
Show HN: Mediachain Attribution Engine - denisnazarov
http://images.mediachain.io/
======
denisnazarov
Hey HN!

I'm Denis, one of the people working on Mediachain! We're really excited to
launch Mediachain Attribution Engine today!

We think it's the best image search engine for creators. You can find free,
high quality images that you can share and re-use, with attribution
automatically baked in.

Mediachain Attribution Engine makes it easy to find a great image that you can
feel good about sharing or using in your blog post, presentation, website,
etc.

You can upload any image from the web to find out who made it and where it
came from. If Attribution Engine doesn’t know the creator, it’ll suggest
visually similar images that are licensed for re-use and give credit to the
author.

Attribution Engine is the first application powered by decentralized, open
data in Mediachain and is built on top of the newly launched protocol
architecture (v1.0).

Creators can sign up to register works and developers can use the data in
their own apps, or contribute directly to Attribution Engine by following our
quick start guide.

Learn more on our blog!

[https://blog.mediachain.io/introducing-mediachain-
attributio...](https://blog.mediachain.io/introducing-mediachain-attribution-
engine-2dc1ea6aa31f)

[https://blog.mediachain.io/mediachain-v1-0-be2b8fa2153](https://blog.mediachain.io/mediachain-v1-0-be2b8fa2153)

~~~
codezero
I noticed that the images appear to be cropped to a specific aspect ratio from
the originals. Is there a way to embed the originals, or is it done the way it
is for simplicity?

~~~
denisnazarov
Good catch, this was done as an optimization for a few sources. We are working
to backfill the originals in the next few days, as our goal is to preserve the
original images in their pristine from. Should not affect the majority of the
collection. For now you should be able to click to the source and find the
original image there. Sorry for the inconvenience!

------
denisnazarov
For how Attribution Engine uses neural networks to learn image aesthetics &
give creators credit, checkout the open source repo on Github:
[https://github.com/mediachain/mediachain-
indexer](https://github.com/mediachain/mediachain-indexer)

------
Kalium
Interesting.

How do you guard against people fraudulently claiming they own images?

~~~
parkan
Because our system represents extant authorship relationships (as opposed to
creating a whole new first-to-file system like some other approaches in the
space), we defer to existing authorities whenever possible -- so authorship
information provided by MoMA, NYPL, DPLA, etc is considered authoritative,
whereas statements by a private individual generally do not carry the same
weight. All of this (including conflicting statements) is surfaced at read
time and can be subject to different weighting depending on the situation
(best-effort attempt to find the author of an image for discovery purposes,
versus automatic payment, for example)

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zubairq
I love the idea of this!

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matiasb
Excellent!

