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ml5js avatar

ml5js/ml5-library

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ml5js.org↗

Ml5 Library

ml5-library is a JavaScript machine learning library that functions as a browser-based inference engine. It provides a high-level wrapper for implementing neural networks and data models, allowing users to execute machine learning predictions directly on the client side.

The library simplifies the integration of machine learning into web applications and creative coding projects by removing the requirement for deep mathematical expertise. It specifically enables web-based image classification through the use of pretrained deep learning models to identify and label objects within images.

The system operates by wrapping low-level tensor operations via TensorFlow.js, utilizing a higher-level API to manage pretrained model loading and asynchronous execution.

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Features

  • Web-Based Machine Learning - Enables the integration of machine learning models directly into websites to process data and make predictions in the browser.
  • High-Level ML Abstractions - Provides an intuitive high-level API that simplifies complex tensor manipulations for common tasks like image classification.
  • High-Level Model APIs - Provides a high-level API for implementing neural networks without requiring deep mathematical expertise.
  • Image Classification - Analyzes image content within web applications to identify and label objects using pretrained neural networks.
  • JavaScript Machine Learning Libraries - Provides a comprehensive JavaScript library for building and running machine learning models in the browser.
  • Browser-based Inference Engines - Functions as a browser-based inference engine to execute pretrained machine learning models on the client side.
  • Pretrained Model Loading - Enables the loading and caching of pretrained model weights and configurations from remote storage for immediate inference.
  • TensorFlow Graph Execution - Executes machine learning models in the browser by wrapping low-level tensor operations via TensorFlow.js.
  • Image Classifiers - Identifies objects within images using pretrained models and returns results through callback functions.
  • Beginner Prototyping Tools - Simplifies machine learning prototyping for beginners by removing the requirement for deep mathematical expertise.
  • Creative Machine Learning Integrations - Integrates computer vision and AI models into digital art and experimental creative coding projects.
  • AI and Machine Learning - Friendly machine learning for the web.
  • Machine Learning Frameworks - Friendly, accessible machine learning library for web developers.
6,581 stars·899 forks·JavaScript·16 views

Star history

Star history chart for ml5js/ml5-libraryStar history chart for ml5js/ml5-library

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

Projects sharing features with Ml5 Library

These projects share indexed features with Ml5 Library. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • tensorflow/tfjstensorflow avatar

    tensorflow/tfjs

    19,134View on GitHub↗

    TensorFlow.js is a JavaScript machine learning library used for training and deploying models in web browsers and server-side environments. It functions as a browser-based model trainer, a WebAssembly inference engine, and a WebGPU accelerated tensor library for low-level linear algebra. The project also includes a model converter to transform Python-based models into optimized formats for JavaScript execution. The library distinguishes itself through a pluggable backend architecture that allows mathematical operations to be executed via CPU, WebGL, or WebGPU. It supports the conversion of Py

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  • tensorflow/tfjs-modelstensorflow avatar

    tensorflow/tfjs-models

    14,791View on GitHub↗

    This project is a collection of pre-trained machine learning models and conversion pipelines designed for running inference directly in the browser using TensorFlow.js. It provides a library of ready-to-use models for computer vision, audio classification, and natural language processing tasks. The suite includes specialized tools for transforming Python-based Keras models into JSON formats compatible with web environments. It enables the deployment of these models by fetching architectures and weight shards via HTTP for client-side execution. The project covers a broad range of capabilities

    TypeScript
    View on GitHub↗14,791
  • wzmiaomiao/deep-learning-for-image-processingWZMIAOMIAO avatar

    WZMIAOMIAO/deep-learning-for-image-processing

    26,281View on GitHub↗

    This project is a PyTorch-based computer vision library and deep learning image processing framework. It provides a collection of neural network architectures designed for visual analysis tasks, specifically focusing on image classification, object detection, and semantic segmentation. The toolset implements diverse methodologies for visual recognition, including anchor-free object detection, regional proposal networks, and heatmap-based keypoint estimation. It utilizes both convolutional neural networks for spatial feature extraction and transformer-based self-attention mechanisms to compute

    Pythonbilibiliclassificationdeep-learning
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  • xenova/transformers.jsxenova avatar

    xenova/transformers.js

    16,141View on GitHub↗

    Transformers.js is a JavaScript library and web machine learning framework designed to run pretrained transformer models directly in the browser. It serves as a client-side inference engine and a wrapper for the ONNX Runtime, enabling the execution of multimodal AI tasks on user devices without the need for a backend server. The library distinguishes itself by providing a unified toolkit for processing text, image, and audio data locally. This architecture supports privacy-preserving model inference and reduces latency by performing all computations on the client's hardware. Its capabilities

    JavaScript
    View on GitHub↗16,141
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Frequently asked questions

What does ml5js/ml5-library do?

ml5-library is a JavaScript machine learning library that functions as a browser-based inference engine. It provides a high-level wrapper for implementing neural networks and data models, allowing users to execute machine learning predictions directly on the client side.

What are the main features of ml5js/ml5-library?

The main features of ml5js/ml5-library are: Web-Based Machine Learning, High-Level ML Abstractions, High-Level Model APIs, Image Classification, JavaScript Machine Learning Libraries, Browser-based Inference Engines, Pretrained Model Loading, TensorFlow Graph Execution.

Which projects share features with ml5js/ml5-library?

Projects with overlapping indexed features include: tensorflow/tfjs — TensorFlow.js is a JavaScript machine learning library used for training and deploying models in web browsers and… tensorflow/tfjs-models — This project is a collection of pre-trained machine learning models and conversion pipelines designed for running… wzmiaomiao/deep-learning-for-image-processing — This project is a PyTorch-based computer vision library and deep learning image processing framework. It provides a… xenova/transformers.js — Transformers.js is a JavaScript library and web machine learning framework designed to run pretrained transformer… transcranial/keras-js — Keras-js is a JavaScript inference engine and browser-based machine learning framework designed to execute pre-trained… 0hq/webgpt — WebGPT is a browser-based machine learning framework designed to execute transformer models entirely within the client…