This ComfyUI workflow demonstrates how to guide MOSS Image generation with a Color-Depth Control LoRA trained by darask0. It lets you steer structure with a depth map while preserving or modulating color from a reference image, making it easy to create style variations that keep geometry intact. At its core, LoadImage brings in your RGB reference and (optionally) a precomputed depth map, while PreviewImage and ImageCompare help you iterate quickly and check differences across runs. SaveImageAdvanced handles clean, configurable exports.
The heavy lifting happens in two custom MOSS Image nodes (IDs: 3d58c0bd-7a87-40a7-bdb5-a209a27f10d7 and 882218ff-0ea7-4047-9b12-b79cdc4e9faa). Together, they wrap the MOSS Image base model and apply the Color-Depth Control LoRA at inference, injecting depth-aware conditioning so the output adheres to your scene layout and perspective. By pairing color information from the source image with structural cues from the depth map, the workflow produces edits and variations that maintain shape, scale, and composition—ideal for product shots, architecture, and concept iterations where consistency matters.
API
從程式碼使用此工作流
每個 Comfy 工作流都是一個 JSON 圖。下方的 payload 就是此工作流，與 ComfyUI 執行時完全相同 — 你可以從此 URL 取得、放入版本控制，或在 ComfyUI 載入並逐節點執行。
使用 Comfy SDK 以 TypeScript 或 Python 執行。相同程式碼可用於 Comfy Cloud 或你自架的 ComfyUI — 只需更改 base URL。
// Install (beta)
npm i @comfyorg/sdk
// Run this workflow (TypeScript)
import { Comfy } from "@comfyorg/sdk";
const client = new Comfy({ apiKey: "comfyui-..." });
const wf = await client.workflows.fromFile("workflow_api.json");
const job = await client.run(wf);
await job.getOutputs("<output-node-id>")[0].toFile("output.png");SDK 需使用 API 格式的工作流：請在 ComfyUI 開啟此工作流，並使用 檔案 → 匯出工作流（API）。
