VOOZH about

URL: https://huggingface.co/xinsir/controlnet-union-sdxl-1.0

⇱ xinsir/controlnet-union-sdxl-1.0 Β· Hugging Face


ControlNet++: All-in-one ControlNet for image generations and editing!

ProMax Model has released!! 12 control + 5 advanced editing, just try it!!!

πŸ‘ images_display

Network Arichitecture

πŸ‘ images

Advantages about the model

  • Use bucket training like novelai, can generate high resolutions images of any aspect ratio
  • Use large amount of high quality data(over 10000000 images), the dataset covers a diversity of situation
  • Use re-captioned prompt like DALLE.3, use CogVLM to generate detailed description, good prompt following ability
  • Use many useful tricks during training. Including but not limited to date augmentation, mutiple loss, multi resolution
  • Use almost the same parameter compared with original ControlNet. No obvious increase in network parameter or computation.
  • Support 10+ control conditions, no obvious performance drop on any single condition compared with training independently
  • Support multi condition generation, condition fusion is learned during training. No need to set hyperparameter or design prompts.
  • Compatible with other opensource SDXL models, such as BluePencilXL, CounterfeitXL. Compatible with other Lora models.

We design a new architecture that can support 10+ control types in condition text-to-image generation and can generate high resolution images visually comparable with midjourney. The network is based on the original ControlNet architecture, we propose two new modules to: 1 Extend the original ControlNet to support different image conditions using the same network parameter. 2 Support multiple conditions input without increasing computation offload, which is especially important for designers who want to edit image in detail, different conditions use the same condition encoder, without adding extra computations or parameters. We do thoroughly experiments on SDXL and achieve superior performance both in control ability and aesthetic score. We release the method and the model to the open source community to make everyone can enjoy it.

Inference scripts and more details can found: https://github.com/xinsir6/ControlNetPlus/tree/main

If you find it useful, please give me a star, thank you very much

SDXL ProMax version has been released!!!,Enjoy it!!!

I am sorry that because of the project's revenue and expenditure are difficult to balance, the GPU resources are assigned to other projects that are more likely to be profitable, the SD3 trainging is stopped until I find enough GPU supprt, I will try my best to find GPUs to continue training. If this brings you inconvenience, I sincerely apologize for that. I want to thank everyone who likes this project, your support is what keeps me going

Note: we put the promax model with a promax suffix in the same huggingface model repo, detailed instructions will be added later.

Advanced editing features in Promax Model

Tile Deblur

πŸ‘ blur0
πŸ‘ blur1
πŸ‘ blur2
πŸ‘ blur3
πŸ‘ blur4
πŸ‘ blur5

Tile variation

πŸ‘ var0
πŸ‘ var1
πŸ‘ var2
πŸ‘ var3
πŸ‘ var4
πŸ‘ var5

Tile Super Resolution

Following example show from 1M resolution --> 9M resolution

Image Inpainting

πŸ‘ inp0
πŸ‘ inp1
πŸ‘ inp2
πŸ‘ inp3
πŸ‘ inp4
πŸ‘ inp5

Image Outpainting

πŸ‘ oup0
πŸ‘ oup1
πŸ‘ oup2
πŸ‘ oup3
πŸ‘ oup4
πŸ‘ oup5

Visual Examples

Openpose

πŸ‘ pose0
πŸ‘ pose1
πŸ‘ pose2
πŸ‘ pose3
πŸ‘ pose4

Depth

πŸ‘ depth0
πŸ‘ depth1
πŸ‘ depth2
πŸ‘ depth3
πŸ‘ depth4

Canny

πŸ‘ canny0
πŸ‘ canny1
πŸ‘ canny2
πŸ‘ canny3
πŸ‘ canny4

Lineart

πŸ‘ lineart0
πŸ‘ lineart1
πŸ‘ lineart2
πŸ‘ lineart3
πŸ‘ lineart4

AnimeLineart

πŸ‘ animelineart0
πŸ‘ animelineart1
πŸ‘ animelineart2
πŸ‘ animelineart3
πŸ‘ animelineart4

Mlsd

πŸ‘ mlsd0
πŸ‘ mlsd1
πŸ‘ mlsd2
πŸ‘ mlsd3
πŸ‘ mlsd4

Scribble

πŸ‘ scribble0
πŸ‘ scribble1
πŸ‘ scribble2
πŸ‘ scribble3
πŸ‘ scribble4

Hed

πŸ‘ hed0
πŸ‘ hed1
πŸ‘ hed2
πŸ‘ hed3
πŸ‘ hed4

Pidi(Softedge)

πŸ‘ pidi0
πŸ‘ pidi1
πŸ‘ pidi2
πŸ‘ pidi3
πŸ‘ pidi4

Teed

πŸ‘ ted0
πŸ‘ ted1
πŸ‘ ted2
πŸ‘ ted3
πŸ‘ ted4

Segment

πŸ‘ segment0
πŸ‘ segment1
πŸ‘ segment2
πŸ‘ segment3
πŸ‘ segment4

Normal

πŸ‘ normal0
πŸ‘ normal1
πŸ‘ normal2
πŸ‘ normal3
πŸ‘ normal4

Multi Control Visual Examples

Openpose + Canny

πŸ‘ pose_canny0
πŸ‘ pose_canny1
πŸ‘ pose_canny2
πŸ‘ pose_canny3
πŸ‘ pose_canny4
πŸ‘ pose_canny5

Openpose + Depth

πŸ‘ pose_depth0
πŸ‘ pose_depth1
πŸ‘ pose_depth2
πŸ‘ pose_depth3
πŸ‘ pose_depth4
πŸ‘ pose_depth5

Openpose + Scribble

πŸ‘ pose_scribble0
πŸ‘ pose_scribble1
πŸ‘ pose_scribble2
πŸ‘ pose_scribble3
πŸ‘ pose_scribble4
πŸ‘ pose_scribble5

Openpose + Normal

πŸ‘ pose_normal0
πŸ‘ pose_normal1
πŸ‘ pose_normal2
πŸ‘ pose_normal3
πŸ‘ pose_normal4
πŸ‘ pose_normal5

Openpose + Segment

πŸ‘ pose_segment0
πŸ‘ pose_segment1
πŸ‘ pose_segment2
πŸ‘ pose_segment3
πŸ‘ pose_segment4
πŸ‘ pose_segment5

Downloads last month
138,888

Model tree for xinsir/controlnet-union-sdxl-1.0

Adapters
73 models
Finetunes
2 models

Spaces using xinsir/controlnet-union-sdxl-1.0 100