Extensions/NBA-ComfyUINode
ComfyUI Extension

NBA-ComfyUINode

Version 1.2.1 - Dependency cleanup and archived LineSelector node

By enternalsaga·Created 10 months ago·Updated 10 months ago· 0
enternalsaga/NBA-ComfyUINode-public
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NBA-ComfyUINode

Version 1.2.1 - Dependency cleanup and archived LineSelector node

A comprehensive collection of custom nodes for ComfyUI, providing advanced image processing, workflow control, and utility functions to enhance your AI image generation workflows.

🚀 Features

  • Flow Control Nodes: Advanced workflow management with gates, branches, and state management
  • Image Processing: Specialized nodes for image manipulation, resizing, and enhancement
  • File Management: Advanced image loading, saving, and organization tools
  • Utility Nodes: Text processing, list management, and data conversion utilities
  • Hugging Face Integration: Direct integration with HF models for captioning and control
  • JavaScript Extensions: Enhanced UI components for better user experience

📦 Installation

Prerequisites

  • ComfyUI installed and running
  • Python 3.8 or higher
  • Required dependencies (see requirements.txt)

Installation Steps

  1. Clone the repository:

    git clone https://github.com/enternalsaga/NBA-ComfyUINode.git
cd NBA-ComfyUINode

  2. Copy to ComfyUI custom_nodes directory:

    cp -r NBA-ComfyUINode /path/to/ComfyUI/custom_nodes/

  3. Install dependencies:

    pip install -r requirements.txt

  4. Restart ComfyUI and the nodes will be automatically discovered and loaded.

🧩 Available Nodes

Flow Control Nodes

  • NBA Flow Any Gate: Conditional workflow execution based on any input
  • NBA Flow Branch: Multi-path workflow branching
  • NBA Flow Gate: Simple conditional execution
  • NBA Flow Multi Gate: Multiple condition evaluation
  • NBA Flow Sequence: Sequential workflow execution
  • NBA Flow Set State: State management for workflows
  • NBA Flow Any Checker: Input validation and checking

Image Processing Nodes

  • NBA Match Size: Resize images to match dimensions
  • NBA Remove Banding Artifacts: Eliminate banding in generated images
  • NBA Resize By Pixel Ratio: Proportional image resizing
  • NBA Scale To Pixels: Precise pixel-based scaling
  • NBA Colorize Depthmap: Convert depth maps to colored images
  • NBA Kontext Diff Merge: Advanced image merging with context

File Management Nodes

  • NBA Image Output: Advanced image saving with metadata
  • NBA Image Output Adv: Enhanced image output with additional features
  • NBA Load Image: Flexible image loading from various sources
  • NBA Load Image Input: Advanced image input with folder support
  • NBA Load Image Input Advanced: Enhanced image loading with subfolder support
  • NBA Load Image From Folder: Batch image loading from directories
  • NBA Save Image To Path: Direct image saving to specified paths
  • NBA Extract File Names: Extract and process filenames
  • NBA List Image Files: List and process image files
  • NBA List Text Files: List and process text files

Utility Nodes

  • NBA Any To Any: Universal data type conversion
  • NBA Text Split By Delimiter: Split/truncate by characters, words, or delimiters with forward/backward slicing, start position, and smart numbering removal
  • NBA List Info: Information extraction from lists
  • NBA Image Filename Info: Extract metadata from image filenames
  • NBA Process Tags: Tag processing and management
  • NBA Save Text File To Path: Text file saving utilities
  • NBA Sym Link: Symbolic link creation utilities

Hugging Face Integration

  • NBA Hf Zen Ctrl: Zen control model integration
  • NBA Hf Joy Caption: Joy captioning model
  • NBA Hf Ic Light V2: IC Light V2 model integration
  • NBA Hf Image2Body: Image to body conversion

Advanced Nodes

  • NBA Kontext Inpainting Conditioning: Advanced inpainting with context
  • NBA Multi Slider: Multi-value slider interface
  • NBA Float Ramp: Float value ramping utilities
  • NBA Dual Condition: Dual condition evaluation
  • NBA OLM Dragcrop: Drag and crop functionality

🎯 Usage Examples

Basic Image Processing Workflow

# Load image and resize
image = LoadImageInput(image_path="input.jpg")
resized = MatchSize(image=image, target_size=(512, 512))

# Process and save
processed = RemoveBandingArtifacts(image=resized)
output = ImageOutput(
    image=processed,
    output_path="./output/",
    save_prefix="processed",
    file_type="png"
)

Advanced Flow Control

# Conditional processing based on image size
checker = FlowAnyChecker(condition="image_width > 512")
gate = FlowAnyGate(
    condition=checker,
    true_branch=ScaleToPixels(image=image, target_pixels=262144),
    false_branch=image
)

Batch Processing with Organization

# Load multiple images from folder
images = LoadImageFromFolder(
    folder_path="./input/",
    file_types=["jpg", "png"]
)

# Process each image with organized output
for image in images:
    processed = RemoveBandingArtifacts(image=image)
    ImageOutput(
        image=processed,
        output_path="./output/%date:yyyy-MM-dd%/",
        save_prefix="batch_%date:HHmmss%",
        prefix_sub="processed",
        number_padding=4
    )

📁 Project Structure

NBA-ComfyUINode/
├── __init__.py              # Auto-discovery and registration
├── nodes/                   # All node implementations
│   ├── Flow*.py            # Flow control nodes
│   ├── Image*.py           # Image processing nodes
│   ├── Load*.py            # Image loading nodes
│   ├── Hf*.py              # Hugging Face integration
│   └── *.py                # Utility and other nodes
├── js/                     # JavaScript UI extensions
│   ├── *.js               # UI enhancement scripts
│   └── *.js.backup        # Backup files
├── examples/               # Usage examples and tutorials
│   └── usage_examples.py  # Comprehensive examples
├── web/                    # Web assets
├── lists/                  # Configuration lists
├── requirements.txt        # Python dependencies
└── README.md              # This file

🔧 Configuration

Node Auto-Discovery

The project uses automatic node discovery. Simply place your node classes in the nodes/ directory with the required attributes:

  • INPUT_TYPES: Define input parameters
  • RETURN_TYPES: Define output types
  • FUNCTION: Main processing function
  • CATEGORY: Node category for organization

JavaScript Extensions

Custom UI components are automatically loaded from the js/ directory. These enhance the user experience with:

  • Dynamic widgets
  • Advanced input controls
  • Drag-and-drop functionality
  • Real-time preview updates

🤝 Contributing

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Add your nodes to the nodes/ directory
  4. Add any JavaScript extensions to the js/ directory
  5. Update documentation and examples
  6. Commit your changes (git commit -m 'Add amazing feature')
  7. Push to the branch (git push origin feature/amazing-feature)
  8. Open a Pull Request

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

  • ComfyUI community for the excellent framework
  • Hugging Face for model integrations
  • All contributors who have helped improve these nodes

📞 Support

  • Issues: Report bugs and request features on GitHub
  • Discussions: Join community discussions for help and ideas
  • Documentation: Check the examples folder for detailed usage examples

Happy Node Building! 🎨