Remote Control Button Area Detection Dataset

The current retail e-commerce industry faces low user interaction efficiency issues, especially in remote control usage scenarios where users often struggle to quickly find the needed buttons. Existing button detection solutions largely rely on traditional image processing technology, with insufficient annotation accuracy that fails to meet practical application needs. This dataset aims to address the limitations of existing technology in button-level understanding and OCR alignment by providing high-quality remote control button area detection data. The dataset contains 5000 images of remote controls. Data collection uses high-resolution cameras in standard lighting environments to ensure data clarity and annotation accuracy. For quality control, multiple rounds of annotation and expert review mechanisms are employed to ensure the consistency and accuracy of the annotations. The data storage format is JPG, and each image is equipped with a corresponding annotation file for ease of use.