Web Reference: Sep 18, 2024 ยท In Stable Diffusion, samplers guide the process of turning noise into an image over multiple steps. The sampler controls the diffusion processโhow each image layer is iteratively improved, transitioning from a random noise field to something recognizable and detailed. To produce an image, Stable Diffusion first generates a completely random image in the latent space. The noise predictor then estimates the noise of the image. The predicted noiseis subtracted from the image. This process is repeated a dozen times. In the end, you get a clean image. This denoising process is called sampling because Stable Diffusion... There are a few different ways to measure convergence in Stable Diffusion. One common way is to use the loss function. The loss function measures the difference between the generated image and the target image. As the model converges, the loss function should gradually decrease.
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