Handheld Thermometer Scene Hand Keypoint Detection Dataset

With the increase in health awareness, the importance of temperature detection in the healthcare industry is becoming more prominent. Current temperature detection methods largely rely on manual operation and are easily affected by environmental and human factors, leading to inaccurate measurements. This dataset aims to provide high-quality hand keypoint detection data to help improve the accuracy of automated temperature detection. The dataset construction includes using high-resolution cameras to take pictures of handheld thermometers under different lighting and background conditions, with multiple rounds of annotation and expert review to ensure data quality. Data is stored in JPG format and organized by folder classification for easy subsequent processing and use. Data quality control measures include consistency checks and expert reviews to ensure the accuracy and completeness of keypoint annotations.