Emergrade is an ambitious, full-stack web application built on Django that seamlessly integrates Virtual Try-On (VTON) technology with Brain-Computer Interface (BCI) data processing. The core mission is to explore how a user's real-time cognitive state, captured via Electroencephalography (EEG), can influence or personalize a virtual clothing try-on experience.
- Virtual Try-On (VTON) Core: Utilizes a computer vision model (likely a Hugging Face model, based on testing scripts) to accurately composite new garment images onto a target person's photo. A dedicated HTML page (
vton_demo.html) serves as the primary front-end for this feature. - Django Web Application: Provides a robust and scalable web framework for the entire platform, handling user interactions, data storage (
db.sqlite3), and the presentation layer. - EEG/BCI Integration: Processes physiological data by acquiring, handling, and analyzing EEG signals (specifically Delta, Theta, Alpha, Beta, Gamma band powers). Dependencies on
muselslconfirm support for streaming data from devices like the Muse headset. This data is the unique layer informing the "NeuroStyle" experience.
This project requires a Python environment managed by Pipenv (using Pipfile).
- Clone the Repository:
git clone [Your Repository URL]
- Install Dependencies:
pipenv install pipenv shell
- Run the Django Server:
python manage.py runserver
EEG band power data is present (eeg_band_powers*.csv), indicating a focus on analyzing cognitive states. The application logic connects the VTON outputs to this neuro-data, paving the way for research into personalized digital commerce or cognitive feedback systems.