/ComfyUI-noEmbryo

Some useful nodes for ComyUI

Primary LanguagePythonMIT LicenseMIT

noEmbryo Nodes

A diverse set of nodes for ComfyUI.

You can access them through "Add node > noEmbryo" submenu.

made-with-python License: MIT


PromptTermList (1-6)

These are some nodes that help with the creation of Prompts inside ComfyUI.

Demo workflow

Usage

Every one of the 6 nodes have a different json file that stores its Prompt Terms in "label"/"value" pairs.
The "label" part is what we see at the node's dropdown menu, and the "value" part is what it produces at its Term output when we run a generation job.

These json files are located inside the TermLists directory, in the node's folder.
There are two ways to add a new term.

  • From within ComfyUI:

    • Connect a text box to the node's text input.
    • Write the "label"/"value" part in the box using the following format:
    label=Descriptive text
    value=masterpiece, artful and cozy
    
    • Enable the store_input switch.
    • Run a generation job.
    • Refresh the page.
  • Manually:

    • Just open the json file and add/remove/change entries.

    Of course we must be very careful with this, to keep the json format of labels/values (with the appropriate commas), otherwise the file will not be parsed.

This text input is also useful if we want to manually add something after our term, or as the only term if we select the None label of the dropdown.
The strength value is changing the impact of the term by using the parenthesis format like this: (a great term:1.3)

We can delete a term by sending an empty value to the text input like this:

label=The label to be deleted
value=

Resolution Scale

Demo workflow A simple node that outputs the resolution of an image using the dimensions of an input image or some custom user-defined dimensions, using a Scale Factor.

If there is an input image connected, setting either width or height to 0 will use the other dimension to scale the image (but always multiple of 4).


Regex Text Chopper

Demo workflow A node that "chops" a text using a regular expression and outputs the chopped parts of the text.


Installation