Virtual Spectacles Try-On using OpenCV & Python | Face Landmarks | Full Source Code Explained
👓 In this video, I demonstrate how to build a REAL-TIME Virtual Spectacles Try-On application using Python, OpenCV, and Computer Vision.
This project uses a live camera feed to detect facial landmarks and accurately place different spectacle frames on the user's face — just like modern AR try-on systems used by e-commerce brands.
🔥 What you’ll learn in this video:
✔️ Live face detection & landmark tracking using OpenCV
✔️ How virtual spectacles are aligned perfectly on the face
✔️ How to dynamically add new spectacle frames
✔️ Flask-based web interface for real-time try-on
✔️ Frontend carousel for selecting different frames
✔️ Complete backend & frontend code explanation
✔️ How real-world virtual try-on systems work
📌 Key Features of the App:
• Real-time camera feed
• Multiple spectacle styles
• Smooth and accurate face alignment
• Interactive and modern UI
• Easily extensible (add new frames in seconds)
💡 This project is perfect for:
✔️ Computer Vision learners
✔️ Python & OpenCV developers
✔️ Final-year / mini-project students
✔️ AR / AI enthusiasts
✔️ Resume-worthy portfolio projects
📂 Source Code:
🔗 https://github.com/jaingaurav126/Spcs...
👍 If you enjoyed this video, don’t forget to LIKE, SHARE & SUBSCRIBE for more AI, Computer Vision, and real-world Python projects!
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