Dataset-Tools: A Simple Dataset Viewer for AI Art

Dataset-Tools is a desktop application designed to help users browse and manage their image and text datasets, particularly those used with AI art generation tools like Stable Diffusion. Developed using PyQt6, it provides a simple and intuitive graphical interface for browsing images, viewing metadata, and examining associated text prompts. This project is inspired by tools within the AI art community (receyuki/stable-diffusion-prompt-reader) and aims to empower users in improving their dataset curation workflow.

Daily updates are here: https://github.com/Ktiseos-Nyx/Dataset-Tools

How to Use Dataset-Tools

Requirements

To run the program, you will need the following software:

Python:

Python.org or Try uv

Git:

Launching the Application

Open your terminal shell console of choice. (ie: powershell, cmd, zsh, bash, etc.)
git clone or download the Dataset-Tools repository from GitHub.
```
git clone https://github.com/Ktiseos-Nyx/Dataset-Tools.git
```
Move into Dataset-Tools folder and pip install the required dependencies:
```
cd Dataset-Tools
pip install .
```
NOTE: uv users
```
cd Dataset-Tools
uv pip install .
```
Run the application with dataset-tools command:
```
dataset-tools
```

You're in!

User Interface Overview

The application window has the following main components:

Current Folder: Displays the path of the currently loaded folder.
Open Folder: A button to select a folder containing images and text files.
Image List: Displays a list of images and text files found in the selected folder.
Image Preview: An area to display a selected image.
Metadata Box: A text area to display the extracted metadata from the selected image (including Stable Diffusion prompt, settings, etc.).
Prompt Text: A text label to display the prompt from the selected image.
Text File Content Area: A text area to display the content of any associated text files.

Managing Images and Text

Selecting Images: Click on an image or text file in the list to display its preview, metadata, and associated text content.
Viewing Metadata: Metadata associated with the selected image is displayed on the text area, such as steps, samplers, seeds, and more.
Viewing Text: The content of any text file associated with the selected image is displayed on the text box.

Key Features

Graphical User Interface (GUI): Built with PyQt6 for a modern and cross-platform experience.
Image Previews: Quickly view images in a dedicated preview area.
Metadata Extraction: Extract and display relevant metadata from PNG image files, especially those generated from Stable Diffusion.
Text Viewing: Display the content of text files.
Clear Layout: A simple and intuitive layout, with list view on the left, and preview on the right.

Future Developments

Thumbnail Generation: Implement thumbnails for faster browsing.
JPEG Metadata: Add support for extracting metadata from JPEG files.
Themes: Introduce customizable themes for appearance.
Filtering/Sorting: Options to filter and sort files.
Better User Experience: Test on different operating systems and screen resolutions to optimize user experience.
Video Tutorials: Create video tutorials to show users how to use the program.
Text Tutorials: Create detailed tutorials in text and image to show the user how to use the program.