The MSC dataset

The Minimum Semantic Content (MSC) image dataset (file data and metadata structure) Each of the 10,426 images in the MSC dataset has been evaluated by 100 observers, ensuring robust data on aesthetic ratings. By including a method for generating "ugly" images alongside more traditionally appealing ones, the MSC dataset enables a re-examination of relationships between low-level image features and aesthetic valuations. We provide a .csv file with raw crowdsourcing results, with each column representing the number of votes received for each of the five aesthetic valuation categories (1 = very ugly, 5 = very beautiful). we also provide results from truncated histogram fittings to the crowdsourcing data. These columns include the final value of mu (mean), the final value of sigma (standard deviation), the final FVAL and ExitFlag values from Matlab’s fminsearch function, and the number of iterations required. Images were modified by observers. We provide categorization columns, specifying whether an image is “uglified,” “beautified,” “auto_uglified,” or “unmodified.” This section also indicates if an image served as the starting point for a modification (e.g., “uglified_original” denotes an image used as the basis for an uglification process). This structure ensures that users can easily identify the type and provenance of each image, as well as access comprehensive metadata and aesthetic ratings for further analysis.