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    KNX Tagger - v1.0
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    KNX-Tagger

    Discord Support us on Ko-fi


    Image tagging tool using Google's Gemini API for Stable Diffusion/Flux LoRA training.

    All issues/feature requests need to be handled on the Github:

    https://github.com/Ktiseos-Nyx/Knx-Tagger

    Requirements

    • Python 3.10+

    • PyQt6

    • Google Gemini API key (free tier available)

    • Supported models: gemini-2.5-flash, gemini-2.5-pro, gemini-flash-latest

    Features

    • Multiple Tagging Modes:

      • Danbooru-style tags (comma-separated)

      • Natural language captions

      • Custom prompts with your own instructions

    • Bias Modes for Focused Tagging:

      • Character focus: Emphasize character details, expressions, poses

      • Style focus: Highlight artistic technique, composition, lighting

      • Realism focus: Detailed environmental and photographic elements

      • Environment focus: Scene context, settings, atmosphere

    • Flexible Workflow:

      • Test mode: Preview tags on 10 images first

      • Batch mode: Process entire folders

      • Skip already-tagged images

      • Tag filtering and exclusion

      • Activation tag prepending (for LoRA triggers)

    • Kohya-Compatible Output:

      • .txt or .caption files alongside images

      • Perfect for SD/Flux training workflows

    • Theme System:

      • 213+ pre-made themes from KNX collection

      • Support for qt-material, unreal-stylesheet, and custom QSS

      • Searchable theme selector dialog

      • Complete skinning documentation for creating custom themes

      • Guides for Krita, GIMP, Photoshop, Affinity, and Illustrator

    • Cost Tracking:

      • Estimates API costs before processing

      • Uses efficient gemini-2.5-flash model

      • Concurrent processing (10 workers) for speed

    Installation

    Recommended: Install as Package (with knx-tagger command)

    # Clone the repo
    git clone https://github.com/Ktiseos-Nyx/Knx-Tagger.git
    cd Knx-Tagger
    
    # Install in editable mode
    pip install -e .
    
    # Now you can run from anywhere:
    knx-tagger

    Alternative 1: Using venv (Standard)

    # Create virtual environment
    python -m venv venv
    
    # Activate it
    # On macOS/Linux (bash/zsh):
    source venv/bin/activate
    
    # On macOS/Linux (fish shell):
    source venv/bin/activate.fish
    
    # On Windows:
    venv\Scripts\activate
    
    # Install as package
    pip install -e .

    Alternative 2: Using uv (Faster, Optional)

    uv is a blazing-fast Python package installer - totally optional but recommended if you want speed!

    # Install uv (if you don't have it)
    curl -LsSf https://astral.sh/uv/install.sh | sh
    
    # Create venv and install in one go
    uv venv
    source .venv/bin/activate  # or .venv/bin/activate.fish for fish shell
    uv pip install -e .

    Get Your API Key

    1. Get a Gemini API key:

    2. Configure API key (optional):

      cp .env.example .env
      # Edit .env and add your key

      Or just enter it when prompted on first run - the app will offer to save it for you!

    Usage

    If Installed as Package:

    knx-tagger

    Or Run Directly:

    python main.py
    # or
    python -m knx_tagger

    Note: You may see a harmless warning like ALTS creds ignored. Not running on GCP... in the console - this is just Google's library noting you're not on Google Cloud Platform. It's safe to ignore; the app uses API key authentication which is working correctly.

    Workflow:

    1. Select folder containing images (JPEG, PNG, WebP)

    2. Choose tagging mode:

      • Danbooru: Creative, descriptive tags

      • Natural: Full sentence captions

      • Custom: Write your own prompt

    3. Test first: Run on 10 images, review quality

    4. Batch process: Tag entire folder after you're satisfied

    5. Output: .txt or .caption files alongside each image

    Themes

    KNX-Tagger includes 213+ pre-made themes! Access them via 🎨 Themes in the top menu.

    Browsing Themes

    • Click 🎨 Themes to open the theme selector

    • Browse by category or search by name

    • Double-click to apply a theme instantly

    • Current theme is highlighted

    Creating Custom Themes

    Want to make your own Winamp-style skins? Check out the documentation:

    • knx_tagger/themes/SKINNING_GUIDE.md - Complete QSS styling reference

    • knx_tagger/themes/WIDGET_LAYOUT_REFERENCE.md - Widget positions for template creation

    • knx_tagger/themes/SOFTWARE_SPECIFIC_GUIDES.md - Tutorials for Krita, GIMP, Photoshop, etc.

    Theme Categories

    • AI themes (ChatGPT, Claude, Gemini, Llama)

    • Retro UI (MS-DOS, Windows XP, Mac OS 9, Linux distros)

    • Games (Genshin Impact, Pokemon, Final Fantasy, Playstation)

    • Aesthetic (Vaporwave, Kawaii, Neon, Sunset gradients)

    • Food & Brands (Taco Bell, Domino's, Coca-Cola)

    • Pop Culture (MLP, Deadpool, X-Men, VTubers)

    • And many more cursed options!

    Tips

    • Danbooru mode is great for inventing new tags beyond standard booru sets

    • Test before batch to ensure prompt quality

    • Skip existing prevents re-tagging already processed images

    • Cost estimates are approximate - actual costs may vary

    • Bias modes help focus on specific aspects (character, style, environment, realism)

    • Exclude tags can filter out unwanted terms from AI-generated tags

    • Some themes may look janky - they were designed for Dataset-Tools originally!

    Extending

    KNX-Tagger is designed to be modular:

    • knx_tagger/core/gemini_tagger.py - API integration

    • knx_tagger/utils/file_handler.py - File operations

    • knx_tagger/ui/main_window.py - PyQt6 interface

    Easy to integrate into larger applications or use as a library.

    License

    MIT

    Description

    Other
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    Details

    Downloads
    13
    Platform
    CivitAI
    Platform Status
    Deleted
    Created
    10/20/2025
    Updated
    4/27/2026
    Deleted
    10/27/2025

    Files

    knxTagger_v10.zip

    Mirrors

    CivitAI (1 mirrors)