One of the biggest context AI LLMs can get from images is their metadata, but it's extremely underutilized. and while PNG and JPEG both offer metadata, it gets stripped way too easily when sharing and is extremely limited for AI based workflows and offer minimal metadata entries for things that are actually useful. Plus, these formats are ancient (1995 and 1992) - it's about time we get an upgrade for our AI era. Meet MEOW (Metadata-Encoded Optimized Webfile) - an Open Source Image file format which is basically PNG on steroids and what I also like to call the purr-fect file format.
Instead of storing metadata alongside the image where it can be lost, MEOW ENCODES it directly inside the image pixels using LSB steganography - hiding data in the least significant bits where your eyes can't tell the difference, this also doesn't increase the image size significantly. So if you use any form of lossless compression, it stays.
What I noticed was, Most "innovative" image file formats died because of lack of adoption, but MEOW is completely CROSS COMPATIBLE WITH PNGs You can quite literally rename a .MEOW file to a .PNG and open it in a normal image viewer.
Here's what gets baked right into every pixel:
- Edge Detection Maps - pre-computed boundaries so AI doesn't waste time figuring out where objects start and end.
- Texture Analysis Data - surface patterns, roughness, material properties already mapped out.
- Complexity Scores - tells AI models how much processing power different regions need.
- Attention Weight Maps - highlights where models should focus their compute (like faces, text, important objects)
- Object Relationship Data - spatial connections between detected elements.
- Future Proofing Space - reserved bits for whatever AI wants to add (or comments for training LORAs or labelling)
Of course, all of these are editable and configurable while surviving compression, sharing, even screenshot-and-repost cycles :p
When you convert ANY image format to .meow, it automatically generates most AI-specific features and data from what it sees in the image, which makes it work way better.
Would love thoughts, suggestions or ideas you all have for it :)
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Hi hackers!
I'm a self-taught solo teenage dev working on Seastar, a unified build system and dependency manager for C and C++. It is capable of compiling and linking projects, managing recursiv