GeekyRemB v4.0: Ultimate AI Background Removal & Video Layering Node for ComfyUI

GeekyRemB v4.0 is a revolutionary image and video processing node suite that brings state-of-the-art AI models, professional compositing, advanced animation, and cutting-edge multimodal capabilities to ComfyUI. Built on the latest AI architectures including RMBG v2.0 with BiRefNet, it represents the pinnacle of background removal and video layering technology.

🚀 What's New in v4.0

• Latest AI Models: RMBG v2.0 with BiRefNet architecture for superior background removal
• Advanced Multimodal Processing: Cross-modal analysis and generation capabilities
• Professional Animation System: 20+ animation types with advanced easing functions
• Physics-Aware Generation: Realistic simulation for next-generation content
• Professional Blending Modes: 15+ industry-standard compositing modes
• Self-Optimizing Workflows: AI-powered workflow optimization and generation
• GPU Acceleration: Optimized performance with intelligent memory management
• Video Batch Processing: Frame-consistent processing for video sequences

Table of Contents

1. Installation
2. Core Features
3. AI Models & Methods
4. Professional Animation System
5. Advanced Positioning & Blending
6. Multimodal Processing
7. Workflow Examples
8. Performance Optimization
9. API Reference
10. Troubleshooting

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Installation

Prerequisites

• ComfyUI (latest version recommended)
• Python 3.8+
• PyTorch 2.0+
• CUDA-capable GPU (recommended for optimal performance)

Quick Installation

1. Clone the repository:

   cd ComfyUI/custom_nodes
   git clone https://github.com/GeekyGhost/ComfyUI-GeekyRemB.git
   cd ComfyUI-GeekyRemB

2. Install dependencies:

   pip install -r requirements.txt

3. GPU Acceleration Setup (Optional but recommended):

   # For NVIDIA GPUs
   pip install onnxruntime-gpu>=1.16.0
   
   # For AMD ROCm
   pip install torch-audio-rocm>=2.0.0

4. Restart ComfyUI to load the new nodes.

Advanced Installation Options

For development or advanced users:

# Create virtual environment
python -m venv geeky_remb_env
source geeky_remb_env/bin/activate  # Linux/Mac
# or: geeky_remb_env\Scripts\activate  # Windows

# Install with optional features
pip install -r requirements.txt
pip install matplotlib imageio ffmpeg-python  # Optional enhancements

---

Core Features

🎯 State-of-the-Art Background Removal

Supported AI Models:

• RMBG v2.0 (BiRefNet) - Latest architecture for superior quality
• RMBG v1.4 (BRIA AI) - Professional-grade removal
• BiRefNet Direct - High-performance segmentation
• Advanced Chroma Key - Professional green/blue screen with spill suppression
• Hybrid AI+Chroma - Combines AI and chroma key for optimal results

Advanced Features:

• Adaptive model selection based on content analysis
• Real-time edge refinement with alpha matting
• Intelligent mask processing with small object removal
• Professional spill suppression and edge feathering
• Batch processing with frame consistency

🎬 Professional Video Processing

• Multi-frame Processing: Optimized for video sequences with frame consistency
• Thread Pool Optimization: Parallel processing for maximum performance
• Advanced Caching: LRU cache system reduces redundant computations
• Memory Management: Intelligent VRAM handling from 1GB to 64GB+ systems
• Export Options: Multiple video formats with quality optimization

🎨 Advanced Compositing Engine

• 15+ Blend Modes: Industry-standard modes including Multiply, Screen, Overlay, Soft Light
• Professional Positioning: 11 positioning modes from absolute pixels to custom anchors
• Transform Controls: Scale, rotation, flip with sub-pixel precision
• Layer Effects: Drop shadows, perspective shadows, lighting effects
• Alpha Channel Management: Sophisticated transparency handling

---

AI Models & Methods

Model Selection Guide

Model	Best For	Performance	Quality	GPU Memory
RMBG v2.0 (BiRefNet)	General use, highest quality	Medium	Excellent	4-8GB
RMBG v1.4 (BRIA AI)	Professional workflows	Fast	Very Good	2-4GB
BiRefNet Direct	Complex subjects, fine details	Slow	Excellent	6-12GB
Advanced Chroma Key	Studio environments	Very Fast	Good	<1GB
Hybrid AI+Chroma	Mixed environments	Medium	Excellent	4-6GB

Configuration Examples

# High-quality portrait processing
removal_config = BackgroundRemovalConfig(
    method=RemovalMethod.RMBG_V2,
    model_precision="fp16",
    processing_resolution=1024,
    edge_feathering=3.0,
    remove_small_objects=True,
    anti_aliasing=True
)

# Speed-optimized processing  
removal_config = BackgroundRemovalConfig(
    method=RemovalMethod.RMBG_V1_4,
    processing_resolution=512,
    batch_size=4,
    use_gpu_acceleration=True
)

# Professional chroma key
removal_config = BackgroundRemovalConfig(
    method=RemovalMethod.CHROMA_KEY,
    chroma_color="green",
    tolerance=0.15,
    spill_suppression=0.9,
    edge_feathering=2.0
)

---

Professional Animation System

20+ Animation Types

Movement Animations:

• slide_left, slide_right, slide_up, slide_down, slide_diagonal
• orbit_circular, spiral_in, bounce_in, bounce_out

Transform Animations:

• scale_in, scale_out, scale_pulse
• rotate_clockwise, rotate_counter_clockwise
• flip_horizontal, flip_vertical

Special Effects:

• fade_in, fade_out, fade_pulse
• elastic_in, elastic_out
• shake_subtle, wobble

Advanced Easing Functions

Professional easing for natural motion:

• Linear: Constant speed movement
• Quadratic: ease_in_quad, ease_out_quad, ease_in_out_quad
• Cubic: Smooth acceleration/deceleration
• Sine: Natural sinusoidal motion
• Exponential: Dramatic speed changes
• Elastic: Spring-like bouncing effects
• Bounce: Realistic bouncing motion
• Back: Overshoot and settle effects

Animation Configuration

# Smooth bounce animation
animation_config = AnimationConfig(
    animation_type=AnimationType.BOUNCE_IN,
    duration=2.0,
    easing=EasingFunction.EASE_OUT_BOUNCE,
    amplitude=150.0,
    frequency=1.0,
    loop_count=3,
    ping_pong=True
)

# Complex orbital motion
animation_config = AnimationConfig(
    animation_type=AnimationType.ORBIT_CIRCULAR,
    duration=4.0,
    easing=EasingFunction.SINE_IN_OUT,
    amplitude=200.0,
    frequency=2.0,
    start_delay=0.5
)

---

Advanced Positioning & Blending

11 Positioning Modes

1. Absolute Pixels - Precise pixel positioning
2. Relative Percent - Percentage-based positioning
3. Center - Automatic centering
4. Corner Positions - Top/bottom + left/center/right combinations
5. Custom Anchor - User-defined anchor points with offset

Professional Blend Modes

Blend Mode	Effect	Best For
Normal	Standard overlay	General compositing
Multiply	Darkening effect	Creating shadows, depth
Screen	Lightening effect	Adding highlights, glow
Overlay	Contrast enhancement	Dramatic effects
Soft Light	Subtle lighting	Natural lighting effects
Hard Light	Strong contrast	Bold, dramatic looks
Color Dodge/Burn	Extreme lighting	Special effects
Darken/Lighten	Selective blending	Texture blending
Difference	Inversion effects	Abstract, artistic looks

Advanced Layer Effects

# Professional drop shadow
blend_config = BlendingConfig(
    blend_mode=BlendMode.NORMAL,
    opacity=0.9,
    drop_shadow=True,
    shadow_offset_x=8.0,
    shadow_offset_y=12.0,
    shadow_blur=15.0,
    shadow_opacity=0.6,
    shadow_color=(0, 0, 0)
)

# Cinematic lighting effect
blend_config = BlendingConfig(
    blend_mode=BlendMode.SOFT_LIGHT,
    opacity=0.8,
    preserve_luminosity=True,
    knock_out=False
)

---

Multimodal Processing

Cross-Modal Analysis

GeekyRemB v4.0 introduces cutting-edge multimodal capabilities:

• Vision-Audio Synchronization: Automatic sync detection for video content
• Text-to-Visual Generation: AI-powered visual generation from descriptions
• Cross-Modal Search: Find content across different modalities
• Multimodal Reasoning: Advanced AI reasoning across image, audio, and text

Usage Examples

# Multimodal content analysis
result = multimodal_processor.process_multimodal(
    processing_mode="analysis",
    image=input_image,
    audio_path="audio_track.wav",
    text_prompt="Analyze the emotional content",
    modality_weights={"vision": 0.4, "audio": 0.4, "text": 0.2}
)

# Cross-modal generation
result = multimodal_processor.process_multimodal(
    processing_mode="generation",
    text_prompt="A serene sunset over calm waters",
    reference_style=style_image,
    quality_target="cinema",
    output_modalities="all"
)

---

Workflow Examples

1. Basic Professional Background Removal

# Input: Portrait photo with complex background
# Output: Clean subject with transparent background

workflow = {
    "nodes": {
        "1": {
            "class_type": "GeekyRemB",
            "inputs": {
                "foreground": ["load_image", 0],
                "skip_background_removal": False,
                "removal_method": "rmbg_v2_birefnet",
                "processing_resolution": 1024,
                "mask_blur": 1.5,
                "edge_feathering": 3.0,
                "remove_small_objects": True
            }
        }
    }
}

2. Cinematic Character Animation

# Create a cinematic character entrance with lighting
workflow = {
    "character_removal": {
        "removal_method": "birefnet_zhengpeng7",
        "quality_target": "cinema",
        "edge_feathering": 2.0
    },
    "animation": {
        "animation_type": "slide_right",
        "duration": 3.0,
        "easing": "ease_out_cubic",
        "amplitude": 400.0
    },
    "lighting": {
        "enable_lighting": True,
        "light_direction_x": -100,
        "light_direction_y": -150,
        "light_intensity": 0.8,
        "enable_shadow": True,
        "shadow_opacity": 0.4
    },
    "composition": {
        "blend_mode": "soft_light",
        "position_mode": "center",
        "scale_x": 1.2,
        "scale_y": 1.2
    }
}

3. Multi-Subject Video Processing

# Process video with multiple subjects and complex backgrounds
workflow = {
    "batch_processing": {
        "total_frames": 120,
        "video_fps": 24.0,
        "removal_method": "hybrid_ai_chroma",
        "batch_processing": True
    },
    "optimization": {
        "use_gpu_acceleration": True,
        "processing_resolution": 720,
        "thread_count": 8
    },
    "output": {
        "video_format": "mp4",
        "quality": "high",
        "maintain_frame_consistency": True
    }
}

4. Advanced Keyframe Animation

# Create complex keyframe-based animation sequence
keyframes = [
    {
        "frame": 0,
        "x_position": -200,
        "y_position": 0,
        "scale": 0.8,
        "rotation": 0,
        "opacity": 0.0
    },
    {
        "frame": 30,
        "x_position": 0,
        "y_position": -50,
        "scale": 1.0,
        "rotation": 15,
        "opacity": 1.0
    },
    {
        "frame": 60,
        "x_position": 150,
        "y_position": 0,
        "scale": 1.1,
        "rotation": 0,
        "opacity": 0.9
    },
    {
        "frame": 90,
        "x_position": 0,
        "y_position": 0,
        "scale": 1.0,
        "rotation": 0,
        "opacity": 1.0
    }
]

animation_config = {
    "use_keyframes": True,
    "easing_function": "ease_in_out_cubic",
    "total_frames": 90,
    "fps": 30
}

---

Performance Optimization

GPU Memory Management

GeekyRemB v4.0 includes intelligent memory management for various GPU configurations:

GPU Memory	Recommended Settings	Performance
1-2GB	LOW_VRAM mode, 512px resolution	Basic processing
4-6GB	NORMAL_VRAM mode, 1024px resolution	Good performance
8-12GB	HIGH_VRAM mode, 1536px resolution	Optimal performance
16GB+	Maximum settings, 2048px+ resolution	Maximum quality

Optimization Settings

# For 4GB GPU
optimization_config = {
    "processing_resolution": 1024,
    "batch_size": 2,
    "use_gpu_acceleration": True,
    "model_precision": "fp16",
    "memory_management": "NORMAL_VRAM"
}

# For 16GB+ GPU  
optimization_config = {
    "processing_resolution": 2048,
    "batch_size": 8,
    "use_gpu_acceleration": True,
    "model_precision": "fp32",
    "memory_management": "HIGH_VRAM",
    "enable_model_caching": True
}

# CPU-optimized (no GPU)
optimization_config = {
    "processing_resolution": 512,
    "batch_size": 1,
    "use_gpu_acceleration": False,
    "thread_count": 8,
    "memory_management": "CPU_ONLY"
}

Performance Tips

1. Model Selection: Use lighter models (RMBG v1.4) for real-time applications
2. Resolution: Process at lower resolution, then upscale if needed
3. Batch Processing: Group similar operations for efficiency
4. Caching: Enable model and result caching for repeated operations
5. Threading: Adjust thread count based on CPU cores (recommended: CPU cores - 1)

---

API Reference

Core Classes

GeekyRemBv4

The main processing node with comprehensive background removal and compositing capabilities.

Key Parameters:

• removal_method: Choose AI model or chroma key method
• processing_resolution: Balance quality vs. performance
• animation_type: Select from 20+ animation types
• blend_mode: Professional compositing modes
• position_mode: Flexible positioning system

BackgroundRemovalConfig

Advanced configuration for background removal algorithms.

config = BackgroundRemovalConfig(
    method=RemovalMethod.RMBG_V2,
    model_precision="fp16",
    batch_size=4,
    chroma_color="green",
    tolerance=0.15,
    spill_suppression=0.9,
    edge_feathering=3.0,
    processing_resolution=1024,
    anti_aliasing=True
)

AnimationConfig

Professional animation control system.

config = AnimationConfig(
    animation_type=AnimationType.BOUNCE_IN,
    duration=2.0,
    easing=EasingFunction.EASE_OUT_BOUNCE,
    amplitude=100.0,
    frequency=1.0,
    loop_count=3,
    ping_pong=True
)

PositionConfig

Comprehensive positioning and transform system.

config = PositionConfig(
    mode=PositionMode.CUSTOM_ANCHOR,
    x_offset=100.0,
    y_offset=-50.0,
    anchor_x=0.5,
    anchor_y=0.3,
    scale_x=1.2,
    scale_y=1.0,
    rotation=15.0,
    flip_horizontal=False
)

Input/Output Types

Supported Input Types:

• IMAGE: Standard ComfyUI image tensors
• STRING: Text prompts and file paths
• FLOAT: Numerical parameters with validation
• INT: Integer values with range checking
• BOOLEAN: Toggle switches for features

Output Types:

• IMAGE: Processed image sequences
• MASK: Generated alpha masks
• STRING: Processing metadata and logs
• FLOAT: Confidence scores and metrics

---

Troubleshooting

Common Issues & Solutions

1. Background Removal Quality Issues

Problem: Poor edge quality or missed details Solutions:

• Try RMBG v2.0 (BiRefNet) for best quality
• Enable alpha_matting for fine details like hair
• Adjust edge_feathering (2.0-5.0 for complex edges)
• Increase processing_resolution to 1024 or higher
• Enable anti_aliasing for smoother edges

2. Performance & Memory Issues

Problem: Slow processing or out-of-memory errors Solutions:

• Reduce processing_resolution (try 512px)
• Switch to lighter model (RMBG v1.4)
• Enable LOW_VRAM mode in settings
• Reduce batch_size to 1-2
• Close other GPU-intensive applications
• Use CPU mode for very limited systems

3. Animation Issues

Problem: Jerky or incorrect animations Solutions:

• Check fps setting matches your target frame rate
• Verify keyframe frame_number values are in correct sequence
• Ensure easing_function is appropriate for animation type
• Check that total_frames encompasses all keyframes
• Verify node connections are correct

4. Video Processing Issues

Problem: Frame inconsistency or export failures Solutions:

• Enable batch_processing for video sequences
• Check that all frames have consistent dimensions
• Verify video_fps matches source material
• Ensure sufficient disk space for output
• Try different output formats (mp4, webm)

5. Chroma Key Issues

Problem: Color spill or incomplete removal Solutions:

• Adjust tolerance (start with 0.15, increase gradually)
• Enable spill_suppression (0.7-0.9)
• Increase edge_feathering (2.0-5.0)
• Check lighting conditions in source material
• Consider hybrid_ai_chroma method for difficult scenarios

Debug Mode

Enable debug logging for detailed troubleshooting:

import logging
logging.basicConfig(level=logging.DEBUG)
logger = logging.getLogger(__name__)

System Requirements Verification

Minimum Requirements:

• Python 3.8+
• PyTorch 2.0+
• 4GB RAM
• 2GB storage space

Recommended:

• Python 3.10+
• PyTorch 2.1+
• CUDA-capable GPU with 8GB+ VRAM
• 16GB+ system RAM
• SSD storage

Optimal:

• Latest Python 3.11+
• PyTorch 2.2+ with CUDA 12+
• RTX 4080/4090 or equivalent
• 32GB+ system RAM
• NVMe SSD storage

---

Contributing

We welcome contributions from the community! Please see our Contributing Guidelines for details on:

• Code style and standards
• Testing requirements
• Documentation guidelines
• Pull request process

Development Setup

# Clone repository
git clone https://github.com/GeekyGhost/ComfyUI-GeekyRemB.git
cd ComfyUI-GeekyRemB

# Create development environment
python -m venv dev_env
source dev_env/bin/activate

# Install development dependencies
pip install -r requirements.txt
pip install pytest black flake8 mypy

# Run tests
pytest tests/

# Code formatting
black --check scripts/
flake8 scripts/
mypy scripts/

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License & Acknowledgements

License

This project is licensed under the MIT License. See LICENSE for details.

Note: Some AI models may have separate licensing requirements for commercial use. Please review individual model licenses.

Acknowledgements

GeekyRemB v4.0 builds upon exceptional open-source projects:

• RMBG - BiRefNet architecture for background removal
• BRIA AI - Professional-grade RMBG models
• ComfyUI - The incredible node-based UI framework
• OpenCV - Computer vision processing
• PyTorch - Deep learning framework

Special Thanks

• ComfyUI Community - Feedback, testing, and feature requests
• AI Researchers - Advancing the state-of-the-art in background removal
• Open Source Contributors - Making this technology accessible to everyone
• Beta Testers - Helping refine v4.0 before release

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Support & Community

• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Documentation: Wiki

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GeekyRemB v4.0 - Pushing the boundaries of what's possible in AI-powered image and video processing.

Made with ❤️ by GeekyGhost and the open-source community.