A computer vision virtual classroom application that leverages computer vision technology to provide an immersive and interactive learning environment for students and teachers in a remote setting.
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Table of Contents
Our application uses computer vision technology to create virtual classrooms with real-time interactions and machine learning models to generate transcripts of real-time writing. With a user-friendly tkinter GUI, this app enhances the virtual learning experience for teachers and students.
- Python
- OpenCV
- Keras
- TensorFlow
- Tkinter
- MediaPipe
Before getting a local copy up, you must ensure that you have the necessary software required.
- Clone the repo
git clone
- Create a virtual environment.
python -m venv env - Activate the virtual environment.
source env/bin/activate # for Linux/MacOS env\Scripts\activate # for Windows - Install the required packages.
pip install -r requirements.txt - (Optional) If you wish to train the model yourself, the dataset will be given below, the file is handwriting_model_train.ipynb.
- Run the GUI using the command below.
python frontend.py
The dataset used for training the ML model can be found here.
- A screen recording feature could be added to allow users to record their entire screen or a specific window while recording a video.
- Integration with Learning Management Systems (LMS): The application could be integrated with popular LMS platforms to streamline the classroom experience for both teachers and students.
- Cloud storage: A cloud storage feature could be added to allow users to store their recorded videos securely and access them from anywhere.
See the open issues for a full list of proposed features (and known issues).
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
Distributed under the MIT License. See LICENSE.txt for more information.
Pratik Jallan - pratikjalan11@gmail.com
Project Link: https://github.com/Yukino2002/Interacti