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Dark teal and copper marbled texture assembled from locally matched image patches

The renderer samples candidate patches from a source swatch and scores their overlap with the filled canvas. Dynamic programming chooses low-error seams through the top and left overlaps; the output retains a map of source coordinates and every seam. A suitable owned swatch renders locally. PopNow can generate a missing texture input after a quote and approval; patch count, candidate count and overlap determine local computation.

Uses PopNow for
Images
Needs
Python 3

Generation is optional when you have suitable input material.

v1.0.0 · Updated Oct 25, 2026 · 13.1 MB · Use it for personal and client work; please don't resell or share the package.

What you get

  1. Quilted texture PNG with raster-wrapped SVG

  2. Seam-location proof image

  3. Patch ledger, copied texture and portable brief

Good for

  • Expanding decorative texture swatches
  • Comparing patch size and seam quality before design use

Not for

  • Guaranteed seamless opposite edges
  • Inventing semantic content absent from the source

How it works

Includes a local renderer

  1. Choose the input

    Choose a source swatch with enough variation for patch reuse.

  2. Render and inspect

    Select and join patches, then inspect the seam-location proof.

  3. Adjust and export

    Adjust patch size or overlap before saving the artwork and patch map.

How the workflow runs

How Image quilting studio works

The renderer samples candidate patches from a source swatch and scores their overlap with the filled canvas. Dynamic programming chooses low-error seams through the top and left overlaps; the output retains a map of source coordinates and every seam.

What's inside the skill

What you can change

  • patch_size: 48–240 pixels
  • overlap: 0.12–0.40 of each patch
  • candidate_count: 16–160 and error_tolerance: 0–0.5
  • source texture, seed and output dimensions

What to review before delivery

  • Every output pixel is filled by a selected source patch.
  • Successive steps on each recorded seam differ by at most one pixel.
  • The saved brief reproduces the PNG and SVG; unsafe replacement is rejected.

See the package files

These are selected working files from this edition, with their actual role. The complete download also contains instructions and applicable license notices.

  • The domain algorithm and invariant checks.

    scripts/recipe.py

  • Runnable, editable example parameters.

    examples/brief.json

  • Control meanings, proof interpretation and limits.

    references/design-notes.md

Why use this skill

Start with this package

The package includes candidate selection, dynamic-programming joins and a source-coordinate ledger. It supplies inspectable texture synthesis instead of stretching or regularly repeating the original swatch.

What PopNow adds

Use PopNow for the missing Images in this workflow. Keep adequate material you already own, then bring new assets back into the editing and assembly steps described here.

Compare the options

A prompt, your own skill, or this workflow?

Start with a prompt

Your agent can create from a plain request. The brief, visual rules, asset choices, output format and review process still need to be established for that project.

Write your own skill

You choose and maintain the reusable instructions, defaults, file structure and checks. This is useful when your process needs different rules or integrations.

A workflow created for PopNow

This workflow was built for PopNow. Its source files, included dependencies and applicable notices are part of the package; the scope described below belongs to this edition.

Guide reviewed Oct 25, 2026

What will this cost?

A suitable owned swatch renders locally. PopNow can generate a missing texture input after a quote and approval; patch count, candidate count and overlap determine local computation.

Generation is optional when you have suitable input material. Free skill. New media is quoted before it runs.

The skill package

Free to install under your account's download allowance. The package license covers your own and client work; redistribution is excluded.

Existing assets and local work

Reusing suitable assets, editing files and running local assembly do not call a PopNow generation model. Your computer and any required runtime still do the work.

New AI images, clips or sound

Quoted for the actual model, inputs, count, duration and resolution. Extra alternatives, revisions or optional enhancement passes can add generation requests.

Your agent and hosting

Any subscription, hosted computer, deployment or other provider fee belongs to that service. Installing this skill does not include those services.

Check the cost of your version first

Your assistant can inspect the available models and quote the exact request first. You choose which optional passes to include and approve spending before generation.

Ask your assistant

  • Use the PopNow skill "Image quilting studio" for my project. List the inputs you can reuse, quote only the missing media, show the quoted total and flag any unpriced steps. Separate optional enhancements, and wait for my approval before starting anything paid.

How PopNow billing works

Connections using a PopNow API key, including API-key MCP connections, spend from the separate API balance in USD. A ChatGPT or Claude connection authorized through OAuth spends website credits. These balances are separate; the quote shown by your connection is the approval basis.

Download allowances and current account conditions apply. A free package does not mean unlimited free generation.

See model ratesAPI USD balanceWebsite credit packs

How to use it

You say

  • Use the PopNow skill "Image quilting studio" (image-quilting-studio) for this: Choose a source swatch with enough variation for patch reuse. Use the packaged example as a starting point and return the actual artwork with its editable inputs.

Then try

  • Rebuild a visibly different version using patch_size: 156 → 90; seed: 31 → 66.

  • Explain the result using its actual proof files and algorithm ledger.

What to have ready

  • A richly textured swatch you may use
  • Desired output size and patch scale
  • Python 3.10+, Pillow and NumPy

Similar skills

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Questions

Is this simple repeated tiling?

No. Each patch is selected against its current neighbors, and a minimum-cost path determines where the overlap changes from old pixels to new pixels. The seam proof shows those actual joins.

Is the result a seamless wallpaper tile?

Not automatically. The algorithm matches neighboring patches inside the output, but it does not constrain opposite outer edges. Inspect and separately prepare edge continuity if a repeating tile is needed.

What costs depend on this workflow?

A suitable owned swatch renders locally. PopNow can generate a missing texture input after a quote and approval; patch count, candidate count and overlap determine local computation.

What is already packaged in Image quilting studio?

The domain algorithm and invariant checks. Runnable, editable example parameters. Control meanings, proof interpretation and limits.

Which parts of Image quilting studio can add a charge?

A suitable owned swatch renders locally. PopNow can generate a missing texture input after a quote and approval; patch count, candidate count and overlap determine local computation. Connections using a PopNow API key, including API-key MCP connections, spend from the separate API balance in USD. A ChatGPT or Claude connection authorized through OAuth spends website credits. These balances are separate; the quote shown by your connection is the approval basis.

How does Image quilting studio differ from writing a prompt or my own skill?

The package includes candidate selection, dynamic-programming joins and a source-coordinate ledger. It supplies inspectable texture synthesis instead of stretching or regularly repeating the original swatch.