HooYa! is an IPFS-like network for sharing and downloading files tagged with rich semantic metadata. Network participants provide a folksonomy of descriptive, searchable tags and metadata for the set of all files across the network. For those familiar with image boorus, consider it a P2P booru.

In the spirit of dogfooding, I use HooYa! to organize my own media even as I build it. For example, I run a private HooYa! network on my home Kubernetes cluster providing all images and videos on this site, including the media on this very page (hooyaception). All code is developed under an open source license and available on GitHub.

As of May 2024 I am rapidly developing a Next.js frontend hooya-web-ui, pictured below. I will deploy a public demo instance soon™.

HooYa! aspires to become completely autonomous and self-governing by issuing its own governance tokens for use in image proposal / acceptance and metadata tagging. It also seeks to incentivize the on-chain commission + minting of new artworks by manga & dōjin artists (hereafter "illustrators") via these governance tokens.

However before I tackle the implementation of network governance, I am focused on building the P2P overlay network for file-sharing and making this a pleasant software to use and host that can be used to organize personal file storage and exchange semantically rich metadata.

Background

The service HooYa! will provide is not novel; it finds inspiration from a handful of Web2 companies (mainly Japanese ones) and from the communities that form around these companies and the illustrators they support. I see HooYa! as a combination of these two communities in particular:

• Pixiv, a Japanese-language community of illustrators who connect with fans by posting original and derivative artworks
• Danbooru, a community dedicated to the archive of illustrations like those posted on pixiv, known mostly for its extensive vocabulary of tags used for organizing and labelling these images

The wealth of information provided by Danbooru has helped many unique projects to create machine-learning models that can both (a) predict appropriate tags for a given illustration (example, src) and (b) generate new illustrations that resemble the Japanese style (example, background).

HooYa! will leverage these pioneering predictive models to suggest tags on images submitted for inclusion on the network.

What is Pixiv?

Pixiv is a community of primarily Japanese illustrators who upload their illustrations, comics and short stories and share them with other pixiv members. This is one of the primary ways that illustrators can connect with their communities and make their artwork accessible to their fans. It is the 10th most visited site in Japan and is most popular among young Japanese illustrators and their fans.

Pixiv offers a Patreon-like subscription program called pixivFANBOX which connect fans with illustrators publishing derivative and original illustrations on a regular basis by providing fans in each subscriber tier with special goods, articles and hi-res renders of illustrations released by the artist.

Because drawing is a popular hobby in Japan (and one which is gaining popularity abroad) the idea of earning a living as an illustrator has attracted many creators, both Japanese and internationals, to the Pixiv platform.

In addition to subscription services pixiv also provides a space for illustrators to sell their illustrations, manga (both short- and long-form) and artbooks on its BOOTH site. These can be digital-only releases but there are also physicals for sale which are produced through its pixivFACTORY service.

Fans can commission personal works from illustrators by a feature on pixiv known as Requests. Requests can be funded entirely by an individual or can be crowd-funded by many fans pooling cash together to commission the piece.

Finally, Pixiv lets fans and illustrators to add a limited set of tags to an image (up to 10) to an image. These Pixiv tags are more akin to hashtags on Twitter than semantic metadata as seen on sites like Danbooru.

Danbooru

Danbooru is a community that tags and archives images from Pixiv, Twitter, DeviantArt and many other platforms. Each image submitted for inclusion on Danbooru goes through a 3-day review period after which it is either accepted or denied inclusion into the Danbooru canon. Danbooru maintains a large vocabulary of tags which are key-value pairs used to describe an image. This makes the set of images easily searchable by specifying (eg) the illustrator, character, franchise or any objects in an image.

As shown above Danbooru lets me search things such as: illustrations of the Love Live! franchise which include product placement of some kind, by issuing the query love_live! product_placement. From left to right, top to bottom these are the Subaru WRX, Starbucks, Coca-Cola, Sprite and the Yamaha Vino. Danbooru limits searches to 2 tags unless the user has purchased a Gold account, in which case the limit is raised to 6. Gold accounts cost a one-time purchase of $20 USD.

Danbooru hosts over 4.9 million images tagged with 162 million tags, of 498k unique tags as of the end of 2021. A single copy of this data consumes 4.5 terrabytes of disk space.

As alluded to earlier, this massive data set has allowed researchers to create predictive models leveraging neural networks to label the objects in a brand new illustration, thus reducing the workload on a single user tagging an image. In addition to predictive models, generative adversarial networks (in particular NVIDIA's StyleGAN) have been trained with the Danbooru set to draw brand new illustrations when prompted with a series of tags.

To the left is Gwern's Danbooru2018 portrait model trained to generate portraits in the Danbooru style (credit Gwern for the model and video). Each image in the interpolation is unique in that it is an original of the GAN, and though the model was seeded from the images collected on Danbooru the portraits are original creations.

What is HooYa! to Pixiv and Danbooru?

HooYa! is built from first principles to be P2P software. This differentiates it from Danbooru, which is centralized, and Hydrus, which is not P2P.

The addition of token governance allows HooYa! to compete in the niche that Pixiv and other commission platforms fill now with the Japanese and Otaku market, by facilitating artwork commissions. A convenient consequence of being a P2P file-sharing network with on-chain governance is that art comissioned on the blockchain that supplies the governance layer could be stored trivially on the overlay network.