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Automatically “block” people in images using a pretrained neural network

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Re: Automatically “block” people in images using a pretrained neural network

#41
post #35

Earlier quoted context omitted.

The age old justification of "if I don't do it, someone else will". You can justify many things with that. I happen to think this particular technology is cool and it's silly to be afraid of it, but no need to employ that justification.

But I think some things are justifiable by that argument. A great example of that is the public disclosure of software vulnerabilities. If you’re not malicious, and you find a bad bug, chances are a malicious actor will eventually find the bug too.

The equivalent example would be: "I might as well hack this account and take all the money because if I don't, someone else will".

I have no problem with: "I should inform the developers of the vulnerability (perhaps publicly to pressure them) so that it will be fixed because someone will hack it otherwise".

Re: Automatically “block” people in images using a pretrained neural network

#42

What purpose does this serve? I'm genuinely curious what are the applications of this?

Imagine wearing AR glasses and blocking out people you find annoying or disagree with.

Or animals that frighten you.

Re: Automatically “block” people in images using a pretrained neural network

#43

The road to hell is paved with good intentions. And I think software engineers are this century's key perpetrators of "good intentions." Here's a hint: if you saw it in a dystopic thriller you probably don't need to build it, even out of morbid curiosity.

Every invention/technology eventually will be used also to harm people, even those which were never meant to be used as such, from electricity to airplanes. Unfortunately seeing anything in a dystopic thriller also means someone else, not just the writer, has already thought about using it. Making more people aware can do more good than harm IMO.

This technology is in its infancy; I fear the day a policeman wearing an encoded transmitter will be able in real time to force all security cameras in the area to exclude his image and cover it with normal background when he knows he abused his power or is going to.

Re: Automatically “block” people in images using a pretrained neural network

#44
post #35

Earlier quoted context omitted.

But I think some things are justifiable by that argument. A great example of that is the public disclosure of software vulnerabilities. If you’re not malicious, and you find a bad bug, chances are a malicious actor will eventually find the bug too.

The equivalent example would be: "I might as well hack this account and take all the money because if I don't, someone else will". I have no problem with: "I should inform the developers of the vulnerability (perhaps publicly to pressure them) so that it will be fixed because someone will hack it otherwise".

We were literally talking about building technologies that might be used in harmful ways. Discovering and developing software exploits is a direct example of this.

Re: Automatically “block” people in images using a pretrained neural network

#45

The road to hell is paved with good intentions. And I think software engineers are this century's key perpetrators of "good intentions." Here's a hint: if you saw it in a dystopic thriller you probably don't need to build it, even out of morbid curiosity.

You can't stop progress, even if it's negative. Especially something that is relatively easy to make. If nukes were easy to make, we'd all be dead.

Re: Automatically “block” people in images using a pretrained neural network

#46

The road to hell is paved with good intentions. And I think software engineers are this century's key perpetrators of "good intentions." Here's a hint: if you saw it in a dystopic thriller you probably don't need to build it, even out of morbid curiosity.

You can't stop progress, even if it's negative. Especially something that is relatively easy to make. If nukes were easy to make, we'd all be dead.

You can't. But you can choose not to be part of it. I refused politely an interview with google and facebook for the same reason in the past.

The world is what you make of it

People keep saying you can't change the world. That you can't do anything about it.

Well yes you can. Don't be part of it.

Oh yes, there is a price to pay.

Re: Automatically “block” people in images using a pretrained neural network

#47

The road to hell is paved with good intentions. And I think software engineers are this century's key perpetrators of "good intentions." Here's a hint: if you saw it in a dystopic thriller you probably don't need to build it, even out of morbid curiosity.

You can't stop progress, even if it's negative. Especially something that is relatively easy to make. If nukes were easy to make, we'd all be dead.

Right. And if babies were easy to kill, our mothers all would have killed us right then and there, but thankfully that's really hard to do.

Re: Automatically “block” people in images using a pretrained neural network

#48
post #14

This would combine well with an in-painting algorithm-- or the video equivalents: https://research.adobe.com/project/content-aware-fill/ https://www.youtube.com/watch?v=j3uCV0JYMJ4

Will someone kindly smash this repo https://github.com/fivemok/image-inpainting together with the submission?

Or, https://github.com/DmitryUlyanov/deep-image-prior

Re: Automatically “block” people in images using a pretrained neural network

#49
This doesn't seem to work for me. I ran "python person_blocker.py -i images/img1.jpg -l" after installing dependencies and I only get:

/home/d33tah/virtualenv-py3/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.

  from ._conv import register_converters as _register_converters
Using TensorFlow backend.

2018-03-31 12:53:18.777911: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA /usr/lib/python3/dist-packages/scipy/misc/pilutil.py:480: FutureWarning: Conversion of the second argument of issubdtype from `int` to `np.signedinteger` is deprecated. In future, it will be treated as `np.int64 == np.dtype(int).type`.

  if issubdtype(ts, int):

/usr/lib/python3/dist-packages/scipy/misc/pilutil.py:483: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.

  elif issubdtype(type(size), float):

Re: Automatically “block” people in images using a pretrained neural network

#50
post #18

The road to hell is paved with good intentions. And I think software engineers are this century's key perpetrators of "good intentions." Here's a hint: if you saw it in a dystopic thriller you probably don't need to build it, even out of morbid curiosity.

I have not watched the dystopic thriller you mention, so I don't know what kind of drawbacks you are expecting, but I think this technology might have some useful applications. E.g. an image-upload site could answer requests for deletion on privacy grounds not by taking the whole image down, but by obscuring only parts of the image. Or imagine you're taking a selfie in a crowded place and don't want all those other p…

tl;dw: the concept has been toyed with in a number of episodes:

Imagine the death penalty was replaced by a simple "ban" from everybody else's perception. Instead of being put to death, you just appear as an outline filled with static and your voice appears as garbled noise.

Alternatively, imagine "parental controls" for a child's perception that automatically filters out "unsafe" content like sex, violence, hobos, hookers and hate speech.

Or imagine altering a soldier's perception to make enemy combatants appear less human so empathy doesn't get in the way of a clean kill.

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