Solar active regions are key source regions of intense solar phenomena such as solar flares and coronal mass ejections (CMEs). Accurate identification of these regions can help forecast the impact of solar activities on Earth's environment. This dataset utilizes solar full-disk magnetograms observed by the Helioseismic and Magnetic Imager onboard the Solar Dynamic Observatory (2010-2019), combined with NOAA AR numbers provided by the SolarMonitor website. The active regions are annotated using an image processing-based recognition method along with manual labeling. The dataset consists of 6,975 solar full-disk magnetograms, taken every 12 hours, with a total numbe of 19,098 annotations consisting of the active-region informationfor each magnetogram.This dataset serves as a benchmark resource for developing deep learning solar active region detection models, and aims to enhance predictive capabilities for severe space weather phenomena through physics-informed training samples.