Office Building Cleaning Tools Standard Storage Inspection Image Dataset

In modern office buildings, cleaning and environmental management are crucial but often face management challenges due to irregular tool storage. Currently, traditional manual inspection methods are time-consuming and labor-intensive, and the lack of automated detection tools limits efficiency and accuracy. This dataset focuses on providing high-quality images for training automated detection systems to meet the demands of improving management in the cleaning field. The data collection process uses HD cameras under varying time, lighting, and distance conditions to ensure diversity and representativeness. In terms of quality control, the data undergoes multiple rounds of labeling, consistency checks, and expert review to ensure accuracy and completeness of labeling. The labeling team consists of experts from the fields of environmental management and image processing, possessing rich experience. Data preprocessing includes steps such as image enhancement and size standardization to improve training effectiveness. The data is stored in JPG format, organized in groups by floor and area for easy retrieval and use.The core advantage of this dataset is its high-quality labeling, with an accuracy of 99%, offering consistency and completeness. Innovative labeling tools and data enhancement techniques are employed to improve the dataset's applicability. In terms of application value, it effectively solves the problem of irregular cleaning tool storage detection in office buildings, significantly improving management efficiency and accuracy. Compared to similar datasets, it offers more comprehensive data sampling and more precise labeling, especially advantageous under varying light and angle conditions. The diversity and comprehensiveness of the data make it applicable and expandable in multiple office building environments.