The perceived wealth and physical disorder scores annotation dataset for Chinese urban street view images

The perceived wealth and physical disorder scores annotation dataset comprises 40,000 Chinese street view images. Half of these images are annotated with perceived wealth scores ranging from 0 to 10, while the other half are annotated with perceived physical disorder scores. Higher scores indicate a greater sense of affluence and disorder in the street scene. These images were annotated by Chinese urban planners. All images are in JPG format and have been uploaded as compressed files. The corresponding perception scores for each image are stored in two CSV tables. These two types of files can be matched using image IDs. Researchers can use this dataset as it is, or augment and supplement it, in order to train their own artificial intelligence perception models to perform large-scale, real-time, automatic inference on other street view images in Chinese cities. This largely overcomes the local prediction bias caused by commonly used datasets such as the MIT Place Pulse Perception Dataset, which rely on Western street view images and Western annotators.Source publication: Zhang, Y., You, Y., Chen, S., & Cai, L. (2025). Geospatial dataset on human perceptions of wealth and physical disorder in urban China using street view imagery and deep learning. Data in Brief, 112116.