---

name: flux-dev-controlnet description: "Flux Controlnet | Multi-Mode Controlled Image Generation. Generate images with canny, depth, or soft edge control using Flux Dev. Triggers: flux controlnet, controlnet, canny, depth, soft edge, controlled generation" allowed-tools: Bash(curl *), WebFetch

Flux Controlnet

Generate images with multi-mode ControlNet support using Flux Dev. Supports canny edge detection, depth maps, and soft edge control types with optional LoRA models.

Quick Start

Requires an each::labs API key. Get one at eachlabs.ai.

curl -X POST https://api.eachlabs.ai/v1/prediction \
  -H "Content-Type: application/json" \
  -H "X-API-Key: $EACHLABS_API_KEY" \
  -d '{
    "model": "flux-dev-controlnet",
    "version": "0.0.1",
    "input": {
      "prompt": "a stunning watercolor painting of a mountain village at sunset",
      "control_image": "https://example.com/village-photo.jpg",
      "control_type": "depth",
      "control_strength": 0.5,
      "guidance_scale": 3.5,
      "steps": 28
    }
  }'

Parameters

Parameter	Type	Default	Description
control_image	string	-	Image to use with ControlNet
control_strength	number	0.5	Strength of ControlNet. Different controls work better at different strengths
control_type	string	depth	Control mode. enum: canny, soft_edge, depth
depth_preprocessor	string	DepthAnything	Depth preprocessor. enum: Midas, Zoe, DepthAnything, Zoe-DepthAnything
guidance_scale	number	3.5	Guidance scale
image_to_image_strength	number	0	Strength of image-to-image control. 0 means no control, 1 means full
lora_strength	number	1	Strength of LoRA model
lora_url	string	-	Optional LoRA model URL (HuggingFace .safetensors or Replicate link)
negative_prompt	string	-	Things you do not want to see in the image
output_format	string	webp	Output format. enum: webp, jpg, png
output_quality	integer	80	Quality of output images, from 0 to 100
prompt	string	-	Text prompt for generation
return_preprocessed_image	boolean	false	Return the preprocessed control image
seed	integer	-	Set a seed for reproducibility
soft_edge_preprocessor	string	HED	Soft edge preprocessor. enum: HED, TEED, PiDiNet
steps	integer	28	Number of steps

Examples

Canny edge control:

curl -X POST https://api.eachlabs.ai/v1/prediction \
  -H "Content-Type: application/json" \
  -H "X-API-Key: $EACHLABS_API_KEY" \
  -d '{
    "model": "flux-dev-controlnet",
    "version": "0.0.1",
    "input": {
      "prompt": "a cyberpunk cityscape at night, neon lights, rain-slicked streets, ultra detailed",
      "control_image": "https://example.com/city-skyline.jpg",
      "control_type": "canny",
      "control_strength": 0.6,
      "guidance_scale": 4,
      "steps": 30,
      "output_format": "png"
    }
  }'

Soft edge with LoRA:

curl -X POST https://api.eachlabs.ai/v1/prediction \
  -H "Content-Type: application/json" \
  -H "X-API-Key: $EACHLABS_API_KEY" \
  -d '{
    "model": "flux-dev-controlnet",
    "version": "0.0.1",
    "input": {
      "prompt": "anime style illustration of a girl in a flower garden, Studio Ghibli",
      "control_image": "https://example.com/person-in-garden.jpg",
      "control_type": "soft_edge",
      "soft_edge_preprocessor": "HED",
      "control_strength": 0.4,
      "lora_url": "https://huggingface.co/my-org/anime-style-lora.safetensors",
      "lora_strength": 0.8,
      "steps": 35,
      "seed": 42
    }
  }'

Related Models

• flux-canny-pro - Pro canny edge control
• flux-depth-pro - Pro depth control
• sdxl-controlnet - SDXL-based ControlNet

Documentation

• each::labs Docs
• API Reference