https://github.com/sps014/BlazorML5

ML5 Machine Learning For Blazor with JSInterop mechanism
https://github.com/sps014/BlazorML5

Last synced: 4 months ago
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ML5 Machine Learning For Blazor with JSInterop mechanism

• Host: GitHub
• URL: https://github.com/sps014/BlazorML5
• Owner: sps014
• License: mit
• Created: 2019-12-29T12:55:58.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2023-09-14T06:32:20.000Z (over 1 year ago)
• Last Synced: 2024-08-31T13:49:41.069Z (6 months ago)
• Language: C#
• Homepage: https://blazor-ml5-sample.netlify.com/
• Size: 7.38 MB
• Stars: 54
• Watchers: 6
• Forks: 16
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-blazor - BlazorML5 -  ML5 Machine Learning for Blazor with JSInterop mechanism. (Sample Projects / Machine Learning)

README

        
# ML5-Blazor

 [![NuGet Package](https://img.shields.io/badge/nuget-v1.0.6%20Preview%204-orange.svg)](https://www.nuget.org/packages/BlazorML5/)

[![NuGet Badge](https://buildstats.info/nuget/BlazorML5)](https://www.nuget.org/packages/BlazorML5)

![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)

  

 ### An Easy Machine Learning Library for Blazor.

 Now supports both Blazor Server and WASM and MAUI Hybrid.

## Current Features

1. Neural Network

2. Image Classification

3. Sound Classifier

4. Object Detector (YOLO and COCOSSD based)

5. PoseNet

6. Sentiment Analyzer

7. FaceMesh

#### Hosted Sample

[Live Demo](https://blazor-ml5-sample.netlify.com/) 

#### Documentation

Install Asp.Net Core payload and then follow [Installation Instructions here](https://github.com/sps014/BlazorML5/wiki/BlazorML5-Installation) to configure ML5 to use it from C# Blazor app.


API documentation can be followed from [here](https://learn.ml5js.org/#/reference/index) after lib configuration.

.

#### Sample Neural Network

```cs

@page "/nn"

@using BlazorML5

@using BlazorML5.Helpers

@inject IJSRuntime runtime

Index

Add Data and Train

@code

{

    NeuralNetwork _network;

    protected override async Task OnInitializedAsync()

    {

        await Ml5.InitAsync(runtime);

        _network = await Ml5.NeuralNetworkAsync(new NeuralNetworkOptions()

        {

            Task = TaskType.Classification,

            DataUrl = "https://raw.githubusercontent.com/ml5js/ml5-library/main/examples/p5js/NeuralNetwork/NeuralNetwork_color_classifier/data/colorData_small.json",

            Debug = true,

            Inputs = new object[]{"r", "g", "b"},

            Outputs = new object[]{"label"}

        });

        _network.OnTraining+=(l,e)=>

        {

            Console.WriteLine($"Training: {e}%");

        };

        _network.OnTrainingComplete+=async ()=>

        {

            Console.WriteLine($"Training Complete");

            await _network.ClassifyMultipleAsync(new object[]{new object[]{12,13,14},new object[]{15,16,17}});

        };

        _network.OnDataLoaded+=(e)=>

        {

            Console.WriteLine($"Data Loaded");

        };

        _network.OnClassify+=async (l,e)=>

        {

            Console.WriteLine(e.Length);

            Console.WriteLine(e[0].Label);

        };

        _network.OnClassifyMultiple+=async (l,e)=>

        {

            Console.WriteLine(e.Length);

            Console.WriteLine(e[0].Length);

            Console.WriteLine(e[0][0].Label);

        };

    }

    async void AddData()

    {

        //data fetched from .csv file no need to manually add and hence directly training 

        //await _network.NormalizeDataAsync();

        await _network.TrainAsync();

    }

}

```

More samples [here](https://github.com/sps014/BlazorML5/tree/master/SampleApp/Pages)