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controlnet · guiding generation

NeuraVSThe Overfit Ogre
Neura saysControlNet and similar tools steer image generation with extra conditioning — pose, edges, depth.

Plain text prompts can't precisely control composition. ControlNet adds a conditioning input — an edge map, human pose skeleton, depth map, or scribble — that constrains the diffusion to match that structure while the prompt sets style/content. It's how you get a generated image in exactly the pose or layout you want. Part of a broader toolkit (img2img, inpainting, LoRAs) for directed, controllable generation.

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The Overfit Ogre attacks — common mistakes

Boss battleExplain how a pose skeleton conditions a generated figure.

Example code

<!doctype html><html><head><meta charset="utf-8"></head>
<body style="background:#06040d;color:#e6e0ff;font-family:monospace;padding:20px"><pre>prompt: "a knight" + ControlNet pose skeleton
→ knight generated in EXACTLY that pose
edges/depth/scribble = other controls</pre></body></html>
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