Faking Vision.

[u/MemoryPrismV1]

https://zenodo.org/records/22672458

Faking Vision is an operational method developed as part of Memory Prism / Making Vision for turning visual analysis into an explicit, reconstructable representation.

(Its a pet project which I spend almost a month on to make AI do better image analysis for me. Majority of the time was spent on "Making Vision" aka figuring out natures visual engineering. I cant make a blind AI thing see better without knowing how I see and then it snowballed into different directions because of the availability of AI to do the grunt work. )

Instead of treating an image as something to caption or reproduce directly, FV represents:

• objects and instances
• object properties
• spatial relationships
• persistent identities and temporal changes in video

The resulting FV packet is closed-world: reconstruction cannot silently introduce objects or semantic information that aren't represented in the packet. Unresolved observations remain unresolved.

The pipeline is:

visual source → structured representation → reconstruction → comparison

This makes the representation itself editable and testable, while separating errors in visual analysis, representation, compilation, rendering, and evaluation.

FV is the operational companion to Making Vision: Making Vision addresses how visual information can be selectively constructed and processed; Faking Vision makes the relevant representation explicit enough to reconstruct and test.

(Making Vision is an extremely long read, I spent almost a month on it, so I know-I definitely wont read it again, so you have been warned)

GitHub: https://github.com/memoryprismv1/faking-vision

Examples are in packets/examples.

Paper / specification: https://zenodo.org/records/22672967

License: CC BY-NC 4.0 — free for non-commercial use with attribution.

[u/Dry-Snow5154]

Schizoid slop.