Unlock Advanced Image Synthesis with FLUX ControlNet V3.0 Workflow
Unlock advanced image synthesis with FLUX ControlNet V3.0! Combine HED, Depth, and Canny edge preprocessing for precise control. Discover key features, core models, and installation details. Get started now!
- Models
- FluxControlnetSd
- Key Nodes
- Controlnet
- VRAM
- Medium VRAM (12–16GB)
- Reading Time
- 5 min
Workflow Overview
Unlock advanced image synthesis with FLUX ControlNet V3.0! Combine HED, Depth, and Canny edge preprocessing for precise control. Discover key features, core models, and installation details. Get started now!
Content type: Workflow
Primary intent: Download
Required Models
- Flux
- Controlnet
- Sd
Required Nodes
- Controlnet
Setup Notes
- Install the required models before opening the workflow template.
- Recommended hardware: Medium VRAM (12–16GB).
1. Workflow Overview
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This workflow leverages FLUX ControlNet V3.0 for multi-condition controlled generation, combining HED soft-edge, Depth, and Canny edge preprocessing to precisely guide image synthesis. Outputs adhere to input structure and text prompts.
Key Features:
Multi-ControlNet Integration (HED + Depth + Canny).
Depth Anything V2 for depth map generation.
WD14 Tagger for auto-prompt generation.
Flux Sampler with FP8 optimization for efficiency.
Output:
High-res images (default 1024x1024), stylized by prompts and ControlNet conditions.
2. Core Models
Model Name | Function |
|---|---|
Stable Diffusion XL | Base image model (Flux.1-Dev fp16 variant). |
Depth Anything V2 | Generates depth maps from input images. |
ControlNet V3 | Provides HED, Depth, and Canny controls. |
WD14 Tagger | Auto-generates tags from input images. |
3. Key Nodes & Installation
Node Name | Function | Installation | Dependencies |
|---|---|---|---|
DownloadAndLoadDepthAnythingV2Model | Loads Depth Anything V2 model. | Manual download to | |
ApplyFluxControlNet | Applies Flux-optimized ControlNet. | Install | Requires ControlNet V3 models (e.g., |
XlabsSampler | Flux sampler with FP8 support. | Part of | FP8-compatible GPU (e.g., RTX 40 series). |
WD14Tagger|pysssss | Auto-tagging for prompts. | Install | Requires |
4. Workflow Groups
HED Group (Blue)
Input: Source image (resized via
ImageResize+).Preprocess:
HEDPreprocessorextracts soft edges.Control Weight: 0.8 (set in
ApplyFluxControlNet).
Depth Group (Orange)
Input: Same image.
Preprocess:
DepthAnything_V2generates depth map.Control Weight: 0.7.
Canny Group (Purple)
Input: Same image.
Preprocess:
CannyEdgePreprocessor(thresholds 100/200).Control Weight: 0.6.
Generation Group
Prompts: Processed by
CLIPTextEncode(e.g., "Makoto Shinkai style").Sampling:
XlabsSamplermerges multi-ControlNet conditions.
5. Inputs & Outputs
Input Parameters:
Image: Loaded via
LoadImage(e.g., sample Redbook image).Prompts: Manual input or auto-generated by
WD14Tagger.Resolution: Default 1024x1024 (set in
EmptyLatentImage).
Output:
Final images saved in
/ComfyUI/output/with metadata.
6. Notes
Hardware:
RTX 40 series recommended (FP8 support), VRAM ≥12GB.
Depth Anything V2 is VRAM-intensive; may crash at high resolutions.
Model Setup:
Download ControlNet V3 models to
/models/controlnet/.Missing models trigger download prompts.
Tips:
Total ControlNet weights should ideally ≤2.0 (e.g., HED 0.8 + Depth 0.7 + Canny 0.6).
FP8 mode may introduce noise; adjust
denoiseinModelSamplingFlux.