Relight subjects using image-based lighting inputs with LBM.

Who it's for: creators who want this pipeline in ComfyUI without assembling nodes from scratch. Not for: one-click results with zero tuning — you still choose inputs, prompts, and settings.

Open preloaded workflow on RunComfy

Open preloaded workflow on RunComfy (browser)

Why RunComfy first
- Fewer missing-node surprises — run the graph in a managed environment before you mirror it locally.
- Quick GPU tryout — useful if your local VRAM or install time is the bottleneck.
- Matches the published JSON — the zip follows the same runnable workflow you can open on RunComfy.

When downloading for local ComfyUI makes sense — you want full control over models on disk, batch scripting, or offline runs.

How to use (local ComfyUI)
1. Load inputs (images/video/audio) in the marked loader nodes.
2. Set prompts, resolution, and seeds; start with a short test run.
3. Export from the Save / Write nodes shown in the graph.

Expectations — First run may pull large weights; cloud runs may require a free RunComfy account.

Overview

LBM Relighting is a flexible image relighting model integrated into ComfyUI via the LBMWrapper. It accepts two primary image inputs—a subject and a lighting reference—and fuses them to generate realistic relit images. In addition to relighting, the model supports extended tasks like object removal, depth and normal map generation, and other advanced image translation operations, all powered by Kijai's custom node system.

Important nodes:

• Subject Image

• Background Image

• Outputs

• model.safetensors

• ComfyUI/models/diffusion_models

Notes

LBM Relighting | I2I — see RunComfy page for the latest node requirements.