The loss of glacier mass and the increase in glacial lakes in High Mountain Asia due to climate change led to water-related crises and hazards, such as glacial lake outburst floods (GLOFs). The Sichuan-Tibet Railway (STR), which is crucial for the development of West China, is facing challenges due to these water-related crises. Therefore, there is an urgent need for a high-quality dataset of glacial lakes along the STR corridor, which remains lacking. This study employed a semi-automated lake mapping method, accompanied by rigorous quality assurance and quality control, to create a comprehensive, high-resolution dataset of glacial lakes in approximately 2021, covering the entire STR corridor. The 10-m resolution glacial lake dataset comprises 17,566 glacial lakes, covering a total area of 582.89 +/- 31.45 km2. This dataset features a larger number of lakes yet exhibits a lower mapping error compared to existing inventories in this region. The high-quality glacial lake dataset has the potential to benefit various applications, including assessing lake mapping accuracy, training deep learning algorithms, evaluating water sources, assessing risks related to glacial lakes, and understanding the interactions between glaciers and lakes.