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https://github.com/dragonscypher/tryspec
A VTO
https://github.com/dragonscypher/tryspec
cv2 dlib face-detection numpy python3
Last synced: 9 days ago
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A VTO
- Host: GitHub
- URL: https://github.com/dragonscypher/tryspec
- Owner: dragonscypher
- License: mit
- Created: 2024-02-15T00:54:49.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-10-30T02:22:48.000Z (20 days ago)
- Last Synced: 2024-10-30T04:59:25.246Z (20 days ago)
- Topics: cv2, dlib, face-detection, numpy, python3
- Language: Python
- Homepage:
- Size: 549 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Virtual Try-On System: Tryspec 💎
## Introduction
Welcome to the Virtual Try-On (VTO) System, a cutting-edge application designed to revolutionize the online shopping experience. Utilizing advanced Augmented Reality (AR), Computer Vision, and deep learning techniques, this system aims to offer users a seamless way to virtually try on accessories like glasses and hats in real time. 🚀## Project Objective 🌟
The primary objective of this project is to provide an enhanced virtual shopping experience by allowing users to interact with products before making a purchase. This reduces uncertainty, builds confidence, and bridges the gap between online and in-store shopping.## Features and Benefits 🏠
- **Real-Time Try-On**: Leveraging AR, users can see how accessories look on them instantly, enhancing the shopping experience.
- **Dynamic Product Selection**: Browse and toggle between various glasses and hats, allowing users to see different styles at the click of a button.
- **Adaptive Personalization**: Adjusts the position and size of accessories dynamically based on facial landmarks, ensuring accurate fitting.
- **User-Friendly Experience**: Simple and intuitive interface designed for effortless use across all demographics.## Technology Stack 🛠️
- **Computer Vision & AR**: Powered by OpenCV and MediaPipe, for precise facial landmark detection and accurate overlay of virtual accessories.
- **Machine Learning**: Enhanced personalization of the try-on experience by learning from user interactions.
- **Python**: The primary programming language used, leveraging libraries like NumPy and OpenCV.## Implementation Highlights 🤖
- **Landmark Detection**: Utilizes MediaPipe's face mesh to identify facial landmarks in real time, providing accurate points to position accessories like glasses and hats.
- **Dynamic Sizing and Positioning**: Facial dimensions are calculated dynamically to adjust accessory scaling, ensuring a realistic and comfortable fit.
- **Real-Time Selection**: Users can toggle between different styles of glasses and hats by pressing keys, providing an interactive and exploratory shopping experience.## How to Use 📜
1. **Start the Camera**: Launch the application, and the webcam will automatically turn on.
2. **Select Accessories**: Press 'g' to toggle between different glasses and 'h' to toggle between hats.
3. **See Yourself**: The selected accessory will be dynamically adjusted and positioned to give a realistic look.
4. **Quit**: Press 'q' to exit the application at any time.## Future Directions 💡
- **Expanded Product Range**: Broader variety of accessories, such as scarves, earrings, and clothing.
- **Social Sharing**: Integrating features that allow users to share their virtual try-on experience on social media platforms.
- **Deeper Personalization**: Improving the recommendation engine to suggest products based on facial features, preferences, and user history.## Challenges and Solutions 💪
- **Real-Time Processing**: Optimized image processing techniques and reduced computational overhead to achieve smooth performance with minimal lag.
- **Accessory Fitting**: Enhanced fitting algorithms to ensure glasses and hats accurately follow the user's head movements, even with rapid changes.