Awesome GitHub RepositoriesTensorFlow.js Models

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

NSFW detection on the client-side via TensorFlow.js

Kalidokit is a web-based motion capture tool that transforms real-time webcam video into 3D character animation data. It functions as a blendshape and kinematics calculator, converting facial, hand, and body tracking data from Mediapipe and TensorFlow.js into blendshape weights and euler rotations for driving digital puppets and avatars. The tool solves face landmarks to derive head rotation, eye blinks, mouth shapes, and brow values for rigging, while hand landmarks are converted into finger joint rotations and body keypoints into per-joint euler rotations for full-body animation. It include

Real-Time-Person-Removal est une application de vision par ordinateur basée sur le web, conçue pour identifier et supprimer les silhouettes humaines des flux vidéo en direct. En utilisant TensorFlow.js, l'outil fonctionne comme un système de soustraction d'arrière-plan en temps réel qui analyse la composition de la scène pour isoler les arrière-plans statiques des personnes en mouvement. Le projet permet la vision par ordinateur dans le navigateur en traitant les flux vidéo de webcam directement côté client. Il utilise l'apprentissage automatique pour différencier les éléments de scène dynamiques de l'arrière-plan, permettant la suppression en temps réel des personnes du champ visuel.

This project is a JavaScript library designed for real-time face detection directly within a web browser. It functions as a machine learning model wrapper that enables developers to identify and track human faces in live video streams without the need for backend server processing. The library utilizes browser-native media access to stream raw camera data into application memory, where it performs pixel-level analysis. By leveraging a tensor-based inference engine and web-assembly acceleration, the tool executes complex neural network calculations locally to achieve high-performance computer