The Virtual Fitting Room is a web application that allows users to try on clothing items virtually by overlaying 2D images of garments onto an image of the user. The application is built using Flask for the backend and uses OpenCV for image processing. The front-end is powered by HTML, CSS, and JavaScript, while Django manages user authentication and other functionalities.
- User Authentication: Secure registration and login system managed by Django.
- 2D Garment Fitting: Upload a photo and try on clothing items virtually.
- Image Processing: Real-time image processing using OpenCV to adjust the garment's position and size based on the user's image.
- Responsive Design: The application is designed to work across various devices and screen sizes.
- Backend: Flask, Django, Python
- Frontend: HTML, CSS, JavaScript
- Image Processing: OpenCV
- Database: MySQL (or any other database supported by Django)
git clone https://github.com/dishvyas/fittingroom.git
cd fitting-roompython3 -m venv venv
source venv/bin/activate
# On Windows use `venv\Scripts\activate`pip install -r requirements.txtSet up your database (e.g., MySQL) and update the database configuration in the Django settings.
# settings.py
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.mysql',
'NAME': 'your_db_name',
'USER': 'your_db_user',
'PASSWORD': 'your_db_password',
'HOST': 'localhost',
'PORT': '3306',
}
}
If you're using Django's ORM, apply the migrations to create the necessary database tables.
python manage.py makemigrations
python manage.py migrateDownload the necessary pre-trained model for landmark detection:
• File: shape_predictor_68_face_landmarks.dat or the appropriate model you’re using.
• Source: Available here - http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2
Place the model file in a directory accessible by the Flask app, typically under the project root or a dedicated models/ directory.
python manage.py runserver # Starts the Django app
python app.py # Starts the Flask appThe application will start on:
• Django: http://127.0.0.1:8000/
• Flask: http://127.0.0.1:5001/
- Register and Log In: Create an account and log in.
- Upload Image: Upload a photo of yourself to the application.
- Virtual Fitting: Select a garment to try on, and the application will overlay it onto your uploaded image.
- View Results: See how the clothing item looks on you with options to download or share the fitted image.
.
├── app.py # Flask application file
├── model2d.py # Handles 2D model fitting logic
├── fittingroom/ # Django app for user management and authentication
│ ├── __init__.py
│ ├── settings.py # Django settings
│ ├── urls.py # URL routing for Django app
│ ├── views.py # Views for handling HTTP requests
│ ├── templates/ # HTML templates
│ ├── static/ # Static files (CSS, JS, images)
│ ├── migrations/ # Database migrations
│ ├── forms.py # Django forms for user creation and login
├── models/ # Directory to hold pre-trained models
│ ├── shape_predictor_68_face_landmarks.dat # Pre-trained model for landmark detection
├── requirements.txt # Python dependencies
├── README.md # This README file
└── ...
- 3D Virtual Fitting: Extend the functionality to allow for 3D virtual fitting using advanced image processing techniques.
- Improved Image Processing: Enhance the image processing algorithms to support more complex garments and better fit accuracy.
- User History: Implement a feature to save and view past fittings.
- Social Sharing: Add options to share the fitted images on social media platforms.
Contributions are welcome! Please fork this repository, make your changes, and submit a pull request.
This project is licensed under the MIT License - see the LICENSE file for details. ](https://github.com/dishvyas/fittingroom)