Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Image To Relief Stl
Turn a source image (or multi-color mask image) into a 3D-printable bas-relief STL by mapping colors (or grayscale) to heights. Use when you have an image from an image-gen skill (nano-banana-pro, etc.) and want a real, printable model (STL) via a deterministic pipeline.
skill openclawclawhub Free
Turn a source image (or multi-color mask image) into a 3D-printable bas-relief STL by mapping colors (or grayscale) to heights. Use when you have an image from an image-gen skill (nano-banana-pro, etc.) and want a real, printable model (STL) via a deterministic pipeline.
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, scripts/image_to_relief.py, scripts/image_to_relief.sh
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 0.1.0
Provenance
- Publisher
- ajmwagar
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
image-to-relief-stl
Generate a watertight, printable STL from an input image by mapping colors (or grayscale) to heights. This is an orchestrator-friendly workflow: Use nano-banana-pro (or any image model) to generate a flat-color image. Run this skill to convert it into a bas-relief model.
Practical constraints (to make it work well)
Ask the image model for: exactly N solid colors (no gradients) no shadows / no antialiasing bold shapes with clear edges That makes segmentation reliable.
Quick start (given an image)
bash scripts/image_to_relief.sh input.png --out out.stl \ --mode palette \ --palette '#000000=3.0,#ffffff=0.0' \ --base 1.5 \ --pixel 0.4
Grayscale mode
bash scripts/image_to_relief.sh input.png --out out.stl \ --mode grayscale \ --min-height 0.0 \ --max-height 3.0 \ --base 1.5 \ --pixel 0.4
Outputs
out.stl (ASCII STL) optional out-preview.svg (vector preview via potrace; best-effort)
Notes
This v0 uses a raster heightfield meshing approach (robust, no heavy CAD deps). The --pixel parameter controls resolution (smaller = higher detail, bigger STL).
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Scripts1 Docs
- SKILL.md
- scripts/image_to_relief.py
- scripts/image_to_relief.sh