Skip to content

mohamedsaeed8223/ARSLwithVMEA

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

13 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

ARSLwithVMEA

Arabic Sign Language Video Classification using Video Masked Auto-Encoder

Description

This repo is part of our machine learning work for our graduation project "Fluent Hands" A mobile application helping people learn sign-language with AI reinfocement.

Technologies

transformers
torch
torchvision
pytorchvideo
flask

to use this repo make sure to install all the dependecies in requirements.txt file

pip install -r requirements.txt

Model Architecture

model The model works using 2 attention methods:
vanilla VIT (vision transformer) -> to understand each frame
joint time-space attention ->to understand relations between frames
but the special part about our model that makes it as robust and data effecient is masked auto encoding you can read more about the model architecture in detail in the model's paper

Deployment

the model was deployed using flask framework and for public API deployment lightning.ai was used
the API was then called from a flutter application to be then incorperated into the app's ecosystem

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published