Other samples:
Android: https://github.com/nipunru/nsfw-detector-android
Flutter (BSD-3): https://github.com/ahsanalidev/flutter_nsfw
Keras MIT https://github.com/bhky/opennsfw2
I feel it’s a good idea for those building native clients for Lemmy implement projects like these to run offline inferences on feed content for the time-being. To cover content that are not marked NSFW and should be.
What does everyone think, about enforcing further censorship, especially in open-source clients, on the client side as long as it pertains to this type of content?
Edit:
There’s also this, but it takes a bit more effort to implement properly. And provides a hash that can be used for reporting needs. https://github.com/AsuharietYgvar/AppleNeuralHash2ONNX .
Python package MIT: https://pypi.org/project/opennsfw-standalone/
It’s an interesting idea, and given the direction some economies are moving (looking at you EU & UK) something like this is likely going to feature whether we like it or not. The question for me however is what is the nature of the training data? What some places consider “porn” (Saudi Arabia, the Vatican, the US) is just people’s bodies in more civilised places. Facebook’s classic “free the nipple” campaign is an excellent example here: why should anyone trust that this software’s opinion aligns with their own?
Yeah. Have been thinking of this exact scenario. How to create solutions around anything that might “filter” while respecting the worldviews of all. I feel the best approach so far, is if filters are to be implemented. It should never be a 1 all be all and should always be “a toggle”. Ultimately respecting the user’s freedom of choice while providing the best quality equipment to utilize effectively when needed