ComfyUI Extension: KarmaNodes

Authored by KarmaSwint

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Custom cycling KSampler with progressive upscale and more. Professional post-processing nodes.

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    README

    ComfyUI-KarmaNodes

    Advanced KSampler node and professional post-processing tools for ComfyUI with multi-cycle sampling, progressive upscaling, and cinematic enhancement capabilities.

    Overview

    ComfyUI-KarmaNodes provides a comprehensive suite of nodes for advanced image generation and post-processing:

    • Karma KSampler Cycle: Specialized KSampler that performs multiple sampling cycles with progressive upscaling between cycles, enabling high-quality, high-resolution image generation with better detail preservation
    • Karma Film Grain: Professional film grain simulation for authentic analog film texture and cinematic aesthetics
    • Karma Kolors: Advanced color grading and correction tools for professional-grade color enhancement

    Features

    🔄 Multi-Cycle Sampling

    • Progressive Upscaling: Automatically upscales images between sampling cycles
    • Configurable Cycles: Support for 2-12 sampling cycles
    • Dynamic Parameters: Adjust sampling parameters between cycles

    🎯 Advanced Sampling Control

    • Dual Model Support: Switch between primary and secondary models at specified cycles
    • Additive Conditioning: Blend additional positive/negative conditioning with strength scaling
    • Dynamic Denoise: Configurable denoise strength scaling with minimum threshold protection
    • Steps Scaling: Flexible steps adjustment with increment/decrement modes and threshold control
    • Threshold Management: Auto-calculated or manual threshold settings for precise control

    🔧 Upscaling Options

    • Basic Upscaling: High-quality image rescaling with multiple resampling methods
    • Model-Based Upscaling: Use dedicated upscale models for enhanced quality
    • Gradual Upscaling: Multi-step upscaling for smoother transitions
    • Configurable Resampling: Separate methods for image and latent space upscaling
    • VAE Compatibility: Ensures dimensions are VAE-compatible (divisible by 8)

    ✨ Post-Processing

    • Sharpening Filter: Optional unsharp mask filter between cycles
    • Film Grain Effects: Realistic analog film grain simulation
    • Color Grading: Professional color correction and enhancement
    • Tiled VAE Support: Handle large images with tiled VAE processing
    • Memory Management: Automatic device management for optimal performance

    Installation

    Method 1: ComfyUI Manager (Recommended)

    1. Install ComfyUI Manager
    2. Search for "KarmaNodes" in the manager
    3. Install and restart ComfyUI

    Method 2: Manual Installation

    1. Navigate to your ComfyUI custom nodes directory:

      cd ComfyUI/custom_nodes/

    2. Clone this repository:

      git clone https://github.com/karmaswint/ComfyUI-KarmaNodes.git

    3. Install dependencies:

      cd ComfyUI-KarmaNodes
pip install -r requirements.txt

    4. Restart ComfyUI

    Usage

    Basic Workflow

    1. Add the Node: Search for "Karma KSampler Cycle" in the node browser
    2. Connect Inputs:
      • Connect your model, VAE, and conditioning inputs
      • Provide an initial latent image
    3. Configure Parameters:
      • Set the number of cycles (2-12)
      • Configure upscale factor and method
      • Adjust denoise strengths
    4. Run: Execute the workflow

    Key Parameters

    Core Sampling

    • Steps: Number of sampling steps per cycle
    • Total Cycles: Number of upscaling/sampling cycles (2-12)
    • Starting Denoise: Denoise strength for the first cycle (0.0-1.0)
    • Cycle Denoise: Denoise strength for subsequent cycles (0.0-1.0)

    Denoise Scaling

    • Enable Denoise Scaling: Automatically adjust denoise strength between cycles
    • Denoise Min Threshold: Minimum denoise value to prevent going too low (0.01-1.0)

    Steps Scaling

    • Enable Steps Scaling: Automatically adjust sampling steps between cycles
    • Steps Scaling Value: Amount to adjust steps by each cycle (1-50)
    • Steps Adjustment Mode:
      • decrement: Reduce steps each cycle (for refinement)
      • increment: Increase steps each cycle (for more detail)
    • Steps Threshold Mode:
      • auto: Automatically calculate threshold based on initial steps
      • manual: Use a fixed threshold value
    • Steps Manual Threshold: Fixed threshold when using manual mode (1-200)

    Upscaling

    • Upscale Factor: Total upscaling factor to achieve
    • Upscale Method:
      • basic: High-quality image rescaling
      • model: Use dedicated upscale model (requires upscale_model input)
    • Scale Sampling: Resampling method for image upscaling (bilinear, bicubic, nearest, lanczos)
    • Latent Upscale Method: Resampling method for latent space upscaling (bilinear, bicubic, nearest, lanczos)
    • Enable Gradual Upscaling: Use multiple intermediate upscaling steps for smoother transitions
    • Gradual Upscale Steps: Number of intermediate steps when gradual upscaling is enabled (1-10)

    Advanced Features

    • Secondary Model: Optional model to switch to at specified cycle
    • Secondary Model Start Cycle: Cycle number to switch to secondary model (1-12)
    • Additive Conditioning: Additional positive/negative prompts with strength control
    • Sharpening: Apply unsharp mask filter between cycles

    Example Workflow

    [Model] → [Karma KSampler Cycle] → [VAE Decode] → [Save Image]
[VAE] ↗                        ↘ [VAE]
[Positive Conditioning] ↗
[Negative Conditioning] ↗
[Empty Latent] ↗

    Advanced Usage

    Dual Model Workflow

    Use different models for different phases of generation:

    1. Connect primary model for initial cycles
    2. Connect secondary model (optional)
    3. Set "Secondary Model Start Cycle" to switch models mid-process

    Additive Conditioning

    Enhance your prompts with additional conditioning:

    1. Connect main positive/negative conditioning
    2. Connect additive positive/negative conditioning (optional)
    3. Adjust strength values and scaling options

    High-Resolution Generation

    For very high-resolution outputs:

    1. Start with lower resolution latent
    2. Set higher upscale factor (2.0-4.0)
    3. Use more cycles (4-8) for gradual upscaling
    4. Enable tiled VAE for memory efficiency

    Steps Scaling Strategies

    Decrement Mode (Refinement Strategy)

    Best for progressive refinement with fewer steps in later cycles:

    • Use Case: When you want detailed initial generation, then refinement
    • Configuration:
      • Steps Adjustment Mode: decrement
      • Steps Scaling Value: 3-8 (moderate reduction)
      • Threshold Mode: auto (prevents going too low)
    • Example: 20 → 15 → 10 → 5 steps across 4 cycles

    Increment Mode (Detail Enhancement Strategy)

    Best for progressive detail enhancement with more steps in later cycles:

    • Use Case: When you want quick initial generation, then detailed refinement
    • Configuration:
      • Steps Adjustment Mode: increment
      • Steps Scaling Value: 5-10 (moderate increase)
      • Threshold Mode: manual with reasonable cap (e.g., 50)
    • Example: 10 → 15 → 20 → 25 steps across 4 cycles

    Gradual Upscaling

    For smoother upscaling transitions:

    1. Enable "Gradual Upscaling"
    2. Set "Gradual Upscale Steps" to 3-5
    3. Use with higher upscale factors (3.0+) for best results

    Post-Processing Nodes

    ComfyUI-KarmaNodes includes specialized post-processing nodes for enhancing your generated images with professional-grade effects and color corrections.

    🎬 Karma Film Grain

    Add authentic analog film grain texture to your images for a cinematic, vintage aesthetic.

    Features

    • Realistic Multi-Layer Grain: Combines multiple noise layers for authentic film texture
    • Luminance-Based Intensity: More grain in darker areas, mimicking real film behavior
    • Configurable Parameters: Adjustable grain strength and particle size
    • Reproducible Results: Seed-based grain patterns for consistent outputs
    • Fallback Support: Works even without scipy dependency

    Parameters

    • Strength (0.01-1.0): Intensity of the film grain effect
    • Grain Size (0.1-5.0): Size/scale of grain particles
    • Seed (0-2³¹-1): Random seed for reproducible grain patterns

    Usage Tips

    • Subtle Effects: Use strength values 0.05-0.15 for realistic film look
    • Vintage Style: Higher strength (0.2-0.4) with larger grain size (2.0-3.0)
    • Fine Detail: Smaller grain size (0.5-1.0) for high-resolution images
    • Consistency: Use the same seed across similar images for matching grain patterns

    🎨 Karma Kolors

    Professional color grading and correction tools for precise image enhancement.

    Features

    • White Balance Correction: Temperature-based color correction (2000K-10000K)
    • Brightness Control: Precise brightness adjustments (-20% to +20%)
    • Contrast Enhancement: Professional contrast control with fine increments
    • Saturation Adjustment: Color intensity control for vibrant or muted looks
    • Optimal Processing Order: Adjustments applied in the correct sequence for best results

    Parameters

    • White Balance: Temperature in Kelvin (2000K-10000K) or "auto"
      • 2000K-3000K: Warm, candlelight tones
      • 3000K-4000K: Warm white, tungsten lighting
      • 5000K-6500K: Daylight, neutral white
      • 6500K-10000K: Cool, blue-tinted lighting
    • Brightness (-20% to +20%): Overall image brightness in 0.5% increments
    • Contrast (-20% to +20%): Contrast adjustment in 0.5% increments
    • Saturation (-20% to +20%): Color intensity in 0.5% increments

    Usage Tips

    • Natural Corrections: Start with small adjustments (±2-5%)
    • Creative Looks: Combine temperature shifts with saturation changes
    • Portrait Enhancement: Slight brightness (+2-5%) and contrast (+3-8%)
    • Landscape Vibrancy: Increase saturation (+5-10%) with slight contrast boost
    • Vintage Look: Warm temperature (3000K-4000K) with reduced saturation (-5-10%)

    Post-Processing Workflow Examples

    Basic Enhancement Chain

    [Generated Image] → [Karma Kolors] → [Karma Film Grain] → [Save Image]

    Professional Color Grading

    [Generated Image] → [Karma Kolors] → [Additional Processing] → [Final Output]
                     ↓
                   White Balance: 5500K
                   Brightness: +3.0%
                   Contrast: +5.0%
                   Saturation: +2.0%

    Cinematic Film Look

    [Generated Image] → [Karma Kolors] → [Karma Film Grain] → [Save Image]
                     ↓                ↓
                   Warm tone (3200K)   Strength: 0.12
                   Contrast: +8%       Grain Size: 1.5
                   Saturation: -3%     Seed: 42

    Requirements

    • Python: 3.9+
    • PyTorch: 2.0.0+
    • Pillow: 9.0.0+
    • NumPy: 1.21.0+
    • scikit-image: 0.19.0+
    • ComfyUI: Latest version

    Optional Dependencies

    • scipy: 1.9.0+ (recommended for enhanced film grain quality)
    • colorsys: Built-in Python module (used for color space conversions)

    Performance Tips

    1. Memory Management: Enable tiled VAE for large images
    2. Cycle Count: More cycles = better quality but longer processing time
    3. Upscale Factor: Higher factors require more VRAM
    4. Model Selection: Use appropriate models for your target resolution

    Troubleshooting

    Common Issues

    Out of Memory Errors:

    • Enable tiled VAE processing
    • Reduce upscale factor or number of cycles
    • Use smaller initial latent size
    • Disable gradual upscaling to reduce intermediate steps

    Poor Quality Results:

    • Increase number of cycles
    • Adjust denoise strengths and enable denoise scaling
    • Try different upscaling methods
    • Enable sharpening filter
    • Use steps scaling with increment mode for more detail in later cycles
    • Enable gradual upscaling for smoother transitions

    Slow Performance:

    • Reduce number of cycles
    • Use basic upscaling instead of model-based
    • Use steps scaling with decrement mode to reduce steps in later cycles
    • Disable gradual upscaling
    • Use auto threshold mode for steps scaling

    Steps Scaling Issues:

    • Steps going too low: Use manual threshold mode with appropriate minimum
    • Steps going too high: Use manual threshold mode with reasonable maximum
    • Inconsistent results: Try auto threshold mode for balanced scaling

    Post-Processing Issues:

    • Film grain too strong: Reduce strength value (try 0.05-0.10 for subtle effects)
    • Grain pattern inconsistent: Use the same seed value across related images
    • Color corrections too harsh: Use smaller adjustment increments (±1-3%)
    • White balance not working: Ensure temperature value is within 2000K-10000K range
    • Scipy warning for film grain: Install scipy for better grain quality: pip install scipy

    Contributing

    Contributions are welcome! Please feel free to submit issues, feature requests, or pull requests.

    License

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

    Acknowledgments

    • Built for the ComfyUI ecosystem
    • Inspired by progressive sampling techniques in diffusion models
    • Thanks to the ComfyUI community for feedback and testing

    Support

    ☕ Support Development

    If you find ComfyUI-KarmaNodes useful and want to support future development, consider buying me a coffee! Your support helps maintain and improve these tools, develop new features, and keep everything free and open-source.

    ☕ Buy me a coffee

    Every contribution, no matter how small, is greatly appreciated and directly contributes to:

    • 🚀 New node development and features
    • 🐛 Bug fixes and performance improvements
    • 📚 Better documentation and tutorials
    • 🔧 Ongoing maintenance and support

    Thank you for being part of the ComfyUI-KarmaNodes community! 🙏

    Note: This node is designed for advanced users familiar with ComfyUI workflows. Basic knowledge of diffusion model sampling is recommended.