Rice Cooker Button Light Anomaly Recognition Dataset

The current popularization of smart home appliances in the industrial field has made products like rice cookers gradually become an important part of the family. However, existing rice cookers often have malfunctions in the light indication function, leading users to inaccurately determine the working status of the rice cooker, which affects user experience. Existing solutions such as manual detection or simple troubleshooting are time-consuming and not accurate enough, failing to effectively enhance the intelligence level of products. This dataset aims to assist in the development of more intelligent fault recognition systems by providing diverse images of rice cooker button light states. The dataset contains a large number of images of rice cooker light states, collected using high-resolution cameras under standard lighting conditions to ensure image clarity and accuracy. We use multiple rounds of annotation and expert review to ensure the quality of the data annotations, ensuring that the labels of each image are strictly reviewed. Data is stored in JPEG format and organized into different folders to classify normal and abnormal states, facilitating subsequent processing and training use.