MetaHub Save Image - ComfyUI Custom Node
Advanced image saving node for ComfyUI with dual metadata support.
Features
- Auto-Extraction - Detects sampler params, prompts, model/VAE, and LoRAs directly from your workflow
- Multi-Format - PNG, JPEG, and WebP with metadata injection
- Filename Patterns - Placeholder-based filenames with sanitization
- 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
- 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)
-
Navigate to your ComfyUI custom nodes directory:
cd ComfyUI/custom_nodes -
Clone this repository:
git clone https://github.com/LuqP2/ImageMetaHub-ComfyUI-Save.git -
Install dependencies:
cd ImageMetaHub-ComfyUI-Save pip install -r requirements.txt -
Restart ComfyUI
Method 2: Manual Installation
- Download this repository as ZIP
- Extract to
ComfyUI/custom_nodes/ImageMetaHub-ComfyUI-Save - Install dependencies:
pip install Pillow>=10.0.0 numpy>=1.24.0 piexif>=1.1.3 - Restart ComfyUI
Usage
Quick Start
- Add "MetaHub Save Image" node to your workflow
- Connect the
imagesoutput from your decoder/sampler - Generate! The node auto-detects and saves metadata.
Auto-detected fields:
- seed, steps, cfg
- sampler and scheduler
- model name + hash
- positive/negative prompts
- LoRAs + weights
- VAE name
Override (Optional)
Connect any override input to replace auto-detected values (seed, steps, cfg, sampler_name, scheduler, model_name, positive, negative, denoise, vae_name).
Filename Pattern
Use filename_pattern to customize names (default ComfyUI_%counter%). Invalid filename characters are sanitized and missing values become unknown. filename_prefix is deprecated but still supported.
| Placeholder | Description | Example |
|---|---|---|
%counter% |
Auto-increment (00001, 00002...) | 00042 |
%seed% |
Seed used | 1234567890 |
%date% |
Date YYYY-MM-DD | 2025-01-15 |
%time% |
Time HH-MM-SS | 14-30-22 |
%datetime% |
Date + time | 2025-01-15_14-30-22 |
%model% |
Model name (no extension) | dreamshaper_v8 |
%sampler% |
Sampler name | euler_ancestral |
%steps% |
Steps | 20 |
%cfg% |
CFG scale | 7.5 |
%width% |
Image width | 1024 |
%height% |
Image height | 768 |
File Formats
file_format: PNG, JPEG, or WebPquality: JPEG/WebP quality (1-100)output_path: custom output directory (empty = ComfyUI default)- PNG uses tEXt "parameters" and iTXt "imagemetahub_data"
- JPEG/WebP use EXIF UserComment (A1111) and ImageDescription (IMH JSON)
If structured metadata cannot be written, the image is still saved.
Multi-Sampler Heuristic
When multiple samplers exist, the node prefers the sampler that feeds the latent used by the VAEDecode connected to the saved images; it falls back to the first sampler found.
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
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 (PNG: tEXt "parameters", JPEG/WebP: EXIF UserComment)
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 (PNG: iTXt "imagemetahub_data", JPEG/WebP: EXIF ImageDescription)
{
"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_PATHenvironment 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_pathempty)
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.