Product Design Process Based on GANs Model

Abstract

In order to solve the difficulties and shortcomings when users use images to describe their requirements, a product design process based on GANs model is proposed. Build a generation countermeasure network and train an intelligent image generation model, so that the computer can quickly generate design cases, and can artificially control the generation results to realize the establishment of case base and the adjustment of image content. In addition, an image artistic style similarity measurement model is proposed to calculate the style differences between images. The results show that the measurement results of this method are consistent with the subjective evaluation of designers. The statistical results of 30 groups of data show that the probability that this method is consistent with the designer’s evaluation results is 90%. So far, in the above performance evaluation experiments, the similarity measurement results of the same/different style works are obviously different, which conforms to the rules of style similarity. In the task of ranking style similarity, this model is 90% consistent with the ranking results of designers. Conclusion: The model is effective in performance evaluation experiments, which lays a foundation for developing style-based design case retrieval and recommendation.