Building Color Quality Evaluation of Urban Street Based on Street View Images from Python Crawler: Taking Qingnian Street as an Example

In the process of urban regeneration, there is a problem of uniformity in the color planning of Chinese urban buildings. In this paper, Python techniques were used to crawl data from Baidu Street View Map and analyze data from about 2.5 km of selected building street view images of the south section of Qingnian Street in Shenyang. This paper used physical psychology methods to explore the relationship between color and the public's subjective perceptions. Finally, the paper evaluated the buildings color quality. According to the survey results, the building colors of Qingnian Street were dominated by blue and white, the building tones tended to be complex. The buildings color quality in the south of the street was higher than that in the north. The color quality in the east side interface was more balanced. The color quality in the west side interface was more disparate. The overall building color quality of Qingnian Street needs to be improved, strengthened and coordinated. The building colors should be harmonious and unified, which can provide informative suggestions for the future color planning and design of urban street buildings.