<h2 id="sdxl-controlnet-simple-workflow">✨ SDXL — ControlNet — Simple Workflow</h2>A clean, all-in-one SDXL ControlNet workflow built entirely with the UmeAiRT Toolkit for ComfyUI. This workflow allows you to generate images from text inspired by an existing image using a ControlNet processor. Only 8 nodes. No spaghetti wires. Just load your model, write your prompt, and hit generate. <span style="background-color:rgb(26, 27, 30);color:rgb(193, 194, 197);font-family:-apple-system, BlinkMacSystemFont, &quot;Segoe UI&quot;, Roboto, Helvetica, Arial, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;;font-size:16px">You can find a step-by-step guide to this workflow in this article: <a target="_blank" rel="ugc" href="https://civarchive.com/articles/29195">link</a><hr /><h3 id="important-nodes-2.0-required">⚠️ IMPORTANT — Nodes 2.0 Required</h3>This workflow is built for the Nodes 2.0 (Vue) interface of ComfyUI. If you don't enable it, the workflow may have display problems.How to activate Nodes 2.0:<ol><li>Open ComfyUI</li><li>Go to Settings (⚙️ icon, bottom-left)</li><li>Find "Use Nodes V2 (Vue)" and toggle it ON</li><li>Refresh the page</li><li>Load the workflow</li></ol>If you prefer the classic interface, check out my Legacy version of this workflow instead (<a target="_blank" rel="ugc" href="https://civarchive.com/models/872149?modelVersionId=2418962">link</a>).<hr /><h2 id="features">🎯 Features</h2><ul><li>Text-to-Image generation with any SDXL/ILLUSTRIOUS checkpoint</li><li>Built-in upscaler — high-quality tiled upscaling (toggleable on/off) Slower than a classic upscaler, but significantly better quality</li><li>Subject Detailer — automatic face or body enhancement (toggleable on/off)</li><li>Full metadata embedding — your images are saved with all generation parameters, ready for online publishing and remixing</li><li>3 LoRA slots — with individual on/off toggles and strength control and you can connect as many other lora modules to each other for as many LoRA as you want.</li></ul><hr /><h2 id="custom-node-required">📦 Custom Node Required</h2>Only one custom node to install:👉 <a target="_blank" rel="ugc" href="https://gitlab.com/UmeAiRT-Studio/ComfyUI-UmeAiRT-Toolkit">ComfyUI-UmeAiRT-Toolkit</a>Install via ComfyUI Manager (search "UmeAiRT") or use the UmeAiRT Auto-Installer. The Toolkit packages everything internally — upscaler, face detailer, metadata saver. No other custom nodes needed.<hr /><h2 id="files-you-need">📂 Files you need</h2>An SDXL model : <a target="_blank" rel="ugc" href="https://civarchive.com/models/827184?modelVersionId=1490781">like this one</a> in <code>ComfyUI/models/checkpoints/</code> An upscale model (optional) : <a target="_blank" rel="ugc" href="https://huggingface.co/zelt54/RoNa/blob/main/R-ESRGAN%204x%2B%20Anime6B.pth">like this one</a> in <code>ComfyUI/models/upscale_models/</code> As many LoRAs as you like (optional) : <a target="_blank" rel="ugc" href="https://civarchive.com/models/674657/flux-lora-umesky">like this</a> one in <code>ComfyUI/models/loras/</code>For the Subject Detailer (optional, download automatically by my toolkit) :A BBOX detector model : <a target="_blank" rel="ugc" href="https://huggingface.co/UmeAiRT/ComfyUI-Auto_installer/tree/main/models/ultralytics/bbox">like this one</a> in <code>ComfyUI/models/ultralytics/bbox/</code> A SAM model : <a target="_blank" rel="ugc" href="https://huggingface.co/UmeAiRT/ComfyUI-Auto_installer/resolve/main/models/sams/sam_vit_b_01ec64.pth?download=true">like this one</a> in <code>ComfyUI/models/sams/</code> A SEGM detector model : <a target="_blank" rel="ugc" href="https://huggingface.co/Bingsu/adetailer/resolve/main/person_yolov8m-seg.pt?download=true">like this one</a> in <code>ComfyUI/models/ultralytics/segm/</code><img src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/d2e44e84-96db-420d-b237-21e7972034db/original=true/d2e44e84-96db-420d-b237-21e7972034db.jpeg" />

【SDXL】ControlNet

<ul><li>tested on ComfyUI 0.3.68,</li><li>less custom node needed,</li><li>UI optimisation,</li><li>new subgraph fonction for backend.</li></ul>

Files with SHA256: 589654559b8f58469f9ab4a189fd980822d6d1897fc5e26ab4753b575f84702f