Face Matching

This project houses two implementations of recognizing human faces, particularly those present in the publicly available 'LFW' dataset (more than 13,000 images; faces recognized with facenet-pytorch) and 'Indian Actor Faces' dataset (more than 5,000 images; faces recognized with face_recognition).

Technologies Used

• Developed using VS Code, Jupyter Notebook and Google Colab
• Python and it's libraries - Flask, Pytorch, face_recognition, pickle, faiss, Pillow, opencv and more
• match_face and recognise_actor APIs tested with Postman

Potential improvements that I want to implement:

• Implementing a Vector DB, like Milvus for practical applications like managing attendance
• Using libraries like deepface
• Handling multiple persons in an image
• Adding more information for better face matching!

Acknowledgements

Thanks to Akshay sir, Abhishek sir, Roshan sir, Himanshu sir, Balesh sir, and Mayank for the constant guidance and support.
Thanks to Cubastion Consulting Pvt. Ltd. for a productive and supportive environment that fosters learning.