![]() The Generator transforms the input image to get the output image. The network is made up of two main pieces, the Generator, and the Discriminator. Pix2pix uses a conditional generative adversarial network (cGAN) to learn a function to map from an input image to an output image. Data were split into train and test randomly. Edges ->shoes 50k training images from UT Zappos50K dataset trained for 15 epochs, batch size 4.Tested on a subset of Imagenet validation set. BW-> color 1.2 million training images (Imagenet training set ), trained for 6 epochs, batch size 4, with only mirroring, no random jitter.Data was then split into train and test set (with a buffer region added to ensure that no training pixel appeared in the test set). Maps aerial photograph 1096 training images scraped from Google Maps, trained for 200 epochs, batch size 1. ![]() Validation set has been used for testing. ![]() The dataset is thus an order of magnitude larger than similar previous attempts)datasets with 2975 training images from the Cityscapes training set trained for 200 epochs, with random jitter and mirroring.
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