Curtain Track Guide Slot Detection Dataset

The current retail e-commerce industry faces challenges such as uneven product quality and low detection efficiency, especially in the detection of curtain track guide slots. Manual inspection is not only time-consuming but also prone to human errors, making quality control difficult. Existing automated detection solutions largely rely on traditional visual recognition technologies, which struggle to adapt to complex environments and still lack accuracy. This dataset aims to improve the detection accuracy and efficiency of curtain track guide slots through high-quality target detection data, meeting the growing quality demands of the smart home product market. Data is collected using high-resolution cameras under standard lighting conditions to ensure clear and usable images. To enhance data quality, we implemented multiple rounds of annotation and consistency checks and invited domain experts for review to ensure data accuracy and reliability. Data is stored in JPEG format and categorized and organized according to product type and detection needs.