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Terminology
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This page gives you an overview of the terminology and abbreviations you might see in relation with ESRGAN.
General AI Terms
- GAN: Generative Adversarial Network
- An AI network that works by having a generator that tries to fool the discriminator. During training, the generator tries to generate realistic fakes of the training data, while the discriminator tries to tell which images are real and which are fake. Both of these two elements keep improving each other during training.
- Iterations: The amount of times your AI model updates itself with new data. Multiply with your batch size to get the total amount of images that have been processed.
- For example: If your model is at 10,000 iterations with batch size 4, it has seen 40,000 training images.
- Epochs: How often your entire dataset was processed. Important: One epoch does not mean your model has finished training! It can still improve, even after seeing the same data many times.
ESRGAN Specific Terms
- ESRGAN: Enhanced Super Resolution Generative Adversarial Network (or just Enhanced SRGAN, as SRGAN has already existed before it)
- BasicSR: The training toolkit for ESRGAN, basically just a re-brand
ESRGAN Training (BasicSR) Specific Terms
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