README

PhotoMaker --


  
 PhotoMaker: Customizing Realistic Human Photos via Stacked ID Embedding  
[Paper]   [Project Page]   [Model Card] 

[💥New 🤗 Demo (PhotoMaker V2)]   [🤗 Demo (Realistic)]   [🤗 Demo (Stylization)] 

[Replicate Demo (Realistic)]   [Replicate Demo (Stylization)]   [Jittor version]  



PhotoMaker-V2 is supported by the HunyuanDiT team. 

🥳 We release PhotoMaker V2. Please refer to comparisons between PhotoMaker V1, PhotoMaker V2, IP-Adapter-FaceID-plus-V2, and InstantID. Please watch this video for how to use our demo. For PhotoMaker V2 ComfyUI nodes, please refer to the Related Resources 



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 🌠  Key Features:

1. Rapid customization within seconds, with no additional LoRA training.
2. Ensures impressive ID fidelity, offering diversity, promising text controllability, and high-quality generation.
3. Can serve as an Adapter to collaborate with other Base Models alongside LoRA modules in community.

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❗❗ Note: If there are any PhotoMaker based resources and applications, please leave them in the discussion and we will list them in the Related Resources section in README file.
Now we know the implementation of Replicate, Windows, ComfyUI, and WebUI. Thank you all! 



!photomaker_demo_fast



 🚩 New Features/Updates
- ✅ July 22, 2024. 💥 We release PhotoMaker V2 with improved ID fidelity. At the same time, it still maintains the generation quality, editability, and compatibility with any plugins that PhotoMaker V1 offers. We have also provided scripts for integration with ControlNet, T2I-Adapter, and IP-Adapter to offer excellent control capabilities. Users can further customize scripts for upgrades, such as combining with LCM for acceleration or integrating with IP-Adapter-FaceID or InstantID to further improve ID fidelity. We will release technical report of PhotoMaker V2 soon. Please refer to this doc for a quick preview. 
- ✅ January 20, 2024. An important note: For those GPUs that do not support bfloat16, please change this line to torch_dtype = torch.float16, the speed will be greatly improved (1min/img (before) vs. 14s/img (after) on V100). The minimum GPU memory requirement for PhotoMaker is 11G (Please refer to this link for saving GPU memory).
- ✅ January 15, 2024. We release PhotoMaker.

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 🔥 Examples


 Realistic generation 

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- PhotoMaker notebook demo


  



  


 Stylization generation 

Note: only change the base model and add the LoRA modules for better stylization

- 
- PhotoMaker-Style notebook demo 


  

  

  


 🔧 Dependencies and Installation

- Python = 3.8 (Recommend to use Anaconda or Miniconda)
- PyTorch = 2.0.0
bash
conda create --name photomaker python=3.10
conda activate photomaker
pip install -U pip

 Install requirements
pip install -r requirements.txt

 Install photomaker
pip install git+https://github.com/TencentARC/PhotoMaker.git


Then you can run the following co