tutorials/basic/text-to-image

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tutorials/basic/text-to-image

This guide will help you understand the concept of text-to-image in AI art generation and complete a text-to-image workflow in ComfyUI

https://docs.comfy.org/tutorials/basic/text-to-image

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This tutorial is very comprehensive, but it seems to need updating.like this

Here’s an explanation of the KSampler node parameters:
Parameter Name Description Function
model Diffusion model used for denoising Determines the style and quality of generated images
positive Positive prompt condition encoding Guides generation to include specified elements
negative Negative prompt condition encoding Suppresses unwanted content
latent_image Latent space image to be denoised Serves as the input carrier for noise initialization
seed Random seed for noise generation Controls generation randomness
control_after_generate Seed control mode after generation Determines seed variation pattern in batch generation
steps Number of denoising iterations More steps mean finer details but longer processing time
cfg Classifier-free guidance scale Controls prompt constraint strength (too high leads to overfitting)
sampler_name Sampling algorithm name Determines the mathematical method for denoising path
scheduler Scheduler type Controls noise decay rate and step size allocation
denoise Denoising strength coefficient Controls noise strength added to latent space, 0.0 preserves original input features, 1.0 is complete noise