Definition
ControlNet lets architects feed a floor plan or sketch into an AI render pipeline as a structural guide so the output preserves geometry instead of hallucinating it.
Why it matters
Without ControlNet, AI renders look pretty but ignore your design. With it, the render respects your massing, openings, and proportions — which is the difference between a moodboard and a deliverable.
Key points
- •Common conditions: Canny edges, depth maps, MLSD line segments, scribbles, normal maps.
- •Multiple ControlNets can be stacked (e.g. depth + edges).
- •Strength is tunable — high values lock geometry, low values allow creative interpretation.
Examples
- ›Feeding a CAD elevation as Canny edges to render a façade.
- ›Using a SketchUp depth pass to render a massing study.
Use cases for architects
1Locking a CAD elevation while exploring façade material variations.
2Driving a night render from a daytime SketchUp screenshot using depth control.
3Maintaining furniture layout while regenerating finishes for client options.
In AI Cadbull Studio
The 3D Visualizer auto-extracts edges and depth from your uploaded floor plan or 3D model and applies multi-stage ControlNet.
Try it nowFrequently asked questions
Which ControlNet should I use for floor plans?
MLSD or Canny — both lock the orthogonal line work that defines architectural drawings.
Can I stack multiple ControlNets?
Yes. A common architectural stack is MLSD (line work) + Depth (massing) + Segmentation (material zones). Lower each strength so they cooperate instead of competing.