A LoRA for FLUX.2 Klein 9B Base that fuses a reference image (identity) with a canny edge map (structure / contours).
It preserves identity and style from the reference while following the shape and composition from the canny control map.
Trigger word: refcontrol
Each preview is a single combined image from ComfyUI: Canny → Reference → Result (left to right).
| Canny → Reference → Result |
|---|
This LoRA was primarily trained on humans, but it also works with stylized characters and some objects.
Its main purpose is to preserve identity — facial features, hairstyle, clothing, or object details — from the reference image, while adapting the subject to the structure and contours defined by the canny edge map.
FLUX.2 Klein 9B Base already handles reference + edge-guided transfer reasonably well with the right prompt alone. This LoRA builds on that capability — it improves consistency and better preserves character identity and edge fidelity than the base model without LoRA.
Part of the RefControl family: reference + control fusion for consistent, controllable generation on FLUX.2 Klein 9B Base.
refcontrol in your prompt.Canny extraction in the included workflow uses CannyEdgePreprocessor (via comfyui_controlnet_aux):
https://github.com/Fannovel16/comfyui_controlnet_aux
You can disable the built-in canny preprocessor if your input is already a canny/edge image.
Trained on and recommended with black-forest-labs/FLUX.2-klein-base-9B.
The undistilled Base variant is intended for LoRA training and custom pipelines (~50 inference steps, guidance_scale ~4.0).
The LoRA also works with the 4-step distilled black-forest-labs/FLUX.2-klein-9B for faster inference (~4 steps, guidance_scale ~1.0), but quality may be slightly lower — especially for identity and edge fidelity — compared to the Base model.
refcontrol
flux2_klein_9b_refcontrol_canny.safetensorsrefcontrol_canny_flux_klein_9b.json