April 2020
Intermediate to advanced
438 pages
12h 2m
English
Content preview from Python Image Processing Cookbook
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How it works...
The generator (net) generates new image instances, while the discriminator evaluates them for authenticity.
The adversarial training focuses on the system's weaknesses, forcing each other to improve over time (the generator gets better at generating realistic images and the discriminator gets better at differentiating the real from the fake images), until the fake images generated by the generator become indistinguishable from the real images and the discriminator can't differentiate them (at this point, the generator has learned how to generate a good image).
The discriminator is just a binary classifier that gets two batches of images as input (from real training data and from the generator) and figures out whether an image ...
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