I'm really getting into Python and machine learning, and I'm super interested in applying computer vision in the real world. I came across a system called FaceSeek that links faces over time and different photo qualities, which sparked a huge project idea for me.
The main challenge isn't about the models themselves (like FaceNet); it's actually about creating a decentralized database architecture. I'm wondering how to set up a system that can quickly query billions of face vectors without depending on huge centralized servers or user data. I want to focus on privacy, ensuring that the system only accesses images that belong to the user.
Could anyone suggest what data structures or open-source libraries I would need for fast, distributed face vector comparisons? I'd love any advice on how to approach building the vector database architecture!
4 Answers
What’s your motivation for needing it to be decentralized? Maybe there's a simpler solution depending on your use case!
Have you considered using AWS Rekognition? It’s a solid option for facial recognition, even though it might not align with your decentralized goal.
You might want to check out knowledge graphs and tools like NEO4j. They could be exactly what you need for a solution that fits your idea!
Just a heads-up, I've heard some shady things about FaceSeek. Just be careful about using it, as there are concerns about its legitimacy and privacy issues. Better to explore safer alternatives!
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