| | --- |
| | 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 |
| | tags: |
| | - Text-to-Image |
| | - ControlNet |
| | - Diffusers |
| | - Stable Diffusion |
| | base_model: black-forest-labs/FLUX.1-dev |
| | --- |
| | |
| |
|
| | # FLUX.1-dev-Controlnet-Union |
| |
|
| | <img src="./images/image_union.png" width = "1000" /> |
| |
|
| |
|
| | ## Release |
| |
|
| | - [2024/08/26] 🔥 Release [FLUX.1-dev-ControlNet-Union-Pro](https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro). Please install from [the source](https://github.com/huggingface/diffusers) before the next release. We have supported CN-Union and Multi-ControlNets via [this PR](https://github.com/huggingface/diffusers/pull/9175). |
| |
|
| | - [2024/08/20] Release the beta version. |
| |
|
| | - [2024/08/14] Release the alpha version. |
| |
|
| |
|
| |
|
| | ## Checkpoint |
| |
|
| | The training of union controlnet requires a significant amount of computational power. |
| | The current release is the first beta version checkpoint that maybe not been fully trained. |
| | The fully trainedbeta version is in the training process. |
| | We have conducted ablation studies that have demonstrated the validity of the code. |
| | The open-source release of the first beta version is solely to facilitate the rapid growth of the open-source community and the Flux ecosystem; |
| | it is common to encounter bad cases (please accept my apologies). |
| | It is worth noting that we have found that even a fully trained Union model may not perform as well as specialized models, such as pose control. |
| | However, as training progresses, the performance of the Union model will continue to approach that of specialized models. |
| |
|
| |
|
| | ## Control Mode |
| |
|
| | | Control Mode | Description | Current Model Validity | |
| | |:------------:|:-----------:|:-----------:| |
| | |0|canny|🟢high| |
| | |1|tile|🟢high| |
| | |2|depth|🟢high| |
| | |3|blur|🟢high| |
| | |4|pose|🟢high| |
| | |5|gray|🔴low| |
| | |6|lq|🟢high| |
| |
|
| |
|
| | # Inference |
| | ```python |
| | import torch |
| | from diffusers.utils import load_image |
| | from diffusers import FluxControlNetPipeline, FluxControlNetModel |
| | |
| | base_model = 'black-forest-labs/FLUX.1-dev' |
| | controlnet_model = 'InstantX/FLUX.1-dev-Controlnet-Union' |
| | |
| | controlnet = FluxControlNetModel.from_pretrained(controlnet_model, torch_dtype=torch.bfloat16) |
| | pipe = FluxControlNetPipeline.from_pretrained(base_model, controlnet=controlnet, torch_dtype=torch.bfloat16) |
| | pipe.to("cuda") |
| | |
| | control_image_canny = load_image("https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Union-alpha/resolve/main/images/canny.jpg") |
| | controlnet_conditioning_scale = 0.5 |
| | control_mode = 0 |
| | |
| | width, height = control_image.size |
| | |
| | prompt = 'A bohemian-style female travel blogger with sun-kissed skin and messy beach waves.' |
| | |
| | image = pipe( |
| | prompt, |
| | control_image=control_image, |
| | control_mode=control_mode, |
| | width=width, |
| | height=height, |
| | controlnet_conditioning_scale=controlnet_conditioning_scale, |
| | num_inference_steps=24, |
| | guidance_scale=3.5, |
| | ).images[0] |
| | image.save("image.jpg") |
| | ``` |
| |
|
| | # Multi-Controls Inference |
| | ```python |
| | import torch |
| | from diffusers.utils import load_image |
| | from diffusers import FluxControlNetPipeline, FluxControlNetModel, FluxMultiControlNetModel |
| | |
| | base_model = 'black-forest-labs/FLUX.1-dev' |
| | controlnet_model_union = './InstantX/FLUX.1-dev-Controlnet-Union' |
| | |
| | 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/InstantX/FLUX.1-dev-Controlnet-Union/resolve/main/images/depth.jpg") |
| | control_mode_depth = 2 |
| | |
| | control_image_canny = load_image("https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Union/resolve/main/images/canny.jpg") |
| | control_mode_canny = 0 |
| | |
| | width, height = control_image.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] |
| | |
| | ``` |
| |
|
| | # Resources |
| | - [InstantX/FLUX.1-dev-Controlnet-Canny](https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Canny) |
| | - [InstantX/FLUX.1-dev-Controlnet-Union](https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Union) |
| | - [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 |
| | Thanks [zzzzzero](https://github.com/zzzzzero) for help us pointing out some bugs in the training. |
| |
|
