American Sign Language prediction in real time using OpenCV. A certain GUI is also built using Tkinter which can be seen in Sign Language Reader.py file. This project also has the feature to speak the generated text using API for text to speech conversion

Snapchat Lens used to transcript American Sign Language

ASL_Learning is web app dedicated to the teaching of American Sing Language using Flash Cards

CSE 572 Data Mining Group 14

This repository contains Python code for a project that performs American Sign Language (ASL) detection using multiclass classification. It utilizes YOLO (You Only Look Once) and MobileNetSSD_deploy for object detection, achieving an accuracy of 91%. The code offers options to predict signs from both images and videos.

This project aims to develop an efficient solution for detecting signs in the form of American Sign Language (ASL) using various cutting-edge technologies. The application will leverage the capabilities of OpenCV, MediaPipe, PyTorch, Transformers, PyTTSX3 and PyQt.5

A model for recognizing the ASL Alphabets. Simple Jupyter notebook with a Kaggle Dataset!

A python based app which can convert the hand gesture to corresponding text label in real time.

Real-time American Sign Language (ASL) letters detection, via PyTorch, OpenCV, YOLOv5, Roboflow and LabelImg 🤟

Deploy deep learning technologies in computer vision to bridge the communication gap between the deaf and everyone else.

communication application to make Complete conversation with deaf people

Proposed a solution to the problem of recognizing the American Sign Language Hand recognition using the Deep Learning method and compare how accurate our solution is when performing data augmentation methods on the images in our dataset.

A sign language recognition webapp I created with my code from the first Google Isolated Sign Language Recognition Competition on Kaggle where it scored 72/1165. The app was my final computational thinking project in 8th grade.

General Assembly Data Science Immersive (GA-DSI) Capstone Project - American Sign Language (ASL) Letter Detector using Computer Vision and Machine Learning run in a Streamlit App.

Image Analysis: Classification of hand poses in the American sign language

The project is a model built with Keras to recognize American Sign Language (ASL) letters.

"Repository containing code and resources for ASL (American Sign Language) image classification using Convolutional Neural Networks (CNNs). Learn data preprocessing, CNN architecture, training, and evaluation for accurate ASL letter recognition."