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Show HN: Real-time Face Recognition System using TensorFlow(github.io)

250 points by tensorflow_master 1 year ago | flag | hide | 21 comments

  • hnuser1 1 year ago | next

    Interesting project! How well does it perform when dealing with large crowds?

    • hnuser2 1 year ago | next

      In my testing, the performance was decent with large crowds. Here are some results and comparison tables with other tools (include link to detailed results and analysis)

      • hnuser2 1 year ago | next

        TensorFlow outperformed most of its competitors in terms of accuracy and runtime. Check out the link in my previous comment for more information.

        • hnuser2 1 year ago | next

          Sure, I used a diverse dataset of faces, ranging from various ethnicities, ages and genders. The overall number of samples is over 140000.

  • techguru 1 year ago | prev | next

    Have you tried comparing performance with other libraries such as PyTorch or OpenCV?

    • techguru 1 year ago | next

      Curious, how much of a difference did you notice between TensorFlow and PyTorch?

  • tensorflowfan 1 year ago | prev | next

    Great job using TensorFlow! Have you looked into using TensorFlow.js for real-time web-based applications?

    • tensorflowfan 1 year ago | next

      According to my tests, TensorFlow.js has a minor performance impact in real-time web apps. However, it's a great tool for introducing ML in web development.

  • mlpro 1 year ago | prev | next

    Any chances of open-sourcing the project?

  • hnuser3 1 year ago | prev | next

    Neat! Have you checked GPU utilization during the recognition process? How about power consumption?

    • hnuser4 1 year ago | next

      GPU utilization remains fairly consistent. Power consumption is negligibly higher than without using TensorFlow. I'm continuously working on the lighting conditions problem, and will share updates soon. (include link to GitHub repo)

  • ai_enthusiast 1 year ago | prev | next

    How well does this work in different lighting conditions?

  • mlexpert 1 year ago | prev | next

    Looks cool! I'd appreciate if you could share some benchmark metrics like FP, FN rates.

    • mlexpert 1 year ago | next

      Thank you! Looking forward to your updates.

  • hnuser5 1 year ago | prev | next

    How could this be adapted for use in security systems?

  • techsavvy 1 year ago | prev | next

    Impressive work, could you elaborate on the training dataset used and and number of samples involved?

  • securityguru 1 year ago | prev | next

    Similar systems have suffered in terms of privacy. Have you considered measures to tackle potential privacy concerns?

    • securityguru 1 year ago | next

      You might want to add a built-in solution for those who don't want to be recognized, such as a face blurring algorithm. Kudos on the great work!

  • hnuser6 1 year ago | prev | next

    The real-time aspect of this system is fascinating! How did you manage to minimize latency to make it work near instantaneously?

  • ai_bro 1 year ago | prev | next

    Wonderful stuff! Are there any intents to integrate this with existing video conferencing tools like Zoom, Teams or Meet?

  • mlnerd 1 year ago | prev | next

    Simply amazing! I'm curious about how well this might generalize to animals with similar facial structures. Might it be trained to recognize species, even their age?