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This article discusses the use of a real-time crop image integrated information acquisition system to collect data for an experiment. The system includes a high-temperature and high-humidity-resistant camera, a dandelion router, and a TCP data transmission module. The experiment uses an Ubuntu operating system and a PyTorch deep-learning framework to verify the effectiveness of the SM-CycleGAN model. The model is evaluated using objective evaluation indexes and compared to other methods.