Over the past two decades, researchers in the field of visual aesthetics have studied numerous quantitative (objective) image properties and how they relate to visual aesthetic appreciation. However, results are difficult to compare between research groups. One reason is that researchers use different sets of image properties in their studies. But even if the same properties are used, the image pre-processing techniques may differ and often researchers use their own customized scripts to calculate the image properties. To provide greater accessibility and comparability of research results in visual experimental aesthetics, we developed an open-access and easy-to-use toolbox (called the 'Aesthetics Toolbox'). The Toolbox allows users to calculate a well-defined set of quantitative image properties popular in contemporary research. The properties include lightness and color statistics, Fourier spectral properties, fractality, self-similarity, symmetry, as well as different entropy measures and CNN-based variances. Compatible with most devices, the Toolbox provides an intuitive click-and-drop web interface. In the Toolbox, we integrated the original scripts of four different research groups and translated them into Python 3. To ensure that results were consistent across analyses, we took care that results from the Python versions of the scripts were the same as those from the original scripts. The toolbox, detailed documentation, and a link to the cloud version are available via Github: https://github.com/RBartho/Aesthetics-Toolbox. In summary, we developed a toolbox that helps to standardize and simplify the calculation of quantitative image properties for visual aesthetics research.

翻译：在过去的二十年里，视觉美学领域的研究者研究了大量定量（客观）图像属性及其与视觉审美评价的关系。然而，不同研究团队之间的结果难以比较。原因之一是研究者在研究中使用了不同的图像属性集。但即使使用相同的属性，图像预处理技术也可能不同，且研究者通常使用自己定制的脚本来计算图像属性。为了提高视觉实验美学研究结果的可获取性和可比性，我们开发了一个开源且易于使用的工具箱（称为“美学工具箱”）。该工具箱允许用户计算当代研究中常用的一组明确定义的定量图像属性。这些属性包括明度和颜色统计、傅里叶频谱属性、分形性、自相似性、对称性，以及不同的熵度量和基于CNN的方差。该工具箱兼容大多数设备，提供直观的拖放式网页界面。在工具箱中，我们整合了四个不同研究团队的原始脚本，并将其转换为Python 3版本。为确保分析结果的一致性，我们确保Python版本脚本的结果与原始脚本的结果相同。该工具箱、详细文档以及云端版本的链接可通过Github获取：https://github.com/RBartho/Aesthetics-Toolbox。总之，我们开发了一个工具箱，旨在帮助标准化和简化视觉美学研究中定量图像属性的计算。