Home Robot Image Classification Dataset

With the rapid development of smart devices, home robots are playing an increasingly important role in daily life. However, existing image recognition technology still lacks accuracy in complex environments, leading to misjudgments when robots recognize obstacles and execute tasks. This dataset aims to address the image classification issues of home robots in different scenes and provides high-quality labeled data for algorithm training. Data collection involved real shooting in various home scenarios, using high-resolution cameras to capture images under different lighting and environmental conditions. To ensure data quality, quality control measures such as multiple rounds of labeling, consistency checks, and expert reviews were used. The final storage is in JPG format, organized in a folder structure for easy subsequent use.