sn0w-scripts

A collection of nodes and improvements created for general ease and testing loras. These are just nodes I made and found useful, they should work with most other nodes. Most nodes that take in a prompt are made with booru tags in mind and might not work as expected with other prompts.

Get Started

Install

1. Install ComfyUi.
2. Clone this repo into custom_nodes:

   git clone https://github.com/sn0w12/ComfyUI-Sn0w-Scripts
   

3. Start up ComfyUI.

Important Note

Many of the nodes require these paths to be in your extra_model_paths.yaml (with your real directories of course).

• loras_xl: C:/path/XL
• loras_15: C:/path/1.5

Nodes

Find Resolution

An easy way to select a width and height.

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• Enable flip if you want to swap the resolutions

Lora Selector

Automatically selects X amount of loras between two numbers.

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• Loras have to be formatted like the default kohya_ss outputs. (lora_name-000001)
• Select the first lora.
• Select the number of the highest lora you want to test.
• Select the amount of loras you want to test.
• Outputs list of loras like this: <lora:name:strength>
• Add default generation adds an extra "nothing" at the end of the list, used in Lora Tester to generate an image without the lora.

Lora Tester (XL)

Automatically generates X amount of images with provided loras.

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• I recommend making lora_info and add_default_generation inputs and using the outputs from the Lora Selector.
• Takes normal KSampler input but takes positive and negative inputs as text.
• Outputs a batch of images.

Character Selector

Outputs a character name and prompt.

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• Loads characters.json and outputs prompt based on it.
• Note: Currently very small list, feel free to add your own to the json file.

Prompt Combine

Combines multiple strings with a specified separator and optionally simplifies the result by removing redundant or incompatible tags.

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• Inputs: Accepts up to four strings and a separator to combine them. An optional boolean simplify flag determines whether to simplify the combined string by removing redundant or incompatible tags based on predefined categories.
• Simplification Process: If enabled, the simplification process identifies and removes redundant tags (e.g., when a tag is fully encompassed by another, more descriptive tag) and tags incompatible with the identified subject's facing direction.
• Outputs: Returns a combined string (PROMPT) with or without simplification, and a string (REMOVED_TAGS) listing tags that were removed during the simplification process.

Lora Stacker

Outputs a list of loras for Lora Tester. Does not load any loras by itself.

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• Basically Lora Selector but manual.
• Specifically for the lora testers.

Load Lora XL/1.5

Normal load lora but from another folder.

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• Add these to your extra_model_paths.yaml (for example):
• loras_xl: C:/path/XL
• loras_15: C:/path/1.5

Load Lora Character

Finds and applies the closest matching Lora model to a character based on name similarity.

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• The process begins by cleaning the input character string for comparison. It then searches a JSON file for a matching character name. If a match is found, it proceeds to select the appropriate folder based on the xl boolean flag.
• To find the closest Lora model, it calculates the Levenshtein distance between the character name (in full and in parts) and the filenames of available Lora models. This ensures a case-insensitive match with the best possible model.
• If no lora is found it just returns the input model and the workflow can continue.

Load Lora Concept

Dynamically applies Lora models based on similarity to a provided prompt.

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• Functionality: This node processes a given prompt to identify and apply the most similar Lora models of the tags found in the prompt.
• Input Processing: The prompt is split into parts using a specified separator, and each part is cleaned to remove unnecessary characters and normalized for comparison.
• Similarity Matching: For each part of the prompt, the node calculates a similarity ratio against available Lora model filenames. Models with a similarity ratio above a threshold (85%) are selected. Each selected Lora model is applied to the input model and clip.
• Outputs: Returns the model and clip, potentially modified by multiple Lora models.
• Note: You need the loras you want to be selected to be in a folder called concept for this to work, they also need to be seperated into XL and 1.5 like stated in the Important Note.

Get Font Size Node

Estimates the optimal font size for text to fit within an image based on Lora information.

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• This node takes an image and a string, estimating the best font size to ensure that the longest piece of the string fits within the image. The approach considers the image's width and the length of the text to find a size that balances visibility and fit.

Example Workflows

Lora Tester

Note: Uses ImagesGrid for making the actual grid from the image output.