ComfyUI Flux2 Fun ControlNet

ComfyUI implementation of FLUX.2-dev-Fun-Controlnet-Union from Alibaba's VideoX-Fun.

A unified ControlNet that supports multiple control modes with a single checkpoint — no mode switching required!

Supported Control Types

| Control Type | Description | |--------------|------------------------------| | Pose | OpenPose skeleton | | Canny | Edge detection | | Depth | Depth maps | | HED | Soft edge detection | | MLSD | Line segment detection | | Tile | Upscaling/detail enhancement |

The model automatically detects the control type from your input image.

Installation

Method 1: Git Clone (Recommended)

cd ComfyUI/custom_nodes
git clone https://github.com/bryanmcguire/comfyui-flux2fun-controlnet.git

Method 2: Download ZIP

1. Download this repository as ZIP
2. Extract to ComfyUI/custom_nodes/comfyui-flux2fun-controlnet

Download Model

Download the ControlNet checkpoint and place in ComfyUI/models/controlnet/:

• FLUX.2-dev-Fun-Controlnet-Union.safetensors (~8.3GB)

Requirements

• ComfyUI with Flux support
• Flux.2-dev base model
• flux2-vae.safetensors (or ae.safetensors)
• Python 3.10+
• PyTorch 2.0+

Nodes

Load Flux2 Fun ControlNet

Loads the ControlNet checkpoint.

| Input | Type | Description | |-----------------|----------|------------------------| | controlnet_name | dropdown | Select checkpoint file |

| Output | Type | Description | |------------|----------------------|--------------| | controlnet | FLUX2_FUN_CONTROLNET | Loaded model |

Apply Flux2 Fun ControlNet

Applies ControlNet to conditioning.

| Input | Type | Description | |---------------|----------------------|------------------------------| | conditioning | CONDITIONING | Text conditioning from CLIP | | controlnet | FLUX2_FUN_CONTROLNET | Loaded ControlNet | | vae | VAE | Flux VAE | | strength | FLOAT | Control strength (0.0 - 2.0) | | control_image | IMAGE (optional) | Control signal | | mask | MASK (optional) | Inpaint mask | | inpaint_image | IMAGE (optional) | Image to inpaint |

| Output | Type | Description | |--------------|--------------|-----------------------| | conditioning | CONDITIONING | Modified conditioning |

Usage

Control Mode (Primary Use Case)

For pose/canny/depth/HED/MLSD/tile control:

1. Load your control image (pose skeleton, canny edges, depth map, etc.)
2. Connect to control_image input
3. Set strength to 0.65–0.80
4. Leave mask and inpaint_image disconnected

Control + Inpaint Mode (Experimental)

For regional regeneration with structural guidance:

1. Connect control_image (structural guide for the region)
2. Connect mask (white = area to regenerate)
3. Connect inpaint_image (original image)
4. Set strength to 0.25–0.40

Note: This is mask-guided regional regeneration, not traditional context-aware inpainting. For best inpainting results, use a dedicated inpaint model like Flux Fill.

Recommended Settings

| Mode | Strength | Steps | CFG | Notes | |----------------------------|-------------|-------|---------|------------------| | Control (pose/canny/depth) | 0.65 - 0.80 | 25-50 | 3.5-4.5 | Primary use case | | Control + Inpaint | 0.25 - 0.40 | 25-50 | 3.5-4.5 | Experimental |

Example Workflows

See the examples folder for ready-to-use workflows.

Technical Details

This implementation:

• Uses a monkey patch to inject control hints — no ComfyUI core modifications needed
• Hints are injected at Flux double stream blocks 0, 2, 4, 6
• Control context is 260 channels: 128 (control) + 4 (mask) + 128 (inpaint)
• Native VideoX-Fun architecture with proper RoPE handling

Troubleshooting

"Module not found" error

Restart ComfyUI after installation.

Black output / no effect

• Check that strength is > 0
• Verify VAE is connected
• Ensure the control image is loaded correctly

Out of memory

• Reduce image resolution
• Use CPU offloading if available
• Close other GPU applications

Credits

• Original Model: alibaba-pai/FLUX.2-dev-Fun-Controlnet-Union
• Reference Implementation: VideoX-Fun

License

Apache 2.0 — same as VideoX-Fun

Contributing

Contributions welcome! See CONTRIBUTING.md for guidelines.