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Dataset Tools for Imaging and Captioning - v0.55

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Jan 21, 2025
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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:

Git:

Launching the Application

  1. Open your terminal shell console of choice. (ie: powershell, cmd, zsh, bash, etc.)

  2. 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 .

  3. 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.

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