Geometry Rendering logo

Geometry Rendering

Organization
VectorSpaceLab
geometry-rendering

Reconstruct 3DMM vertices, serialize mesh outputs, and manage 3DDFA rendering helpers.

Overview

PublisherVectorSpaceLab
RepositoryAREX-Skill
Skill namegeometry-rendering
Stars
341
Forks
26
Bundled files
7
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 7 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by VectorSpaceLab on GitHub. Read the source before you install it.

Installation

Install the Geometry Rendering AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/3ddfa/sub-skills/geometry-rendering
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git /tmp/AREX-Skill
mkdir -p .claude/skills
cp -r /tmp/AREX-Skill/skills/repositories/repo-skills/3ddfa/sub-skills/geometry-rendering .claude/skills/geometry-rendering
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Geometry Rendering in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Geometry Rendering on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Geometry Rendering is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

geometry-rendering

Use this sub-skill for the geometry side of 3DDFA: parameter reconstruction, ROI-to-image conversion, sparse and dense vertices, mesh serialization, pose matrices, depth/PNCC/PAF outputs, and the Cython-backed render path.

Use when

  • you have a 62-D parameter vector or cropped ROI and need 68 landmarks or dense vertices;
  • you need PLY, OBJ, .mat, depth, PNCC, PAF, or pose artifacts;
  • you need to build or troubleshoot utils.cython;
  • you need dense render or video assembly helpers.

Start here

Bundled helpers

Route elsewhere

  • Full detector/model inference and CLI flags belong in the sibling inference sub-skill.
  • Training losses, benchmark scripts, and dataset preparation belong in the training sub-skill.
  • ONNX export and the C++ port belong in the C++ sub-skill.

Working facts

  • utils.ddfa.reconstruct_vertex is the canonical 3DMM reconstruction entry point.
  • The verified smoke for a zero 62-D vector returns sparse (3, 68) and dense (3, 53215) vertices.
  • visualize/tri.mat provides the triangle indices used by the renderer paths.
  • utils.render and utils.lighting depend on the compiled mesh_core_cython extension.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Geometry Rendering AI skill do?

Reconstruct 3DMM vertices, serialize mesh outputs, and manage 3DDFA rendering helpers.

Why use Geometry Rendering on TypingMind?

Because you install it once and use it with any model. Geometry Rendering is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Geometry Rendering in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/3ddfa/sub-skills/geometry-rendering. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Geometry Rendering?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Geometry Rendering?

As many as you like. As long as a model supports skills, you can use Geometry Rendering with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Geometry Rendering AI skill free?

Yes. It is published on GitHub by VectorSpaceLab under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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