Layerage
A collage tool that uses neural image similarity to make patterns inside thousands of community-created layers explorable.
Layerage builds collages out of r/Layer, Reddit’s community canvas, made in partnership with Adobe and once open for everyone to draw on, in the spirit of r/place. Tens of thousands of small drawings accumulated there, and I was so intrigued by their creativity and granularity that I had to experiment on them: first with timelapses while r/Layer was still running, then with a zoomable explorer for all the layers, built on VIKUS Viewer, and finally with this tool, which felt more accessible for everyone.
Search for a layer, hit build, and Layerage assembles a collage of its nearest neighbors: drawings a neural network considers similar. The canvas automatically adapts to your screen, so the result is a ready-made desktop or phone background. A menu tweaks dimensions, layer size and count; a random button picks a set for you, and on mobile, you can just shake your phone.

The similarity behind it: every public layer is run through a neural net (Inception/MobileNet) to extract an imprint of its visual character, then t-SNE and UMAP reduce those imprints to a 2D similarity space. Pick a point in that space, select the closest layers, distribute them to fit the canvas: collage. The first experiments lived in an Observable notebook before becoming a Vue.js app.
Some honest notes from the process: running t-SNE on ~50,000 × 1,000-dimensional vectors makes your system sweat. I hit memory limits until I switched to the WebGL implementation (TFJS-TSNE), and YaleDHLab’s UMAP implementation helped too. And while the quick Observable experiments were pure fun, carrying a finished app over the line took considerably more self-motivation.
The code is on GitHub under a CC BY-NC 4.0 license. Contributions and feature ideas welcome.
Thanks to u/youngluck for the support.




Images
Left and right arrow keys flip through the pile, Enter enlarges the top image.