Files
LuqP2-ImageMetaHub-ComfyUI-…/README.md
T
LuqP2 f6bdd59fdc Add workflow auto-extraction and multi-format metadata saving
Auto-detect sampler/model/vae/prompts/loras with concrete node lists and multi-sampler heuristic
Switch to None sentinels for overrides and add filename placeholders + sanitization
Add JPEG/WebP metadata via EXIF (piexif) and update README/docs

Implement UI preview structure for ComfyUI frontend, matching Save Image behavior.
2025-12-20 21:16:27 -03:00

194 lines
6.1 KiB
Markdown

# 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)
1. Navigate to your ComfyUI custom nodes directory:
```bash
cd ComfyUI/custom_nodes
```
2. Clone this repository:
```bash
git clone https://github.com/LuqP2/ImageMetaHub-ComfyUI-Save.git
```
3. Install dependencies:
```bash
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 piexif>=1.1.3`
4. Restart ComfyUI
## Usage
### Quick Start
1. Add "MetaHub Save Image" node to your workflow
2. Connect the `images` output from your decoder/sampler
3. 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 WebP
- `quality`: 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:
```bash
# 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)
```json
{
"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](https://github.com/LuqP2/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](https://github.com/LuqP2/Image-MetaHub) ecosystem.