Smart Toilet Sensing Area Detection Dataset

In the current retail e-commerce industry, smart toilets as emerging products are increasingly favored by consumers. However, existing sensing technology still faces many challenges in recognition accuracy and response speed, resulting in poor user experience. Traditional solutions mostly rely on simple sensors, which cannot accurately determine the user's operation intentions, causing false triggering or lack of triggering. This dataset aims to improve the sensing area recognition ability of smart toilets through object detection technology, meeting the market demand for efficient and precise products. The dataset is constructed using high-resolution image capture equipment and shot in real usage scenarios to ensure the authenticity and diversity of the data. We have implemented multiple rounds of annotation and expert reviews as quality control measures to ensure the consistency and accuracy of the annotations. In addition, the data is stored in JPG format, with a clear organizational structure for easy subsequent processing and analysis.