WearSediment vs Toukasane Lab

WearSediment focuses on recording irreversible wear and aging marks on physical objects, turning time’s textures into a comparable, traceable archive of material age. - Capture wear and aging details on wood, leather, metal, stone, fabric, and more - Archive by material, aging type, duration depth, and wear tags - Add short notes to preserve what you saw in the moment - Compare how the same object evolves over time - Browse and search archived age traces in one place

Toukasane Lab is an on-device craft assistant for translucent layered washi dyeing. It turns soak, stacking, and wet-press steps into adjustable parameters so you can compare formulas before you work, and review finished pieces afterward. What you can do: • Browse a built-in washi paper library (such as gampi, mitsumata, sugihara, Mino, and handmade thin translucent sheets), inspect absorbency, transmittance, and layer limits, and load defaults into the studio • Adjust moisture level, soak time, layer count, press strength, press duration, and dye strength; see live scores for clarity, evenness, texture, and integrity, plus risk tips • Compare two formulas side by side and get a style-based pick among Fresh / Antique / Deep • Preview multi-layer translucent dye results (Metal compute shading when available, otherwise on-device drawing); zoom, copy a parameter list, and save the simulation image • Choose a finished photo from your library for on-device preprocessing and feature-based analysis of eight dye-related defect types (dry spots, uneven layers, wet-press wrinkles, edge bleed, muddy color, fiber fuzz, layer shift, over-bleed), with cause and fix suggestions • Read a twelve-step process guide, use style samples and parameter templates • Save experiments to a log, archive formulas, search, pin, reuse, and check for duplicate parameter sets What makes it distinctive: • Built around translucent stacking and wet-press craft—not a general color mixer or paint app • Parameters, simulation, diagnosis, and logs stay in one workflow for iteration • No account or social features; craft data stays on your device. Defect review runs locally and does not call an online recognition API • Ambient humidity/temperature tips are in-app references, not sensor readings; photo quality affects diagnosis Made for makers who want measurable notes and fewer blind trials.