Text-to-Image
Diffusers
Safetensors
English
Text-to-Image
ControlNet
Diffusers
Flux.1-dev
image-generation
Stable Diffusion
Instructions to use mo22323234545/FLUX.1-dev-ControlNet-Union-Pro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mo22323234545/FLUX.1-dev-ControlNet-Union-Pro with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mo22323234545/FLUX.1-dev-ControlNet-Union-Pro", torch_dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
| license: other | |
| license_name: flux-1-dev-non-commercial-license | |
| license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md | |
| language: | |
| - en | |
| library_name: diffusers | |
| pipeline_tag: text-to-image | |
| tags: | |
| - Text-to-Image | |
| - ControlNet | |
| - Diffusers | |
| - Flux.1-dev | |
| - image-generation | |
| - Stable Diffusion | |
| base_model: black-forest-labs/FLUX.1-dev | |
| # FLUX.1-dev-ControlNet-Union-Pro | |
| This repository contains a unified ControlNet for FLUX.1-dev model jointly released by researchers from [InstantX Team](https://huggingface.co/InstantX) and [Shakker Labs](https://huggingface.co/Shakker-Labs). | |
| <div class="container"> | |
| <img src="./assets/poster.png" width="1024"/> | |
| </div> | |
| # Model Cards | |
| - This checkpoint is a Pro version of [FLUX.1-dev-Controlnet-Union](https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Union) trained with more steps and datasets. | |
| - This model supports 7 control modes, including canny (0), tile (1), depth (2), blur (3), pose (4), gray (5), low quality (6). | |
| - The recommended controlnet_conditioning_scale is 0.3-0.8. | |
| - This model can be jointly used with other ControlNets. | |
| # Showcases | |
| <div class="container"> | |
| <img src="./assets/teaser1.png" width="1024"/> | |
| <img src="./assets/teaser2.png" width="1024"/> | |
| <img src="./assets/teaser3.png" width="1024"/> | |
| </div> | |
| # Inference | |
| Please install `diffusers` from [the source](https://github.com/huggingface/diffusers), as [the PR](https://github.com/huggingface/diffusers/pull/9175) has not been included in currently released version yet. | |
| # Multi-Controls Inference | |
| ```python | |
| import torch | |
| from diffusers.utils import load_image | |
| from diffusers import FluxControlNetPipeline, FluxControlNetModel | |
| from diffusers.models import FluxMultiControlNetModel | |
| base_model = 'black-forest-labs/FLUX.1-dev' | |
| controlnet_model_union = 'Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro' | |
| controlnet_union = FluxControlNetModel.from_pretrained(controlnet_model_union, torch_dtype=torch.bfloat16) | |
| controlnet = FluxMultiControlNetModel([controlnet_union]) # we always recommend loading via FluxMultiControlNetModel | |
| pipe = FluxControlNetPipeline.from_pretrained(base_model, controlnet=controlnet, torch_dtype=torch.bfloat16) | |
| pipe.to("cuda") | |
| prompt = 'A bohemian-style female travel blogger with sun-kissed skin and messy beach waves.' | |
| control_image_depth = load_image("https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro/resolve/main/assets/depth.jpg") | |
| control_mode_depth = 2 | |
| control_image_canny = load_image("https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro/resolve/main/assets/canny.jpg") | |
| control_mode_canny = 0 | |
| width, height = control_image_depth.size | |
| image = pipe( | |
| prompt, | |
| control_image=[control_image_depth, control_image_canny], | |
| control_mode=[control_mode_depth, control_mode_canny], | |
| width=width, | |
| height=height, | |
| controlnet_conditioning_scale=[0.2, 0.4], | |
| num_inference_steps=24, | |
| guidance_scale=3.5, | |
| generator=torch.manual_seed(42), | |
| ).images[0] | |
| ``` | |
| We also support loading multiple ControlNets as before, you can load as | |
| ```python | |
| from diffusers import FluxControlNetModel | |
| from diffusers.models import FluxMultiControlNetModel | |
| controlnet_model_union = 'Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro' | |
| controlnet_union = FluxControlNetModel.from_pretrained(controlnet_model_union, torch_dtype=torch.bfloat16) | |
| controlnet_model_depth = 'Shakker-Labs/FLUX.1-dev-Controlnet-Depth' | |
| controlnet_depth = FluxControlNetModel.from_pretrained(controlnet_model_depth, torch_dtype=torch.bfloat16) | |
| controlnet = FluxMultiControlNetModel([controlnet_union, controlnet_depth]) | |
| # set mode to None for other ControlNets | |
| control_mode=[2, None] | |
| ``` | |
| # Resources | |
| - [InstantX/FLUX.1-dev-Controlnet-Canny](https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Canny) | |
| - [Shakker-Labs/FLUX.1-dev-ControlNet-Depth](https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Depth) | |
| - [Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro](https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro) | |
| # Acknowledgements | |
| This project is trained by [InstantX Team](https://huggingface.co/InstantX) and sponsored by [Shakker AI](https://www.shakker.ai/). The original idea is inspired by [xinsir/controlnet-union-sdxl-1.0](https://huggingface.co/xinsir/controlnet-union-sdxl-1.0). All copyright reserved. | |