Abstract: Aiming at the problems of insufficient training data, low data quality and inconsistent evaluation standards in the training and evaluation process of the existing image automatic recognition model of the railway vehicle trackside image detection system, this paper studied the training and verification platform for for railway vehicle monitoring image recognition model, designed methods such as unified access to fault image data, expert calibration data formation, automatic recognition model access, training, comparative evaluation, etc., provided the ability of standard training data, unified evaluation, verification, and management services for fault image automatic recognition models. The practices show that this platform implements centralized collection and unified management of vehicle fault image data, provides strong support for the development of automatic recognition technology for railway vehicle monitoring images.