🧪 LoRA x Sampler x Scheduler Grid (Forge)

💡 An advanced script for Stable Diffusion Forge that generates comprehensive comparison grids exploring LoRA models across different samplers, schedulers, and weight combinations.

📝 Description

This script creates detailed image grids in two operational modes: XY Grid for systematic combinatorial testing and Batch Grid for custom sampler-scheduler pair configurations. It's designed to help artists and researchers visualize the impact of different LoRA weights across various generation parameters.

✨ Features

• 🎯 Dual Operation Modes: XY Grid for automatic matrix generation and Batch Grid for customized pair combinations
• 🔄 LoRA Weight Testing: Flexible weight range configuration with min/max values and step precision
• 🏷️ Smart Label Positioning: Configurable label placement (Top, Bottom, Left, Right) with automatic collision detection
• ⚡ Trigger Word Support: Optional trigger word integration with display toggle
• 🛡️ Error Resilience: Fallback image generation with detailed error information when generation fails
• 📊 Progress Monitoring: Real-time generation progress logging with detailed parameter information
• 🖼️ Flexible Output: Individual cell saving and multiple format support (WEBP/PNG)
• 🎨 Custom Font Support: Barlow-SemiBold.ttf integration for improved label readability
• 📏 Auto-Scaling: Automatic downscaling of large grids beyond 16380px dimensions
• 🛑 Process Control: Dedicated stop generation button for long-running operations

⚙️ Installation

1. Clone the repository into your Forge /extensions/ folder: git clone https://github.com/PupaBoo/Forge-Grid-Sampler-Scheduler

2. Navigate to the project directory: cd Forge-Grid-Sampler-Scheduler

3. Install dependencies: pip install -r requirements.txt

4. (Optional) Place the Barlow-SemiBold.ttf font in the fonts/ folder for improved label display.

5. Restart WebUI: The script will appear in the txt2img scripts dropdown as "🧪 LoRa x Sampler x Scheduler Grid (Forge)"

🚀 Usage

1. Launch Forge WebUI and select 🧪 LoRa x Sampler x Scheduler Grid (Forge) from the txt2img script dropdown.

2. Choose a mode:

   • XY Grid: Select one or multiple samplers and schedulers via dropdowns. The script automatically generates all possible combinations in a comprehensive matrix format.
   • Batch Grid: Add custom sampler-scheduler pairs using dropdowns with the "Add Pair" button or manually enter pairs in the text field (format: Sampler Name, Scheduler Name per line).

3. Configure parameters:

   • LoRA Model: Select from available LoRA models in your models/Lora directory
   • LoRA Weights: Set minimum, maximum, and step values for weight testing range
   • Trigger Word: Optional activation word with display toggle option
   • Positive/negative prompts
   • Seed (leave blank for random)
   • Steps, CFG scale, image dimensions, padding
   • Save format (WEBP/PNG)
   • Label positions for LoRA, sampler, and scheduler (Top/Bottom/Left/Right)
   • Label visibility options
   • Individual cell saving option (saves to outputs/cells/)

4. Click "Generate" to create the grid. Generation progress for each combination and any errors are logged in the terminal. Use the "🛑 Stop Generation" button to interrupt long-running operations.

📁 Output Structure

outputs/
└── 🧪 LoRa x Sampler x Scheduler Grid (Forge)/
    ├── cells/                                  # Individual cell images
    │   ├── LoRAName_W0.50_Sampler_Scheduler_0_0.webp
    │   └── ...
    ├── xy_grid_1700000000_001.webp             # XY Grid output (WEBP format)
    ├── xy_grid_1700000000_001.png              # XY Grid output (PNG format)
    ├── batch_grid_1700000000_001.webp          # Batch Grid output (WEBP format)
    └── batch_grid_1700000000_001.png           # Batch Grid output (PNG format)

🛠 Requirements

• Stable Diffusion Forge
• Python 3.7+
• Libraries: gradio, Pillow (included with Forge)

⚡ Technical Features

• Auto-Correction: Intelligent name matching for samplers and schedulers.
• Validation: Comprehensive configuration validation with helpful error messages.
• Unicode Support: Proper handling of special characters and emojis in names.
• Font Caching: Optimized performance through font caching mechanisms.
• Memory Management: Efficient handling of large grids with auto-scaling.

⚠️ Limitations

• Mode Restriction: Works exclusively in txt2img mode.
• Resource Intensive: Large grids may require significant VRAM and processing time.
• Font Dependency: Optimal text rendering requires Barlow-SemiBold.ttf availability.
• Grid Size: Very large combinations may produce extremely large output files.

📜 License

MIT License © 2025 - Free to use with attribution.

🙌 Acknowledgments

• Built with Gradio and Pillow libraries
• Developed with AI assistance tools
• Inspired by the needs of the Stable Diffusion artist community

🤝 Contributing

Feedback, bug reports, and feature suggestions are welcome. Please report issues with detailed descriptions of the problem and your configuration.

📸 Examples

🧩 Batch Grid	🔄 XY Grid
📊 Small Steps Grid
⚡ With Trigger Word	🚫 Without Trigger Word
🐋 Huge Grid