This project demonstrates the use of neural networks and computer vision to create a classifier that interprets the Brazilian Sign Language.

Last update: Oct 14, 2022

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Overview

LIBRAS-Image-Classifier

This project demonstrates the use of neural networks and computer vision to create a classifier that interprets the Brazilian Sign Language. At the moment, the project interprets only the first 6 letters of the alphabet. A Convolutional Neural Network was used in order to train and test a network so that, through the webcam, it is possible to identify the signal made by the user's hand.

Data prediction

In order to teach the neural network, we obtain image captures of the hand signal with the webcam inported in grayscale on the /data folter. There are a total of 1200 images, 200 of each signal.

Technologies used

Keras
Tensorflow
OpenCV
Python 3.8

Owner

Aryclenio Xavier Barros

Aryclenio Barros (Ary), a Front-end and IoT developer. Always aiming at usability and code performance at all costs.

GitHub Repository

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This project demonstrates the use of neural networks and computer vision to create a classifier that interprets the Brazilian Sign Language.

Related tags

Overview

LIBRAS-Image-Classifier

Data prediction

Technologies used

Owner

Aryclenio Xavier Barros

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