The project focuses on enabling seamless communication for mute individuals during video calls by transcribing American Sign Language (ASL) into English text in real-time. Leveraging advanced computer vision and natural language processing technologies, our system provides accurate captions for ASL gestures, ensuring inclusivity and accessibility in digital communication.

• @Ashish_Pandey
• @Darshan_Poudel
• @Ankit_Mehta

1. Clone the project's github repository :

git clone https://github.com/Darshan808/Sign-Ease-2.0

2. Change directory to the project folder :

cd Sign-Ease

3. For Frontend :

cd client

npm install

npm run dev

4. For Backend :

cd model

pip install -r requirements.txt

python access.py

https://drive.google.com/file/d/17DAo7MrDE9cwxysOt2shryFd2HLYbbl9/view?usp=sharing

MIT

1. Click on Try Now to access the trial phase of this project.
2. Click on HandSign icon to turn on the video
3. Once a green bleep appears next to your username, you can start showing the hand signs.
4. The shown hand signs will be transcibed as English text on the caption section.

@Ashish_Pandey @Darshan_Poudel @Ankit_Mehta