README.md

metadata

license: other
license_name: flux-1-dev-non-commercial-license
license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.
language:
  - en
  - ka
pipeline_tag: text-to-image
tags:
  - Stable Diffusion
  - image-generation
  - Flux
  - diffusers

This repository provides a collection of ControlNet checkpoints for FLUX.1-dev model by Black Forest Labs

See our github for comfy ui workflows.

See our github for train script, train configs and demo script for inference.

Models

Our collection supports 3 models:

• Canny
• HED
• Depth (Midas)

Each ControlNet is trained on 1024x1024 resolution and works for 1024x1024 resolution. We release v2 versions - better and realistic versions, which can be used directly in ComfyUI!

Please, see our ComfyUI custom nodes installation guide

Examples

See examples of our models results below.
Also, some generation results with input images are provided in "Files and versions"

Inference

To try our models, you have 2 options:

1. Use main.py from our official repo
2. Use our custom nodes for ComfyUI and test it with provided workflows (check out folder /workflows)

See examples how to launch our models:

Canny ControlNet (version 2)

1. Clone our x-flux-comfyui custom nodes
2. Launch ComfyUI
3. Try our canny_workflow.json

Canny ControlNet (version 1)

1. Clone our repo, install requirements
2. Launch main.py in command line with parameters

python3 main.py \
 --prompt "a viking man with white hair looking, cinematic, MM full HD" \
 --image input_image_canny.jpg \
 --control_type canny \
 --repo_id XLabs-AI/flux-controlnet-collections --name flux-canny-controlnet.safetensors --device cuda --use_controlnet \
 --model_type flux-dev --width 768 --height 768 \
 --timestep_to_start_cfg 1 --num_steps 25 --true_gs 3.5 --guidance 4

Depth ControlNet (version 2)

1. Clone our x-flux-comfyui custom nodes
2. Launch ComfyUI
3. Try our depth_workflow.json

Depth ControlNet (version 1)

1. Clone our repo, install requirements
2. Launch main.py in command line with parameters

python3 main.py \
 --prompt "Photo of the bold man with beard and laptop, full hd, cinematic photo" \
 --image input_image_depth1.jpg \
 --control_type depth \
 --repo_id XLabs-AI/flux-controlnet-collections --name flux-depth-controlnet.safetensors --device cuda --use_controlnet \
 --model_type flux-dev --width 1024 --height 1024 \
 --timestep_to_start_cfg 1 --num_steps 25 --true_gs 3.5 --guidance 4

python3 main.py \
 --prompt "photo of handsome fluffy black dog standing on a forest path, full hd, cinematic photo" \
 --image input_image_depth2.jpg \
 --control_type depth \
 --repo_id XLabs-AI/flux-controlnet-collections --name flux-depth-controlnet.safetensors --device cuda --use_controlnet \
 --model_type flux-dev --width 1024 --height 1024 \
 --timestep_to_start_cfg 1 --num_steps 25 --true_gs 3.5 --guidance 4

python3 main.py \
 --prompt "Photo of japanese village with houses and sakura, full hd, cinematic photo" \
 --image input_image_depth3.webp \
 --control_type depth \
 --repo_id XLabs-AI/flux-controlnet-collections --name flux-depth-controlnet.safetensors --device cuda --use_controlnet \
 --model_type flux-dev --width 1024 --height 1024 \
 --timestep_to_start_cfg 1 --num_steps 25 --true_gs 3.5 --guidance 4

HED ControlNet (version 1)

python3 main.py \
 --prompt "2d art of a sitting african rich woman, full hd, cinematic photo" \
 --image input_image_hed1.jpg \
 --control_type hed \
 --repo_id XLabs-AI/flux-controlnet-collections --name flux-hed-controlnet.safetensors --device cuda --use_controlnet \
 --model_type flux-dev --width 768 --height 768 \
 --timestep_to_start_cfg 1 --num_steps 25 --true_gs 3.5 --guidance 4

python3 main.py \
 --prompt "anime ghibli style art of a running happy white dog, full hd" \
 --image input_image_hed2.jpg \
 --control_type hed \
 --repo_id XLabs-AI/flux-controlnet-collections --name flux-hed-controlnet.safetensors --device cuda --use_controlnet \
 --model_type flux-dev --width 768 --height 768 \
 --timestep_to_start_cfg 1 --num_steps 25 --true_gs 3.5 --guidance 4

License

Our weights fall under the FLUX.1 [dev] Non-Commercial License