Team 700_GESTURE VISION

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Inspiration: The problem is the lack of effective communication between deaf and mute individuals and non-sign language users.

Sign language, being their primary mode of communication, poses a barrier to effective interaction, as most people are not proficient in sign language. There is a need for a solution that can accurately predict sign language gestures in real-time and provide translations to facilitate communication and inclusivity.

What it does:

Our solution is a gesture prediction system for conveying sign language. It utilizes deep learning techniques and real-time video processing to recognize and interpret sign language gestures. The system captures video input, preprocesses it, and feeds it into a trained model that predicts the corresponding sign gesture. The predicted gesture is then translated into textual form to enable communication with non-sign language users.

How we built it: The frontend of our website was designed using HTML, CSS, and JavaScript. We

crafted a user-friendly interface that enables users to interact effortlessly. To ensure a secure user experience, we incorporated Django's built-in authentication system. This allowed users to register, log in, and access personalized features. We also implemented role-based permissions to protect sensitive data and functionalities. It utilizes deep learning techniques and real-time video processing to recognize and interpret sign language gestures.

Challenges we ran into:

we faced issues while training the model and rendering it into webpage

Accomplishments that we're proud of:

Yes, we are very proud that we have completed our task and what all things that we want to add in the project has been achieved

What we learned:

Team work time management and training model using python.

What's next for GESTURE VISION:

Expansion of Gesture Vocabulary: The system can be further developed to recognize and predict a broader range of sign language gestures, allowing for more comprehensive communication. Mobile Application: Developing a mobile application version of the system can make it more accessible and convenient for peer to peer communication.