Draw a branching botanical structure over time and let extracted engraved leaves grow at its tips. A seeded parent-child graph grows curved strokes in depth order. Color-distance extraction reuses the supplied botanical engraving pixels at terminal nodes, rather than merely citing an unused reference image. PopNow can supply missing artwork, footage or sound after a quote; owned material and the local example work without a connection.
- Uses PopNow for
- Images · Music & voice
- Needs
- Python 3 · FFmpeg
The skill is free. Optional AI images, video and sound are quoted for your approval before generation. API-key calls use your separate API balance in USD; generation through ChatGPT or Claude connected via OAuth/MCP uses your website credits.
v1.0.0 · Updated Oct 25, 2026 · 3.0 MB · Use it for personal and client work; please don't resell or share the package.
What you get
An 8-second 1280 × 720 H.264 MP4 made by the local algorithm
A seeded parent-child graph grows curved strokes in depth order. Color-distance extraction reuses the supplied botanical engraving pixels at terminal nodes, rather than merely citing an unused reference image.
Editable JSON, a six-frame contact sheet and a receipt with actual checks
Good for
- Botanical title sequences, elegant growth studies and illustrated nature growth films
- Original creative work using owned or licensed material
Not for
- Species identification, biological growth prediction or automatic leaf recognition
- Publishing without watching the rendered result
How to use it
You say
Use the PopNow skill "Branching Engraving Growth" (branching-engraving-growth) for this: Draw a branching botanical structure over time and let extracted engraved leaves grow at its tips. Use the bundled project, render the example and inspect the full result before delivery.
Then try
Change angleDegrees from 32 to 24 and seed to 31 for a narrower tree.
Use my licensed music; keep source audio discarded.
What to have ready
- A botanical fragment on a uniform dark background, plus branch depth and angle.
- Python 3.10+, FFmpeg/ffprobe, Pillow and NumPy
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Questions
Are the leaves actually taken from my image?
Yes. Color-distance extraction creates a local alpha matte and the renderer rotates those pixels onto branch tips. Complex backgrounds need cleanup first.
How does branch growth remain connected?
Every child begins at its parent endpoint. The audit verifies graph connectivity and safe tip positions; depth-ordered growth reveals each path progressively.
Does the local render spend generation funds?
No. It reads local media and renders locally. Missing media can be made through PopNow after an exact quote and approval; no paid call occurs in the renderer.