MODEL TRAINING METHOD, AND IMAGE QUALITY EVALUATION METHOD AND APPARATUS

摘要

A model training method, and an image quality evaluation method and apparatus. The training method comprises: acquiring a real image sample set, wherein the real image sample set comprises a plurality of real image samples (101); performing iterative training on a pre-built generative adversarial network by using the real image sample set, and collecting a plurality of pseudo image sample sets that are respectively generated within a plurality of rounds of iteration by a generative network in the generative adversarial network (102); generating a first training sample library composed of the real image sample set and the plurality of pseudo image sample sets, and automatically categorizing and labeling each first training sample of the first training sample library according to a plurality of preset image quality levels to obtain the first training sample library (103); and training a preset multi-classification network by using the first training sample library so as to obtain an image quality evaluation model (104). By using the foregoing method, only a small number of clear real image samples need to be collected to generate a large number of pseudo image samples of different quality levels, and automatic labeling reduces manual costs while improving the quality of data labeling, so that the image quality evaluation model is trained at a lower cost.