RH-RunningHub

RH-RunningHub / ComfyUI_RH_Pixal3D

Public

ComfyUI nodes for TencentARC Pixal3D image-to-3D generation

19
0
89% credibility
Found May 22, 2026 at 18 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

ComfyUI_RH_Pixal3D is a free plugin that brings Pixal3D's image-to-3D technology into ComfyUI. It lets anyone transform a single photograph into a complete, textured 3D model (GLB format) without needing any 3D modeling skills. The tool handles everything automatically - analyzing the image, generating the 3D shape, and applying realistic textures. Users can adjust quality settings based on their graphics card capabilities, and the resulting 3D models work immediately in games, virtual reality, websites, or 3D printing workflows.

How It Works

1
🖼️ You pick a photo

You choose any image you want to turn into a 3D model - a product photo, portrait, or object shot.

2
⚙️ You load the 3D generator

With one click, you load the Pixal3D model into ComfyUI, choosing settings that match your computer's graphics card.

3
✨ Watch your image become 3D

The magic happens automatically - the AI analyzes your photo and builds a complete 3D shape with textures.

4
🔄 Adjust quality if needed

You can tweak how detailed the 3D model looks and how many steps the AI takes to refine it.

5
💾 Save your creation

Export your new 3D model as a GLB file that's ready to use in games, websites, or 3D printing.

🎉 Your 3D asset is ready

You now have a fully textured 3D model that you can use anywhere - complete with colors, materials, and proper formatting.

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AI-Generated Review

What is ComfyUI_RH_Pixal3D?

This is a Python plugin that brings TencentARC Pixal3D into the ComfyUI ecosystem. Pixal3D converts a single image into a textured 3D model (GLB format). The plugin exposes three nodes: one to load the model pipeline, one to run the image-to-3D generation, and one to export the result as a downloadable file. It handles the full pipeline from loading your image through sampling steps to final mesh export, outputting camera metadata for downstream preview tools.

Why is it gaining traction?

The hook is obvious: turn any image into a 3D asset without leaving your existing ComfyUI workflow. Game artists and 3D modelers who already live in ComfyUI get image-to-3D capabilities without switching tools. The low-VRAM mode makes it accessible on consumer GPUs (24GB recommended), and the workflow includes sensible defaults for quick testing. The generation process has multiple sampling step controls across three stages, letting users trade speed for quality.

Who should use this?

3D artists who need rapid prototyping of textured models from reference images. Game developers looking to generate placeholder assets quickly. ComfyUI power users who want to chain image-to-3D with other nodes for complex pipelines. Not for production 3D workflows requiring precise control, and definitely not for anyone without a beefy GPU and patience for the CUDA extension setup.

Verdict

This fills a real gap in the ComfyUI ecosystem, but the credibility score of 0.8999999761581421% and modest star count reflect an early-stage project with complex dependencies. The setup is brutal: multiple CUDA extensions, specific PyTorch/CUDA versions, and manual model downloads across five different sources. If you have the hardware and tolerance for dependency hell, the output quality justifies the effort. Start with the provided workflow and 12 sampling steps as a baseline.

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