all 12 comments

[–]EternalSunset 3 insightful - 3 fun3 insightful - 2 fun4 insightful - 3 fun -  (0 children)

That's cool.

[–]Entropick 2 insightful - 3 fun2 insightful - 2 fun3 insightful - 3 fun -  (0 children)

Sugary!

[–]neolib 1 insightful - 2 fun1 insightful - 1 fun2 insightful - 2 fun -  (6 children)

Do you plan to implement perceptual image hashing (https://en.wikipedia.org/wiki/Perceptual_hashing)? It would be possible to ban bad images by hash then (and also it's useful for finding alternative versions of images - of better quality for example).

[–]x0x7[S] 2 insightful - 3 fun2 insightful - 2 fun3 insightful - 3 fun -  (2 children)

Interesting. It's strange that it doesn't talk about techniques. Wikipedia articles are usually vebose. I know about similar methods using auto-encoders. I have done image categorization with resnet-50, which is an AI that uses auto-encoders. Before reading that article auto-encoders would have been how I would have done it similar image finding.

I'm going to add that to my scrum and I'll be assessing that.

[–]neolib 1 insightful - 1 fun1 insightful - 0 fun2 insightful - 1 fun -  (1 child)

it doesn't talk about techniques

It's all scattered among different articles - external links in "Perceptual hashing" page, algorithms section in https://en.wikipedia.org/wiki/Reverse_image_search , some vague description in https://en.wikipedia.org/wiki/PhotoDNA (this one is big: "As of 2022, PhotoDNA was widely used by online service providers for their content moderation efforts including Google's Gmail, Twitter, Facebook, Adobe Systems, Reddit, Discord.")

[–]x0x7[S] 2 insightful - 2 fun2 insightful - 1 fun3 insightful - 2 fun -  (0 children)

The problem with using PhotoDNA is I don't want to send visual data of every image a user uploads to a third party. Sure they can help you categorize one thing you need to moderate, but are they categorizing in more ways then one on their back end?

Having done some reading I'd be more interested in latent space representation that can help me find similar themed images over a technology intended to find the same image (what perceptual hash is for). That's doing 7/8th of the copyright harassers job for them. Technically cool, practically stupid and low value for anyone I want to produce value for.

[–][deleted] 1 insightful - 2 fun1 insightful - 1 fun2 insightful - 2 fun -  (2 children)

That's easy

[–]neolib 1 insightful - 1 fun1 insightful - 0 fun2 insightful - 1 fun -  (1 child)

PhotoDNA (which big websites use) is closed source though, and it's unclear (for me) whether open source ones from wiki article are good enough (https://www.phash.org & https://github.com/commonsmachinery/blockhash/).

[–][deleted] 3 insightful - 1 fun3 insightful - 0 fun4 insightful - 1 fun -  (0 children)

I have a C source file I can post. As I recall, the keywords are ahash, vhash, and ddhash. Or you can always go hacky and just downsample the colors to 5 bits and simhash the thing.

[–]tarafoster 1 insightful - 2 fun1 insightful - 1 fun2 insightful - 2 fun -  (0 children)

Thanks for sharing.. https://www.tigerishome.us/

[–]iamonlyoneman 1 insightful - 1 fun1 insightful - 0 fun2 insightful - 1 fun -  (0 children)

just use imgur

[–]In-the-clouds 1 insightful - 1 fun1 insightful - 0 fun2 insightful - 1 fun -  (0 children)

one low cost enough to stay up forever

cost reduction advantages

I just tested it and it took an image without me having to create an account or pay any money.

Is this free for us to use? What are the "costs"?