
Alayarenderer Generative World
This is a two-stage video rendering pipeline that first extracts G-buffers (albedo, normal, depth, roughness, metallic) from RGB video using a fine-tuned 7B Cosmos model, then resynthesizes stylized video from those G-buffers plus text prompts using a 1.3B Wan2.1 diffusion model. Think game footage relighting: you can take existing gameplay and transform it to look like it's set in a frozen tundra or cyberpunk rainy night just by changing the prompt. Requires two separate conda environments because of dependency conflicts, which is a bit annoying but manageable. Trained on 4M+ frames from Cyberpunk 2077 and Black Myth: Wukong, so it understands game rendering conventions well.
- skills.sh installs
- 522
- GitHub stars
- 61
- last updated
- Jul 14, 2026
Install
$ npx -y skills add aradotso/trending-skills --skill alayarenderer-generative-world --agent claude-codeInstalls into .claude/skills of the current project.
Files
AlayaRenderer — Generative World Renderer
Skill by ara.so — Daily 2026 Skills collection.
AlayaRenderer is a two-stage framework for high-quality video rendering:
- Inverse Renderer (RGB → G-buffers): Extracts albedo, normal, depth, roughness, and metallic maps from RGB video using a fine-tuned Cosmos-Transfer1-DiffusionRenderer 7B model.
- Game Editing (G-buffers + Text → Stylized RGB): Synthesizes photorealistic, stylized RGB video from G-buffer inputs using a fine-tuned Wan2.1 1.3B model via DiffSynth-Studio.
Installation
Clone the Repository
git clone --recurse-submodules https://github.com/ShandaAI/AlayaRenderer.git
cd AlayaRenderer
Important: Use
--recurse-submodules— DiffSynth-Studio is a git submodule required for Game Editing.
Two Separate Conda Environments (Recommended)
The two models have conflicting dependencies. Use separate environments:
# Environment 1: Inverse Renderer
conda create -n inverse_renderer python=3.10 -y
conda activate inverse_renderer
cd inverse_renderer
# Follow inverse_renderer/ instructions for Cosmos-Transfer1 setup
Sponsors
Details
- Repository
- github.com/aradotso/trending-skills
- First seen
- Jun 3, 2026
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