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1

Sumi-e no Kurozuappu Ink Painting Closeups

Dataset Description

This dataset contains 1,250 synthetically generated images of Japanese Sumi-e ink paintings. The images were created to explore the capabilities of diffusion models in replicating the nuanced art style of traditional Japanese ink painting. The dataset is ideal for those interested in niche artistic model creation, generating LORAs, or simply enjoying and sharing these artistic expressions.

Example Image

Traditional Japanese ink painting of bamboo stalks and leaves

An example of traditional Japanese ink painting featuring bamboo stalks and leaves, showcasing the intricate details and nuanced brushwork characteristic of Sumi-e art.

Dataset Structure

  • image: The image data (Sumi-e ink painting close-ups).
  • seed: Random seed used for image generation.
  • positive_prompt: Prompt used to guide the generation towards desired features.
  • negative_prompt: Prompt used to avoid undesired features in the images.
  • model: Model utilized for generating the images.
  • steps: Number of iterations used by the model during generation.
  • cfg: Configuration parameters applied during generation.
  • sampler_name: Sampler algorithm used in the process.
  • scheduler: Scheduling algorithm or method employed.
  • denoise: Denoising level applied to the final images.

Usage

This dataset is open for any type of use, including but not limited to:

  • Sharing the images.
  • Creating LORAs (Low-Rank Adaptation of Large Language Models).
  • Building niche artistic models based on Sumi-e art style.

Licensing

This dataset is shared under the CC BY 4.0 license. No warranties or guarantees are provided.

Citation

If you use this dataset, please cite it as follows:

@dataset{takara-ai_sumi-e_no_kurozuappu,
  author = {Takara.ai},
  title = {Sumi-e no Kurozuappu Ink Painting Closeups},
  year = {2024},
  url = {https://huggingface.co/datasets/takara-ai/Sumi-e_no_kurozuappu_ink_painting_closeups}
}

Disclaimer

This dataset is offered with no warranties or guarantees. Use it at your own discretion.

Related Resources

If you enjoyed exploring this dataset, check out more of our art-related datasets at the Takara.ai open-source gallery. Discover a variety of unique collections that showcase different art styles and creative expressions.

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