MetaHub Save Image - ComfyUI Custom Node

Advanced image saving node for ComfyUI with dual metadata support.

Features

• A1111/Civitai Compatible - Saves metadata in tEXt chunk ("parameters") recognized by Automatic1111, Civitai, and most SD tools
• Image MetaHub Compatible - Saves extended metadata in iTXt chunk ("imagemetahub_data") with full workflow JSON
• Auto-Detection - Automatically extracts LoRAs and their weights from your workflow
• Model Hashes - Calculates SHA256 hashes (AutoV2 format) for models and LoRAs
• IMH Pro Fields - Support for user tags, notes, and project names
• Performance - Hash caching and graceful degradation ensure fast generation
• Never Fails - Silent fallback on errors - your generation never stops

Installation

Method 1: Clone Repository (Recommended)

1. Navigate to your ComfyUI custom nodes directory:

   cd ComfyUI/custom_nodes
   

2. Clone this repository:

   git clone https://github.com/LuqP2/ImageMetaHub-ComfyUI-Save.git
   

3. Install dependencies:

   cd ImageMetaHub-ComfyUI-Save
   pip install -r requirements.txt
   

4. Restart ComfyUI

Method 2: Manual Installation

1. Download this repository as ZIP
2. Extract to ComfyUI/custom_nodes/ImageMetaHub-ComfyUI-Save
3. Install dependencies: pip install Pillow>=10.0.0 numpy>=1.24.0
4. Restart ComfyUI

Usage

Basic Usage

1. Add "MetaHub Save Image" node to your workflow

2. Connect the images output from your sampler

3. Fill in the generation parameters:

   • positive: Your positive prompt
   • negative: Your negative prompt
   • seed, steps, cfg: Generation settings
   • sampler_name, scheduler: Sampler configuration
   • model_name: Your checkpoint filename (e.g., model.safetensors)

4. Generate! Images are saved with full metadata.

Advanced Features

Auto-Detection of LoRAs

The node automatically scans your workflow for LoRA Loader nodes and extracts:

• LoRA filename
• Weight/strength value

No manual input needed!

IMH Pro Fields (Optional)

Organize your generations with Image MetaHub Pro features:

• user_tags: Tag your images (e.g., "portrait, fantasy, character")
• notes: Add generation notes or experiments
• project_name: Group images by project

Custom Output

• filename_prefix: Change output filename prefix (default: "ComfyUI")
• output_path: Save to custom directory (empty = ComfyUI default)

Configuration (Optional)

If your models are in non-standard locations, set environment variables:

# Windows (PowerShell)
$env:COMFYUI_CHECKPOINT_PATH="D:\MyModels\Checkpoints"
$env:COMFYUI_LORA_PATH="D:\MyModels\Loras"
$env:COMFYUI_VAE_PATH="D:\MyModels\VAE"

# Linux/macOS
export COMFYUI_CHECKPOINT_PATH="/path/to/checkpoints"
export COMFYUI_LORA_PATH="/path/to/loras"
export COMFYUI_VAE_PATH="/path/to/vae"

Metadata Formats

A1111/Civitai Format (tEXt chunk: "parameters")

masterpiece, best quality, 1girl, portrait
Negative prompt: ugly, blurry
Steps: 20, Sampler: euler, CFG scale: 7.0, Seed: 12345, Size: 512x768, Model: mymodel, Model hash: abc1234567, Lora hashes: "detail: def9876543"

Image MetaHub Format (iTXt chunk: "imagemetahub_data")

{
  "generator": "ComfyUI",
  "prompt": "masterpiece, best quality, 1girl, portrait",
  "negativePrompt": "ugly, blurry",
  "seed": 12345,
  "steps": 20,
  "cfg": 7.0,
  "sampler_name": "euler",
  "model": "mymodel.safetensors",
  "model_hash": "abc1234567",
  "loras": [{"name": "detail.safetensors", "weight": 0.8}],
  "imh_pro": {
    "user_tags": "portrait, fantasy",
    "notes": "Experimental composition",
    "project_name": "Character Design"
  },
  "workflow": { }
}

Integration with Image MetaHub

This node is the official companion for Image MetaHub.

Images saved with this node are fully compatible with Image MetaHub's:

• Search and filtering
• LoRA detection
• Analytics dashboard
• IMH Pro features

Troubleshooting

"Model hash is 0000000000"

• Your model file wasn't found in standard paths
• Set COMFYUI_CHECKPOINT_PATH environment variable
• Or ensure models are in ComfyUI/models/checkpoints/

"LoRAs not detected"

• Make sure you're using standard LoRA Loader nodes
• Check that LoRAs are connected in the workflow
• Custom LoRA nodes might not be detected

"Cannot create output directory"

• Check folder permissions
• Try using default output path (leave output_path empty)

Performance

• First image: ~200ms overhead (hash calculation)
• Subsequent images: ~60ms overhead (hashes cached)
• Batch processing: Minimal overhead per image

Hash calculation is cached in memory, so repeated generations with the same models are very fast.

License

MIT License

Contributing

Issues and pull requests welcome at https://github.com/LuqP2/ImageMetaHub-ComfyUI-Save

Credits

Developed for the Image MetaHub ecosystem.