Generative adversarial network-based grayscale picture colorizing method
A colorization and network technology, applied in the field of deep learning and image generation, can solve the problems of easy loss of details and complex operation of images
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[0066] The image generation method combining DiscoGAN, Progressive Growing GAN, WGAN and CGAN is explained in detail below in conjunction with the accompanying drawings.
[0067] The gray-scale image colorization system of the present invention should include the following parts: sample data collection, sample image preprocessing, generation of confrontation network model establishment, network training and testing and adjustment of hyperparameters. The main steps included in the present invention include: collecting pictures and preprocessing, inputting the pictures to generate a confrontation network, training the survival confrontation network, adjusting the hyperparameters of the generation confrontation network and repeating training to obtain the final model, such as figure 1 Shown. Its system structure is like figure 2 Shown. The sample data collection link is responsible for collecting enough gray-scale pictures and color pictures that contain rich detailed information ...
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