🎨 ColorFlow:

Retrieval-Augmented Image Sequence Colorization

Project Page | ArXiv Preprint | GitHub Repository

NOTE: Each time you switch the input style, the corresponding model will be reloaded, which may take some time. Please be patient.

Welcome to the demo of ColorFlow. Follow the steps below to explore the capabilities of our model:

  1. Choose input style: GrayImage(ScreenStyle)、Sketch with Shading or Sketch.
  2. Upload your image: Use the 'Upload' button to select the image you want to colorize.
  3. Preprocess the image: Click the 'Preprocess' button to decolorize the image.
  4. Upload reference images: Upload multiple reference images to guide the colorization.
  5. Set sampling parameters (optional): Adjust the settings and click the Colorize button.

⏱️ ZeroGPU Time Limit: Hugging Face ZeroGPU has an inference time limit of 180 seconds. You may need to log in with a free account to use this demo. Large sampling steps might lead to timeout (GPU Abort). In that case, please consider logging in with a Pro account or running it on your local machine.

注意：每次切换输入样式时，相应的模型将被重新加载，可能需要一些时间。请耐心等待。

欢迎使用 ColorFlow 演示。请按照以下步骤探索我们模型的能力：

  1. 选择输入样式：灰度图(ScreenStyle)、线稿+阴影、线稿。
  2. 上传您的图像：使用“上传”按钮选择要上色的图像。
  3. 预处理图像：点击“预处理”按钮以去色图像。
  4. 上传参考图像：上传多张参考图像以指导上色。
  5. 设置采样参数（可选）：调整设置并点击 上色 按钮。

⏱️ ZeroGPU时间限制：Hugging Face ZeroGPU 的推理时间限制为 180 秒。您可能需要使用免费帐户登录以使用此演示。大采样步骤可能会导致超时（GPU 中止）。在这种情况下，请考虑使用专业帐户登录或在本地计算机上运行。

Input Style
Select Resolution(Width*Height)
0 100000
4 100

Quick Examples
Examples
Image to Colorize Reference Images (Upload multiple) Input Style Select Resolution(Width*Height) Random Seed Inference Steps
GitHub Stars

If ColorFlow is helpful, please help to ⭐ the Github Repo. Thanks!

📧 Contact
If you have any questions, please feel free to reach me out at zhuangjh23@mails.tsinghua.edu.cn.

📝 Citation
If our work is useful for your research, please consider citing:

@misc{zhuang2024colorflow,
      title={ColorFlow: Retrieval-Augmented Image Sequence Colorization}, 
      author={Junhao Zhuang and Xuan Ju and Zhaoyang Zhang and Yong Liu and Shiyi Zhang and Chun Yuan and Ying Shan},
      year={2024},
      eprint={2412.11815},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2412.11815},
}