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@@ -1,243 +1,277 @@
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# ComfyUI-RMBG Update Log
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## v1.6.0 (2025/01/22)
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### New Face Segment Custom Node
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- Added a new custom node for face parsing and segmentation
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- Support for 19 facial feature categories (Skin, Nose, Eyes, Eyebrows, etc.)
|
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- Precise facial feature extraction and segmentation
|
||||
- Multiple feature selection for combined segmentation
|
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- Same parameter controls as other RMBG nodes
|
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- Automatic model downloading and resource management
|
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- Perfect for portrait editing and facial feature manipulation
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||||
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## v1.5.0 (2025/01/05)
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### New Fashion and accessories Segment Custom Node
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- Added a new custom node for fashion and accessories segmentation.
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- Capable of identifying and segmenting various fashion items such as dresses, shoes, and accessories.
|
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- Utilizes advanced machine learning techniques for accurate segmentation.
|
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- Supports real-time processing for enhanced user experience.
|
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- Ideal for fashion-related applications, including virtual try-ons and outfit recommendations.
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- Support for gray background color.
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## v1.4.0 (2025/01/02)
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### New Clothes Segment Node
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- Added intelligent clothes segmentation functionality
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- Support for 18 different clothing categories (Hat, Hair, Face, Sunglasses, Upper-clothes, etc.)
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- Multiple item selection for combined segmentation
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- Same parameter controls as other RMBG nodes (process_res, mask_blur, mask_offset, background options)
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- Automatic model downloading and resource management
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## v1.3.2 (2024/12/29)
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### Updates
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- Enhanced background handling to support RGBA output when "Alpha" is selected.
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- Ensured RGB output for all other background color selections.
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## v1.3.1 (2024/12/25)
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### Bug Fixes
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- Fixed an issue with mask processing when the model returns a list of masks.
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- Improved handling of image formats to prevent processing errors.
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## v1.3.0 (2024/12/23)
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### New Segment (RMBG) Node
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- Text-Prompted Intelligent Object Segmentation
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- Use natural language prompts (e.g., "a cat", "red car") to identify and segment target objects
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- Support for multiple object detection and segmentation
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- Perfect for precise object extraction and recognition tasks
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||||
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||||
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### Supported Models
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- SAM (Segment Anything Model)
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- sam_vit_h: 2.56GB - Highest accuracy
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- sam_vit_l: 1.25GB - Balanced performance
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- sam_vit_b: 375MB - Lightweight option
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- GroundingDINO
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- SwinT: 694MB - Fast and efficient
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- SwinB: 938MB - Higher precision
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### Key Features
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- Intuitive Parameter Controls
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- Threshold: Adjust detection precision
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- Mask Blur: Smooth edges
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- Mask Offset: Expand or shrink selection
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- Background Options: Alpha/Black/White/Green/Blue/Red
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- Automatic Model Management
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- Auto-download models on first use
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- Smart GPU memory handling
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### Usage Examples
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1. Tag-Style Prompts
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- Single object: "cat"
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- Multiple objects: "cat, dog, person"
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- With attributes: "red car, blue shirt"
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- Format: Use commas to separate multiple objects (e.g., "a, b, c")
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2. Natural Language Prompts
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- Simple sentence: "a person wearing a red jacket"
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- Complex scene: "a woman in a blue dress standing next to a car"
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- With location: "a cat sitting on the sofa"
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- Format: Write a natural descriptive sentence
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|
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3. Tips for Better Results
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- For Tag Style:
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- Separate objects with commas: "chair, table, lamp"
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- Add attributes before objects: "wooden chair, glass table"
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- Keep it simple and clear
|
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- For Natural Language:
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- Use complete sentences
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- Include details like color, position, action
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- Be as descriptive as needed
|
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- Parameter Adjustments:
|
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- Threshold: 0.25-0.35 for broad detection, 0.45-0.55 for precision
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- Use mask blur for smoother edges
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- Adjust mask offset to fine-tune selection
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## v1.2.2 (2024/12/12)
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### Improvements
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- Changed INSPYRENET model format from .pth to .safetensors for:
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- Better security
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- Faster loading speed (2-3x faster)
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- Improved memory efficiency
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- Better cross-platform compatibility
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- Simplified node display name for better UI integration
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## v1.2.1 (2024/12/02)
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### New Features
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- ANPG (animated PNG), AWEBP (animated WebP) and GIF supported.
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||||
|
||||
https://github.com/user-attachments/assets/40ec0b27-4fa2-4c99-9aea-5afad9ca62a5
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||||
|
||||
### Bug Fixes
|
||||
- Fixed video processing issue
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|
||||
### Performance Improvements
|
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- Enhanced batch processing in RMBG-2.0 model
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- Added support for proper batch image handling
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- Improved memory efficiency by optimizing image size handling
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### Technical Details
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- Added original size preservation for maintaining aspect ratios
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||||
- Implemented proper batch tensor processing
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- Improved error handling and code robustness
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- Performance gains:
|
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- Single image processing: ~5-10% improvement
|
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- Batch processing: up to 30-50% improvement (depending on batch size and GPU)
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## v1.2.0 (2024/11/29)
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### Major Changes
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- Combined three background removal models into one unified node
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- Added support for RMBG-2.0, INSPYRENET, and BEN models
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- Implemented lazy loading for models (only downloads when first used)
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||||
|
||||
### Model Introduction
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- RMBG-2.0 ([Homepage](https://huggingface.co/briaai/RMBG-2.0))
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- Latest version of RMBG model
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- Excellent performance on complex backgrounds
|
||||
- High accuracy in preserving fine details
|
||||
- Best for general purpose background removal
|
||||
|
||||
- INSPYRENET ([Homepage](https://github.com/plemeri/InSPyReNet))
|
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- Specialized in human portrait segmentation
|
||||
- Fast processing speed
|
||||
- Good edge detection capability
|
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- Ideal for portrait photos and human subjects
|
||||
|
||||
- BEN (Background Elimination Network) ([Homepage](https://huggingface.co/PramaLLC/BEN))
|
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- Robust performance on various image types
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- Good balance between speed and accuracy
|
||||
- Effective on both simple and complex scenes
|
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- Suitable for batch processing
|
||||
|
||||
### Features
|
||||
- Unified interface for all three models
|
||||
- Common parameters for all models:
|
||||
- Sensitivity adjustment
|
||||
- Processing resolution control
|
||||
- Mask blur and offset options
|
||||
- Multiple background color options
|
||||
- Invert output option
|
||||
- Model optimization toggle
|
||||
|
||||
### Improvements
|
||||
- Optimized memory usage with model clearing
|
||||
- Enhanced error handling and user feedback
|
||||
- Added detailed tooltips for all parameters
|
||||
- Improved mask post-processing
|
||||
|
||||
### Dependencies
|
||||
- Updated all package dependencies to latest stable versions
|
||||
- Added support for transparent-background package
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- Optimized dependency management
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||||
|
||||
## v1.1.0 (2024/11/21)
|
||||
|
||||
### New Features
|
||||
- Added background color options
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||||
- Alpha (transparent background)
|
||||
- Black, White, Green, Blue, Red
|
||||
|
||||
|
||||
|
||||
- Improved mask processing
|
||||
- Better detail preservation
|
||||
- Enhanced edge quality
|
||||
- More accurate segmentation
|
||||
|
||||
|
||||
|
||||
- Added video batch processing
|
||||
- Support for video file background removal
|
||||
- Maintains original video framerate and resolution
|
||||
- Multiple output format support (with Alpha channel)
|
||||
- Efficient batch processing for video frames
|
||||
|
||||
https://github.com/user-attachments/assets/259220d3-c148-4030-93d6-c17dd5bccee1
|
||||
|
||||
- Added model cache management
|
||||
- Cache status checking
|
||||
- Model memory cleanup
|
||||
- Better error handling
|
||||
|
||||
### Parameter Updates
|
||||
- Renamed 'invert_mask' to 'invert_output' for clarity
|
||||
- Added sensitivity adjustment for mask strength
|
||||
- Updated tooltips for better clarity
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||||
|
||||
### Technical Improvements
|
||||
- Optimized image processing pipeline
|
||||
- Added proper model cache verification
|
||||
- Improved memory management
|
||||
- Better error handling and recovery
|
||||
- Enhanced batch processing performance for videos
|
||||
|
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### Dependencies
|
||||
- Added timm>=0.6.12,<1.0.0 for model support
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||||
- Updated requirements.txt with version constraints
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||||
|
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### Bug Fixes
|
||||
- Fixed mask detail preservation issues
|
||||
- Improved mask edge quality
|
||||
- Fixed memory leaks in model handling
|
||||
|
||||
### Usage Notes
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- The 'Alpha' background option provides transparent background
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- Sensitivity parameter now controls mask strength
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- Model cache is checked before each operation
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- Memory is automatically cleaned when switching models
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- Video processing supports various formats and maintains quality
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# ComfyUI-RMBG Update Log
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## v1.7.0 (2024/01/05)
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### New Model Added: BEN2
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- Added support for BEN2 (Background Elimination Network 2)
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- Improved performance over original BEN model
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- Better edge detection and detail preservation
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- Enhanced batch processing capabilities (up to 3 images per batch)
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- Optimized memory usage and processing speed
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### Model Changes
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- Updated model repository paths for BEN and BEN2
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- Switched to 1038lab repositories for better maintenance and updates
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- Maintained full compatibility with existing workflows
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### Technical Improvements
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- Implemented efficient batch processing for BEN2
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- Optimized memory management for large batches
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- Enhanced error handling and model loading
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- Improved model switching and resource cleanup
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||||
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### Comparison with Previous Models
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- BEN2 vs BEN:
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- Better edge detection
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- Improved handling of complex backgrounds
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||||
- More efficient batch processing
|
||||
- Enhanced detail preservation
|
||||
- Faster processing speed
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||||
|
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### Repository Updates
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||||
- Updated documentation to include BEN2 model
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- Added new model license information
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- Improved installation instructions
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- Updated version number to 1.7.0
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|
||||
## v1.6.0 (2025/01/22)
|
||||
|
||||
### New Face Segment Custom Node
|
||||
- Added a new custom node for face parsing and segmentation
|
||||
- Support for 19 facial feature categories (Skin, Nose, Eyes, Eyebrows, etc.)
|
||||
- Precise facial feature extraction and segmentation
|
||||
- Multiple feature selection for combined segmentation
|
||||
- Same parameter controls as other RMBG nodes
|
||||
- Automatic model downloading and resource management
|
||||
- Perfect for portrait editing and facial feature manipulation
|
||||
|
||||
|
||||
|
||||
## v1.5.0 (2025/01/05)
|
||||
|
||||
### New Fashion and accessories Segment Custom Node
|
||||
- Added a new custom node for fashion and accessories segmentation.
|
||||
- Capable of identifying and segmenting various fashion items such as dresses, shoes, and accessories.
|
||||
- Utilizes advanced machine learning techniques for accurate segmentation.
|
||||
- Supports real-time processing for enhanced user experience.
|
||||
- Ideal for fashion-related applications, including virtual try-ons and outfit recommendations.
|
||||
- Support for gray background color.
|
||||
|
||||
|
||||
|
||||
## v1.4.0 (2025/01/02)
|
||||
|
||||
### New Clothes Segment Node
|
||||
- Added intelligent clothes segmentation functionality
|
||||
- Support for 18 different clothing categories (Hat, Hair, Face, Sunglasses, Upper-clothes, etc.)
|
||||
- Multiple item selection for combined segmentation
|
||||
- Same parameter controls as other RMBG nodes (process_res, mask_blur, mask_offset, background options)
|
||||
- Automatic model downloading and resource management
|
||||
|
||||
|
||||
|
||||
## v1.3.2 (2024/12/29)
|
||||
|
||||
### Updates
|
||||
- Enhanced background handling to support RGBA output when "Alpha" is selected.
|
||||
- Ensured RGB output for all other background color selections.
|
||||
|
||||
## v1.3.1 (2024/12/25)
|
||||
|
||||
### Bug Fixes
|
||||
- Fixed an issue with mask processing when the model returns a list of masks.
|
||||
- Improved handling of image formats to prevent processing errors.
|
||||
|
||||
## v1.3.0 (2024/12/23)
|
||||
|
||||
### New Segment (RMBG) Node
|
||||
- Text-Prompted Intelligent Object Segmentation
|
||||
- Use natural language prompts (e.g., "a cat", "red car") to identify and segment target objects
|
||||
- Support for multiple object detection and segmentation
|
||||
- Perfect for precise object extraction and recognition tasks
|
||||
|
||||
|
||||
|
||||
### Supported Models
|
||||
- SAM (Segment Anything Model)
|
||||
- sam_vit_h: 2.56GB - Highest accuracy
|
||||
- sam_vit_l: 1.25GB - Balanced performance
|
||||
- sam_vit_b: 375MB - Lightweight option
|
||||
- GroundingDINO
|
||||
- SwinT: 694MB - Fast and efficient
|
||||
- SwinB: 938MB - Higher precision
|
||||
|
||||
### Key Features
|
||||
- Intuitive Parameter Controls
|
||||
- Threshold: Adjust detection precision
|
||||
- Mask Blur: Smooth edges
|
||||
- Mask Offset: Expand or shrink selection
|
||||
- Background Options: Alpha/Black/White/Green/Blue/Red
|
||||
- Automatic Model Management
|
||||
- Auto-download models on first use
|
||||
- Smart GPU memory handling
|
||||
|
||||
### Usage Examples
|
||||
1. Tag-Style Prompts
|
||||
- Single object: "cat"
|
||||
- Multiple objects: "cat, dog, person"
|
||||
- With attributes: "red car, blue shirt"
|
||||
- Format: Use commas to separate multiple objects (e.g., "a, b, c")
|
||||
|
||||
2. Natural Language Prompts
|
||||
- Simple sentence: "a person wearing a red jacket"
|
||||
- Complex scene: "a woman in a blue dress standing next to a car"
|
||||
- With location: "a cat sitting on the sofa"
|
||||
- Format: Write a natural descriptive sentence
|
||||
|
||||
3. Tips for Better Results
|
||||
- For Tag Style:
|
||||
- Separate objects with commas: "chair, table, lamp"
|
||||
- Add attributes before objects: "wooden chair, glass table"
|
||||
- Keep it simple and clear
|
||||
- For Natural Language:
|
||||
- Use complete sentences
|
||||
- Include details like color, position, action
|
||||
- Be as descriptive as needed
|
||||
- Parameter Adjustments:
|
||||
- Threshold: 0.25-0.35 for broad detection, 0.45-0.55 for precision
|
||||
- Use mask blur for smoother edges
|
||||
- Adjust mask offset to fine-tune selection
|
||||
|
||||
## v1.2.2 (2024/12/12)
|
||||
|
||||
|
||||
### Improvements
|
||||
- Changed INSPYRENET model format from .pth to .safetensors for:
|
||||
- Better security
|
||||
- Faster loading speed (2-3x faster)
|
||||
- Improved memory efficiency
|
||||
- Better cross-platform compatibility
|
||||
- Simplified node display name for better UI integration
|
||||
|
||||
## v1.2.1 (2024/12/02)
|
||||
|
||||
### New Features
|
||||
- ANPG (animated PNG), AWEBP (animated WebP) and GIF supported.
|
||||
|
||||
https://github.com/user-attachments/assets/40ec0b27-4fa2-4c99-9aea-5afad9ca62a5
|
||||
|
||||
### Bug Fixes
|
||||
- Fixed video processing issue
|
||||
|
||||
### Performance Improvements
|
||||
- Enhanced batch processing in RMBG-2.0 model
|
||||
- Added support for proper batch image handling
|
||||
- Improved memory efficiency by optimizing image size handling
|
||||
|
||||
### Technical Details
|
||||
- Added original size preservation for maintaining aspect ratios
|
||||
- Implemented proper batch tensor processing
|
||||
- Improved error handling and code robustness
|
||||
- Performance gains:
|
||||
- Single image processing: ~5-10% improvement
|
||||
- Batch processing: up to 30-50% improvement (depending on batch size and GPU)
|
||||
|
||||
## v1.2.0 (2024/11/29)
|
||||
|
||||
### Major Changes
|
||||
- Combined three background removal models into one unified node
|
||||
- Added support for RMBG-2.0, INSPYRENET, and BEN models
|
||||
- Implemented lazy loading for models (only downloads when first used)
|
||||
|
||||
### Model Introduction
|
||||
- RMBG-2.0 ([Homepage](https://huggingface.co/briaai/RMBG-2.0))
|
||||
- Latest version of RMBG model
|
||||
- Excellent performance on complex backgrounds
|
||||
- High accuracy in preserving fine details
|
||||
- Best for general purpose background removal
|
||||
|
||||
- INSPYRENET ([Homepage](https://github.com/plemeri/InSPyReNet))
|
||||
- Specialized in human portrait segmentation
|
||||
- Fast processing speed
|
||||
- Good edge detection capability
|
||||
- Ideal for portrait photos and human subjects
|
||||
|
||||
- BEN (Background Elimination Network) ([Homepage](https://huggingface.co/PramaLLC/BEN))
|
||||
- Robust performance on various image types
|
||||
- Good balance between speed and accuracy
|
||||
- Effective on both simple and complex scenes
|
||||
- Suitable for batch processing
|
||||
|
||||
### Features
|
||||
- Unified interface for all three models
|
||||
- Common parameters for all models:
|
||||
- Sensitivity adjustment
|
||||
- Processing resolution control
|
||||
- Mask blur and offset options
|
||||
- Multiple background color options
|
||||
- Invert output option
|
||||
- Model optimization toggle
|
||||
|
||||
### Improvements
|
||||
- Optimized memory usage with model clearing
|
||||
- Enhanced error handling and user feedback
|
||||
- Added detailed tooltips for all parameters
|
||||
- Improved mask post-processing
|
||||
|
||||
### Dependencies
|
||||
- Updated all package dependencies to latest stable versions
|
||||
- Added support for transparent-background package
|
||||
- Optimized dependency management
|
||||
|
||||
## v1.1.0 (2024/11/21)
|
||||
|
||||
### New Features
|
||||
- Added background color options
|
||||
- Alpha (transparent background)
|
||||
- Black, White, Green, Blue, Red
|
||||
|
||||
|
||||
|
||||
- Improved mask processing
|
||||
- Better detail preservation
|
||||
- Enhanced edge quality
|
||||
- More accurate segmentation
|
||||
|
||||
|
||||
|
||||
- Added video batch processing
|
||||
- Support for video file background removal
|
||||
- Maintains original video framerate and resolution
|
||||
- Multiple output format support (with Alpha channel)
|
||||
- Efficient batch processing for video frames
|
||||
|
||||
https://github.com/user-attachments/assets/259220d3-c148-4030-93d6-c17dd5bccee1
|
||||
|
||||
- Added model cache management
|
||||
- Cache status checking
|
||||
- Model memory cleanup
|
||||
- Better error handling
|
||||
|
||||
### Parameter Updates
|
||||
- Renamed 'invert_mask' to 'invert_output' for clarity
|
||||
- Added sensitivity adjustment for mask strength
|
||||
- Updated tooltips for better clarity
|
||||
|
||||
### Technical Improvements
|
||||
- Optimized image processing pipeline
|
||||
- Added proper model cache verification
|
||||
- Improved memory management
|
||||
- Better error handling and recovery
|
||||
- Enhanced batch processing performance for videos
|
||||
|
||||
### Dependencies
|
||||
- Added timm>=0.6.12,<1.0.0 for model support
|
||||
- Updated requirements.txt with version constraints
|
||||
|
||||
### Bug Fixes
|
||||
- Fixed mask detail preservation issues
|
||||
- Improved mask edge quality
|
||||
- Fixed memory leaks in model handling
|
||||
|
||||
### Usage Notes
|
||||
- The 'Alpha' background option provides transparent background
|
||||
- Sensitivity parameter now controls mask strength
|
||||
- Model cache is checked before each operation
|
||||
- Memory is automatically cleaned when switching models
|
||||
- Video processing supports various formats and maintains quality
|
||||
|
||||
Reference in New Issue
Block a user