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strkyyy/
ukiyoe-woodblock

Name: ukiyoe-woodblock
Availability: InStock

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SDXL LoRA: Ukiyo-e Woodblock Print Style

What it does

Capture the essence of traditional Japanese ukiyo-e woodblock prints with this LoRA model. It renders images in the distinctive style characterized by flat color planes, bold ink outlines, and a palette dominated by indigo and vermilion.

How to use

To apply the ukiyo-e aesthetic, add 'uk1y03' as your trigger word to your prompt. For best results, set the strength between 0.6 and 1.0, with 0.85 being a good starting point. Use an EMA sampler for smoother transitions.

Best for

Adding traditional Japanese art style to any scene
Illustrating historical or fantasy scenes involving Japan
Depicting iconic figures like samurai warriors or courtesans in period attire
Enhancing natural landscapes with the elegance of ukiyo-e
Creating stylized artwork inspired by Edo-period aesthetics

Tips

Incorporate Japanese motifs and patterns to complement the style.
Adjust the strength based on the complexity of your scene for optimal results.

Example Prompts

uk1y03 A serene Japanese tea house under cherry blossoms at dusk, evoking peace and tranquility.

uk1y03 Vibrant indigo kimono with intricate gold patterns, elegant portrait of a samurai warrior in profile.

uk1y03 Bold red bridge crossing blue river, architectural scene with pagoda and cherry trees in full bloom.

uk1y03 A carpenter meticulously carving woodblocks for ukiyo-e print, hands painted in black ink outlines.

uk1y03 Moonlit night over Tokyo bay, mysterious and eerie mood with silhouettes of boats and distant lights.

uk1y03 Abstract pattern inspired by ukiyo-e motifs, swirling indigo and vermillion colors on aged paper texture.

Trigger word

Activate with uk1y03. Recommended strength: 0.9.

Showcase

Usage with `diffusers`

python

from diffusers import AutoPipelineForText2Image
import torch

pipe = AutoPipelineForText2Image.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16).to("cuda")
pipe.load_lora_weights("strkyyy/ukiyoe-woodblock")
image = pipe("uk1y03, your prompt", num_inference_steps=30).images[0]

strkyyy/ukiyoe-woodblock