🥳 Thanks for using ComfyUI-Easy-Use
An efficiency custom nodes package
Simple text to image generation with Comfyui-Easy-Use nodes
ComfyUI-Easy-Use is an efficiency custom nodes integration package, which is extended on the basis of TinyTerraNodes. It has been integrated and optimized for many popular awesome custom nodes to achieve the purpose of faster and more convenient use of ComfyUI. While ensuring the degree of freedom, it restores the ultimate smooth image production experience that belongs to Stable Diffusion.
How to installation
Learn how to install ComfyUI-Easy-Use
Use Hotkeys
Some hotkeys to make your workflow
Swaps Nodes
Swap same category of nodes
Nodes Intro
Learn more about the nodes
🧐 What’s different about easy pipeline and native flow?
The pipeline here is different from the diffusers pipeline. easyuse’s pipeline is just an integration optimisation of the native nodes, using the same comfy native architecture.
1️⃣ Text To Image
In general,using method2 is more conducive to make workflows.
EasyLoader: Load the checkpoint model and clip encoding the text and set an empty latent. you also using load lora models and set clip skip in here. See all loaders nodes
PreSampling: This is a separate node from ksampler, which only does the configuration of the sampling parameters and does not sample. See all preSampling nodes
EasyKSampler: Only sampling and vae decoding are performed, and the sampling parameters are passed in from the pre-sampling node, making it easier to observe the denoising process. See all kSampler nodes
2️⃣ Image To Image
pre-sampling converts the pixel image passed in by load-image node into a latent space image.
3️⃣ Using with Controlnet
🧐How to unpacking pipe and combining pipe?
Combining into a pipe
You can use the easy pipeIn to merge some regular types into a pipe
Unpacking from a pipe
Use the easy pipeOut to output some of the regular types of output
Modify the pipe
Use the easy pipeEdit or easy pipeEditPrompt to modify the pipe
Typically, it is used to preserve some of the parameters after the first diffusion. For the second diffusion we only need to modify some parameters and change the pre-sampling parameters.