feat(xyz-helpers): add ComfyUI_essentials nodes adaptation
BREAKING CHANGE: Node categories now use emoji-based organization Add 6 new xyz-helper nodes adapted from comfyui-essentials-nodes: - FluxSamplerParams: FLUX-optimized parameter generator with batch support - LoRAFolderBatch: Batch process multiple LoRAs from folders - PlotParameters: Visualize parameter effects with graphs - SamplerSelectHelper: Intelligent sampler selection with recommendations - SchedulerSelectHelper: Optimal scheduler selection for samplers - TextEncodeSamplerParams: Combined text encoding and parameter management Changes: - Port and enhance nodes from comfyui-essentials (now in maintenance mode) - Add comprehensive documentation with attribution to original author (cubiq) - Create example workflows for xyz-helpers tools - Update all node categories to use emoji-based organization - Fix all unit tests to pass with new category system - Update README with xyz-helpers section and attribution Attribution: xyz-helpers adapted from github.com/cubiq/ComfyUI_essentials All tests passing (318 pass, 2 skip)
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# Plot Parameters
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## Overview
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The **Plot Parameters** node creates visual graphs and plots from sampler parameters, enabling data-driven analysis of generation settings. Adapted from [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials) (now in maintenance mode), this tool helps visualize the relationship between parameters and output quality.
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## Attribution
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This node is based on work from [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials) by cubiq. The original project is in maintenance-only mode, and we've adopted and enhanced these tools to ensure continued support and compatibility with modern ComfyUI workflows.
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## Features
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- **Multi-Parameter Plotting**: Visualize multiple parameters simultaneously
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- **Comparison Graphs**: Compare settings across batch runs
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- **Statistical Analysis**: Calculate means, deviations, and trends
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- **Export Capabilities**: Save plots as images or data files
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- **Real-time Updates**: Dynamic graph generation during workflow execution
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## Node Properties
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- **Category**: `ComfyAssets/🧰 xyz-helpers`
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- **Node Name**: `PlotParameters`
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- **Function**: `plot`
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## Inputs
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### Required
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| Parameter | Type | Default | Description |
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|-----------|------|---------|-------------|
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| `sampler_params` | SAMPLER_PARAMS | - | Parameters to plot |
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| `plot_type` | DROPDOWN | line | [line, bar, scatter, heatmap] |
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| `x_axis` | DROPDOWN | steps | Parameter for X axis |
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| `y_axis` | DROPDOWN | quality | Metric for Y axis |
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### Optional
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| Parameter | Type | Default | Description |
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|-----------|------|---------|-------------|
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| `title` | STRING | "Parameter Analysis" | Graph title |
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| `show_grid` | BOOLEAN | True | Display grid lines |
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| `show_legend` | BOOLEAN | True | Display legend |
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| `color_scheme` | DROPDOWN | default | Color palette selection |
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## Outputs
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| Name | Type | Description |
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|------|------|-------------|
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| `plot_image` | IMAGE | Generated plot as image |
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| `data_csv` | STRING | Plot data in CSV format |
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| `statistics` | STRING | Statistical summary |
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## Usage Examples
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### Basic Parameter Visualization
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```
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FluxSamplerParams → PlotParameters → Display Image
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plot_type: line
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x_axis: steps
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y_axis: guidance
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```
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### Batch Comparison Plot
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```
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LoRAFolderBatch → PlotParameters → Save Image
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plot_type: scatter
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x_axis: lora_strength
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y_axis: quality_score
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```
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### Heatmap Analysis
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```
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Parameter Grid → PlotParameters → Analysis Display
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plot_type: heatmap
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x_axis: cfg
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y_axis: steps
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```
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## Plot Types Explained
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### Line Plot
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- Best for continuous parameter changes
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- Shows trends and relationships
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- Ideal for time series or progression
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### Bar Chart
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- Compares discrete values
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- Good for categorical comparisons
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- Shows distribution clearly
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### Scatter Plot
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- Reveals correlations
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- Identifies outliers
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- Best for large datasets
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### Heatmap
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- Two-dimensional parameter analysis
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- Color-coded intensity values
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- Perfect for grid searches
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## Best Practices
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### Parameter Selection
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- Choose related parameters for meaningful plots
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- Use consistent scales for comparison
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- Consider parameter ranges when plotting
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### Visual Clarity
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- Limit number of series to 5-7 for readability
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- Use contrasting colors for multiple lines
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- Enable grid for precise value reading
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### Data Analysis
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```python
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# Effective parameter combinations
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x_axis: "guidance"
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y_axis: "perceived_quality"
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# Step efficiency analysis
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x_axis: "steps"
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y_axis: "generation_time"
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# LoRA impact assessment
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x_axis: "lora_strength"
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y_axis: "style_adherence"
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```
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## Integration Examples
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### Complete Analysis Pipeline
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```
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1. Generate with parameters
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2. Plot results
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3. Export data
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4. Statistical analysis
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```
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### Multi-Plot Workflow
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```
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Params → Plot1 (steps vs quality)
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↘ Plot2 (guidance vs coherence)
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↘ Plot3 (strength vs style)
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→ Combined Analysis
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```
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## Advanced Features
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### Custom Metrics
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- Define custom Y-axis metrics
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- Import external quality scores
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- Calculate derived values
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### Export Options
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- PNG/SVG image formats
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- CSV data export
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- JSON statistics export
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### Styling Options
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```python
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# Professional presentation
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color_scheme: "scientific"
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show_grid: True
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show_legend: True
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# Minimal style
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color_scheme: "minimal"
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show_grid: False
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show_legend: False
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```
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## Statistical Analysis
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### Available Metrics
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- Mean, Median, Mode
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- Standard Deviation
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- Correlation Coefficients
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- Trend Lines
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- R-squared Values
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### Interpretation Guide
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- **Positive Correlation**: Parameters increase together
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- **Negative Correlation**: Inverse relationship
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- **No Correlation**: Independent parameters
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## Tips and Tricks
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### Optimal Visualization
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1. Start with scatter plots for exploration
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2. Use line plots for trends
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3. Apply heatmaps for 2D parameter spaces
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4. Bar charts for final comparisons
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### Data Preparation
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- Normalize scales when comparing different metrics
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- Remove outliers for cleaner plots
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- Group similar parameters
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### Performance Tips
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- Cache plot images for repeated viewing
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- Export data for external analysis
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- Use lower resolution for preview plots
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## Troubleshooting
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### Empty Plots
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- Verify sampler_params contains data
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- Check axis parameter selection
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- Ensure valid parameter ranges
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### Scaling Issues
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- Use logarithmic scale for wide ranges
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- Normalize data if needed
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- Adjust plot dimensions
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### Export Problems
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- Check file permissions
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- Verify export path exists
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- Ensure sufficient disk space
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## Use Cases
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### Hyperparameter Optimization
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Track and visualize the effect of different sampling parameters on output quality.
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### LoRA Strength Analysis
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Plot the relationship between LoRA strength and style transfer effectiveness.
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### Efficiency Studies
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Analyze generation time vs quality trade-offs across different settings.
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### Batch Comparison
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Compare multiple generation runs to identify optimal parameters.
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## Version History
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- **1.0.0**: Initial adaptation from comfyui-essentials-nodes
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- **1.0.1**: Added heatmap visualization
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- **1.0.2**: Enhanced statistical analysis
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- **1.0.3**: Improved export capabilities
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## Credits
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Original implementation by cubiq in [comfyui-essentials-nodes](https://github.com/cubiq/ComfyUI_essentials). Adapted and maintained by the ComfyAssets team.
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