We introduce Lunara Aesthetic II, a publicly released, ethically sourced image dataset designed to support controlled evaluation and learning of contextual consistency in modern image generation and editing systems. The dataset comprises 2,854 anchor-linked variation pairs derived from original art and photographs created by Moonworks. Each variation pair applies contextual transformations, such as illumination, weather, viewpoint, scene composition, color tone, or mood; while preserving a stable underlying identity. Lunara Aesthetic II operationalizes identity-preserving contextual variation as a supervision signal while also retaining Lunara's signature high aesthetic scores. Results show high identity stability, strong target attribute realization, and a robust aesthetic profile that exceeds large-scale web datasets. Released under the Apache 2.0 license, Lunara Aesthetic II is intended for benchmarking, fine-tuning, and analysis of contextual generalization, identity preservation, and edit robustness in image generation and image-to-image systems with interpretable, relational supervision. The dataset is publicly available at: https://huggingface.co/datasets/moonworks/lunara-aesthetic-image-variations.

翻译：我们介绍了Lunara美学II，这是一个公开发布、符合伦理的图像数据集，旨在支持对现代图像生成与编辑系统中上下文一致性的受控评估与学习。该数据集包含2,854个基于锚点的变体对，源自月球作品创作的原创艺术与摄影作品。每个变体对应用了上下文变换，例如光照、天气、视角、场景构图、色调或氛围，同时保持稳定的底层身份特征。Lunara美学II将身份保持的上下文变体操作化为监督信号，同时保留了Lunara标志性的高美学评分。结果显示其具有高身份稳定性、强目标属性实现度，以及超越大规模网络数据集的稳健美学特征。本数据集基于Apache 2.0许可证发布，旨在为图像生成和图像到图像系统中上下文泛化、身份保持和编辑鲁棒性的基准测试、微调和分析提供可解释的关系监督。数据集公开发布于：https://huggingface.co/datasets/moonworks/lunara-aesthetic-image-variations。