Washing Machine Control Panel Detection Dataset

In the current retail e-commerce industry, the proliferation of smart home devices has led to increased demand for automatic recognition of product control panels. However, existing image recognition solutions often fail to accurately identify various models of washing machine control panels, causing difficulties for users. This dataset aims to solve the model training challenges in object detection by providing high-quality images of washing machine control panels, meeting the market's demand for smart recognition technology. Data collection is primarily conducted using professional photography equipment in a standardized environment to ensure the clarity and quality of the captured images. During the data annotation process, multiple rounds of annotation and consistency checks are used to ensure the accuracy of each sample's annotation. Data is stored in JPG format, organized by category and image ID, facilitating subsequent processing and use.