Sign Language Translator enables the hearing impaired user to communicate efficiently in sign language, and the application will translate the same into text/speech. The user has to train the model, by recording its own sign language gestures. Internally it uses MobileNet and KNN classifier to classify the gestures.

It is a best Visualiser for implementing K-Nearest Neighbours Algorithm with 3 different classes i.e A,B,C. It is developed using ml5.js and p5.js.

This project is inspired by the teachable Machine project by Google. It's about the Real-time application of Machine Learning and how FUN to play and experienced it.

Ez Video Background Semantic Segmentation

A personal collection of Machine Learning / Data Science / AI resources. This collections consists of papers, blog posts, tutorials and also self-trained models or reimplementations of widespread machine learning algorithms.

A sentiment analysis app with ML5JS and HTML

ml5.js example to use the image classifier via image upload

A browser-based face expression detection app built with face-api.js. Supports real-time webcam analysis and image uploads to identify emotions using facial landmarks and expression recognition.

Posture Correction project using PoseNet model from TensorFlow.js

A app developed for demo using ml5.js

A simple image classifier with ml5JS

Real-time human pose detection using PoseNet from ml5.js. Supports both webcam and image uploads for detecting body keypoints and skeletal connections directly in the browser.

Yoga_Pose_detector

A simple web app that performs real-time object detection using your webcam or uploaded images, powered by ml5.js and COCO-SSD model. Built with p5.js for easy canvas rendering.

Image Recognition Starter Application (MobileNet Model)

beginner-friendly machine learning tutorials in JavaScript (with p5.js and ml5.js)

Computer Vision, Machine Learning, Text to speach and more with the P5js

The Aim of this project is to deliver the basic use cases of the Pose Net model for real time human pose estimation in the Browser with Tensor Flow using a webcam feed as the data.