklite for python](https://github.com/axegon/SkLite) in the specified directory

Import the library in your application and load the model:

```

import 'package:flutter/material.dart';

import 'package:sklite/SVM/SVM.dart';

import 'package:sklite/utils/io.dart';

import 'dart:convert';

void main() => runApp(new MaterialApp(

  home: new HomePage(),

  debugShowCheckedModeBanner: false)

);

class HomePage extends StatefulWidget {

  @override

  _HomePageState createState() {

    return new _HomePageState();

  }

}

class _HomePageState extends State {

  SVC svc;

  _HomePageState() {

    loadModel("assets/svcmnist.json").then((x) {

      this.svc = SVC.fromMap(json.decode(x));

    });

  }

  @override

  Widget build(BuildContext context) {

    return Scaffold(

        // add any widget with svc.predict() callback

    );

  }

```