Introducing the Ultimate ComfyUI Tutorial Series: Master AI Image Workflows Like a Pro

Are you ready to dive into the world of ComfyUI, a powerful and versatile framework designed for AI-driven image workflows? Whether you’re a beginner or an advanced user, our SysOSX tutorial series provides step-by-step guidance to help you master everything from the basics to advanced techniques. With over 30 detailed articles, this series covers topics ranging from installation and … Read more

C23: Fine-Tuning ControlNet Parameters in ComfyUI

Introduction In our previous article, we explored how ControlNet can be used in ComfyUI workflows to direct image composition using external inputs like line drawings. While this approach allowed us to achieve precise object placement, the results were not always satisfactory due to the default ControlNet parameters. For example, the generated dog followed the contours of a simple … Read more

C22: Mastering Composition with ControlNet in ComfyUI: A Step-by-Step Guide

Introduction One of the common challenges in AI image generation is achieving precise art direction. While prompts can guide the general style and content of an image, they often fall short when it comes to controlling specific composition details, such as screen direction or object placement. In this article, we’ll explore how ControlNet can be used in ComfyUI workflows to overcome … Read more

C21: Mastering Image-to-Image Prompting and CFG Scale in ComfyUI

Introduction In our previous article, “Image-to-Image Transformation in ComfyUI”, we explored the fundamentals of building an image-to-image workflow. We discussed how latent space diffusion enables creative transformations while preserving essential elements of the input image. If you’re new to ComfyUI or image-to-image workflows, we recommend reading that article first to understand the basics. In this follow-up … Read more

C20: Mastering Image-to-Image Transformation in ComfyUI

Introduction Image-to-image transformation is a powerful technique used in AI-driven generative models to modify or enhance images by converting them into a latent space and applying diffusion processes. Unlike starting from noise, this approach allows users to work with existing images, enabling transformations that respect the original content while incorporating stylistic changes. This article explains how … Read more

C17: Workflow for Stable Diffusion 3.5: A Comprehensive Guide

Stable Diffusion 3.5 is the latest iteration in AI image generation technology, offering enhanced performance, better prompt understanding, and compatibility with systems that have limited video RAM. With advancements in model architecture and text encoders, this version enables creators to produce high-quality images quickly and efficiently. This guide provides an in-depth overview of Stable Diffusion … Read more

C14: Daisy-Chaining Samplers for Enhanced Image Refinement in Stable Diffusion/ComfyUI

Stable Diffusion has revolutionized image generation by operating in the latent space rather than the pixel space, providing users with unparalleled flexibility and control. One particularly powerful technique enabled by this framework is daisy-chaining samplers, a method that allows you to refine image fidelity and prompt adherence while preserving the desired composition. In this article, we’ll … Read more

C12: How to Upscale Images for Higher Resolution Using ComfyUI, step by step guide

Introduction Upscale images is an essential step in improving their resolution for print, web, or other applications. AI image generation tools like Stable Diffusion and ComfyUI typically produce images with resolutions around 1024 x 1024 pixels (1 megapixel). However, for high-definition (HD) and ultra-high-definition (4K) purposes, higher resolutions are required—HD images are around 2 megapixels, while 4K images are … Read more

C11: Mastering Inference Steps and CFG Scale in AI Image Generation

When working with AI-powered image generation tools like ComfyUI, understanding inference steps and CFG (classifier-free guidance) scale is essential for producing high-quality results. In this article, we’ll explore how these parameters affect image generation and how to adjust them to achieve the best outcomes. Understanding Inference Steps Inference steps, also known as sampling steps, define … Read more

C09: Avoiding Prompting Pitfalls: Best Practices for Writing Effective Prompts in AI Image Generation

Crafting effective prompts is essential for generating high-quality images in AI systems like Stable Diffusion, which rely on models such as CLIP (Contrastive Language–Image Pretraining). However, understanding the limitations of CLIP and avoiding common mistakes can significantly improve your results. This guide outlines key pitfalls to avoid and provides actionable strategies for writing better prompts. … Read more