Overview / Usage

Introducing "Boot Brain," an innovative game-based E-learning website that offers a dynamic platform for children to embark on an interactive learning journey. Harnessing the power of image recognition technology, web scraping, and text-to-speech capabilities, Boot Brain transforms the way kids engage with educational content. By simply placing objects before their camera, children unlock a world of knowledge. The platform seamlessly identifies objects, retrieves accurate and age-appropriate information from reputable sources on the web, and delivers captivating audio descriptions through advanced text-to-speech functionality. This immersive approach not only fosters curiosity and critical thinking but also ensures that learning is retained through engaging interactions. With an intuitive, child-friendly interface characterized by vibrant colors and intuitive navigation, Boot Brain creates a safe and enriching space for kids to explore, learn, and grow.

Methodology / Approach

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• Importing Libraries
• Data Importing
• Data Exploration
• Preparing the Data
  • Creating a Generator for Training Set
  • Creating a Generator for Testing Set
• Writing the labels into a labels.npy
• Model Creation
• Model Compilation
• Training the Model ( epochs = 100)
• Testing Predictions
• Saving model as 'model.h5'
• Deploying the Model as a Web Application using Django ,and desktop applicationTkinter

Technologies Used

• oneAPI/one
• Devcloud
• Python
• Django
• Tkinter
• cvzone
• Tensorflow
• openvino
• DNN
• ​

Other links

• GitHub (https://github.com/LavanyaR007/Hackathon_Boot_Brain.git)

Collaborators