AI Image Processing Toolkit

A collection of specialized scripts for AI image processing, dataset preparation, and model training workflows.

🛠️ Scripts Overview

WDV3 (Waifu Diffusion V3 Tagger)

An image tagging script using the WD V3 tagger models. Supports multiple model architectures (ViT, SwinV2, ConvNext) and can process both single images and directories recursively.

Features

Multiple model architecture support
Batch processing capabilities
Adjustable confidence thresholds
CUDA acceleration with FP16 support
JXL image format support

Training Functions (train_functions.zsh)

A set of ZSH functions for managing AI model training workflows:

Script execution management
Training variable setup
Git repository state tracking
Output directory management
Automatic cleanup of empty outputs

Git Wrapper (git-wrapper.zsh)

Enhanced Git functionality for dataset management:

Automatic submodule handling
LFS integration for JXL files
Dataset-specific Git attributes management

Check4sig (check4sig.zsh)

Dataset caption file watermark detection utility:

Scans .caption files for watermark-related text
Batch processing support
Interactive editing with nvim
Recursive directory scanning

Gallery-dl Wrapper (gallery-dl.zsh)

Directory-aware wrapper for gallery-dl:

Automatically changes to ~/datasets directory
Maintains consistent download locations
Preserves original command functionality

JoyCaption (joy)

Advanced image captioning system using CLIP and LLM:

Multiple caption styles (descriptive, training prompts, art critic, etc.)
Custom image adapters
Tag-based caption generation
Batch processing support

PNG to MP4 Converter (png2mp4)

Training progress visualization tool:

Converts PNG sequences to MP4
Customizable frame rates and durations
Step counter overlay support
Multiple sample handling

XY Plot Generator (xyplot)

Image comparison grid generator:

Supports multiple image formats
Customizable grid layouts
Optional row/column labels
Automatic image padding and alignment

Caption Concatenator (concat_captions)

Utility for combining multiple caption files:

Merges .caption and .tags files
Maintains original image associations
Batch processing support
Error handling for missing files

🚀 Installation

Clone the repository: (optional)

git clone https://huggingface.co/k4d3/toolkit

Add the repository to your PATH: (optional)

export PATH="$PATH:~/path/to/toolkit"

Add the .zshrc to your shell: (optional and you will need to make changes to it)

source ~/path/to/toolkit/.zshrc
nano ~/.zshrc

📝 Requirements

miniconda with the environment set up for training with sd-scripts, timm, etc
ZSH shell (optional)
CUDA-capable GPU (recommended)
Required Python packages:
- torch
- transformers
- pillow
- pillow-jxl
- opencv-python
- numpy
- and a lot more

🔧 Usage

Each script can be used independently or as part of a workflow. Here are some common usage examples:

JoyCaption

joy --feed-from-tags=10 --custom_prompt="Write a very long descriptive caption for this image in a formal tone. Do not mention feelings and emotions evoked by the image." .

png2mp4

png2mp4 --repeat 16

inject_to_txt

inject_to_txt 1_honovy "honovy"

replace_comma_with_keep_tags_txt

replace_comma_with_keep_tags_txt 1 1_honovy

📦 Directory Structure

~/
├── datasets/
├── output_dir/
├── models/
├── toolkit/

📄 License

WTFPL - Do what the fuck you want with it.

The included data and models are copyrighted by their respective owners with their own licenses.

🤝 Contributing

Contributions are welcome! For major changes, please open an issue first to discuss what you would like to change.

📚 Documentation

If the documentation of a script is missing, ask a language model about it.