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A.I Joe
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# ComfyUI-Metadata-Extractor
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# ComfyUI Metadata Extractor
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A powerful custom node for ComfyUI that extracts metadata from images, videos, and audio files generated by ComfyUI.
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## Features
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✅ **Multiple File Format Support:**
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- **Images:** PNG, JPEG
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- **Videos:** MP4, AVI, MOV, MKV, WebM
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- **Audio:** FLAC, MP3, WAV, OGG
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✅ **Comprehensive Metadata Extraction:**
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- Positive prompt
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- Negative prompt
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- Seed
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- Steps
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- CFG scale
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- Sampler name
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- Scheduler
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- Width/Height/Dimensions
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- Batch size
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- FPS (for videos)
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- Full workflow JSON
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✅ **Two Node Variants:**
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1. **MetadataExtractor (File)** - Works with file paths
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2. **ImageMetadataExtractor (Image)** - Works with IMAGE tensor inputs
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## Installation
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### Method 1: Manual Installation
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1. Navigate to your ComfyUI custom_nodes directory:
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```bash
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cd ComfyUI/custom_nodes/
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```
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2. Create a new folder for the node:
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```bash
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mkdir ComfyUI-Metadata-Extractor
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cd ComfyUI-Metadata-Extractor
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```
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3. Copy these files into the folder:
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- `__init__.py`
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- `metadata_extractor_node.py`
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4. Install required dependencies:
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```bash
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pip install pillow mutagen
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```
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5. Restart ComfyUI
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### Method 2: Git Clone (if you create a repo)
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```bash
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cd ComfyUI/custom_nodes/
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git clone https://github.com/yourusername/ComfyUI-Metadata-Extractor.git
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cd ComfyUI-Metadata-Extractor
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pip install -r requirements.txt
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```
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## Usage
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### MetadataExtractor (File Path)
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1. Add the **"Extract Metadata (File)"** node to your workflow
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2. Connect a file path string to the `file_path` input
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3. All metadata outputs will be available as separate connections:
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- `positive_prompt` (STRING)
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- `negative_prompt` (STRING)
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- `seed` (STRING)
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- `steps` (STRING)
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- `width` (INT)
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- `height` (INT)
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- `batch_size` (INT)
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- `cfg` (FLOAT)
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- `sampler_name` (STRING)
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- `scheduler` (STRING)
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- `full_workflow_json` (STRING)
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### ImageMetadataExtractor (Image Input)
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1. Add the **"Extract Metadata (Image)"** node to your workflow
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2. Connect an IMAGE output to the `image` input
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3. Optionally provide the source file path for full metadata extraction
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4. Outputs:
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- `prompt` (STRING)
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- `negative_prompt` (STRING)
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- `width` (INT)
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- `height` (INT)
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- `metadata_json` (STRING)
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## Example Workflows
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### Example 1: Extract and Reuse Prompts
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Load an image → Extract Metadata (File) → Connect `positive_prompt` to CLIPTextEncode → Generate similar image
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### Example 2: Batch Processing
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Load multiple images → Extract Metadata → Save prompts to text files → Analyze generation patterns
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### Example 3: Video Analysis
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Load video path → Extract Metadata (File) → Get FPS, dimensions, and generation settings
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## Technical Details
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### How It Works
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**For PNG Images:**
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- Reads metadata from PNG `info` dictionary
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- Extracts `workflow` and `prompt` JSON data
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- Parses node structure to find generation parameters
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**For Videos:**
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- Uses ffprobe to read video metadata
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- Looks for ComfyUI metadata in format tags
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- Extracts dimensions and FPS from stream info
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**For Audio:**
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- Uses mutagen library to read audio tags
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- Searches for JSON metadata in comment/description fields
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- Preserves generation parameters
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### Metadata Structure
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ComfyUI stores metadata in a node-based JSON structure. This node intelligently parses:
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- KSampler nodes for sampling parameters
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- CLIPTextEncode nodes for prompts
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- EmptyLatentImage nodes for dimensions
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- Custom metadata fields
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## Dependencies
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- Python 3.8+
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- PIL/Pillow (image handling)
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- mutagen (audio metadata)
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- ffprobe (video metadata, optional but recommended)
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## Troubleshooting
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**"No metadata found"**
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- Ensure the file was generated by ComfyUI with metadata saving enabled
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- Check that the file hasn't been re-encoded or processed by other tools
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**Video metadata extraction fails**
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- Install ffmpeg/ffprobe: `apt-get install ffmpeg` or download from ffmpeg.org
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- Ensure ffprobe is in your system PATH
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**Audio metadata extraction fails**
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- Install mutagen: `pip install mutagen`
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- Some audio formats may not preserve metadata after encoding
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## Limitations
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- Only extracts metadata that was embedded during generation
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- Images downloaded from web sources typically have metadata stripped
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- Video metadata preservation depends on the encoder settings
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- Some file formats have limited metadata support
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## Future Enhancements
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- [ ] Support for more video formats
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- [ ] Batch processing multiple files
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- [ ] Export metadata to CSV/JSON files
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- [ ] Metadata comparison between files
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- [ ] Automatic prompt reconstruction from partial data
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## Contributing
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Feel free to submit issues, feature requests, or pull requests!
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## License
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MIT License - Free to use and modify
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## Credits
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Created for the ComfyUI community. Special thanks to the ComfyUI developers and the AI art community.
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@@ -0,0 +1,8 @@
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"""
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ComfyUI Metadata Extractor
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Extracts metadata from PNG images and MP4/video files generated by ComfyUI
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"""
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from .metadata_extractor import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS
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__all__ = ['NODE_CLASS_MAPPINGS', 'NODE_DISPLAY_NAME_MAPPINGS']
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"""
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ComfyUI Metadata Extractor - Improved Version
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Extracts metadata from PNG images and MP4/video files
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Now properly extracts: prompts, seed, steps, cfg, sampler, scheduler
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"""
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import json
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import os
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import subprocess
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import folder_paths
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try:
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from PIL import Image
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except ImportError:
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import PIL.Image as Image
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class MetadataExtractorImproved:
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"""
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Extracts metadata from ComfyUI-generated files
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Properly parses seed, steps, cfg from the prompt structure
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"""
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def __init__(self):
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self.output_dir = folder_paths.get_output_directory()
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self.input_dir = folder_paths.get_input_directory()
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@classmethod
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def INPUT_TYPES(cls):
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input_dir = folder_paths.get_input_directory()
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files = []
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try:
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files = [f for f in os.listdir(input_dir)
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if os.path.isfile(os.path.join(input_dir, f)) and
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f.lower().endswith(('.png', '.jpg', '.jpeg', '.mp4', '.avi', '.mov', '.mkv', '.webm'))]
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except:
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pass
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return {
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"required": {},
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"optional": {
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"video": ("IMAGE",),
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"file_path": ("STRING", {
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"default": "",
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"multiline": False,
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"placeholder": "Full path to file"
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}),
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"filename": ([""] + sorted(files), {
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"default": ""
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}),
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}
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}
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RETURN_TYPES = ("STRING", "STRING", "INT", "INT", "FLOAT", "STRING", "STRING", "STRING", "STRING")
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RETURN_NAMES = ("positive_prompt", "negative_prompt", "seed", "steps", "cfg", "sampler", "scheduler", "metadata_json", "file_info")
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FUNCTION = "extract"
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CATEGORY = "utils/metadata"
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OUTPUT_NODE = False
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def find_video_file_in_workflow(self, video_tensor):
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"""Try to find source video file"""
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possible_locations = [self.input_dir, self.output_dir]
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video_files = []
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for location in possible_locations:
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if not os.path.exists(location):
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continue
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try:
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for f in os.listdir(location):
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if f.lower().endswith(('.mp4', '.avi', '.mov', '.mkv', '.webm')):
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full_path = os.path.join(location, f)
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video_files.append((full_path, os.path.getmtime(full_path)))
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except:
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pass
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video_files.sort(key=lambda x: x[1], reverse=True)
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if video_files:
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print(f"[Metadata] 💡 Found: {os.path.basename(video_files[0][0])}")
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return video_files[0][0]
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return None
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def extract_video_metadata(self, file_path):
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"""Extract metadata from video files using ffprobe"""
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try:
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cmd = ['ffprobe', '-v', 'quiet', '-print_format', 'json',
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'-show_format', '-show_streams', file_path]
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result = subprocess.run(cmd, capture_output=True, text=True, timeout=10)
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if result.returncode != 0:
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return None
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video_info = json.loads(result.stdout)
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tags = video_info.get('format', {}).get('tags', {})
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print(f"[Metadata] Video tags: {list(tags.keys())}")
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metadata = {}
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metadata_fields = ['comment', 'Comment', 'description', 'Description',
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'workflow', 'Workflow', 'prompt', 'Prompt']
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for field in metadata_fields:
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if field in tags:
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try:
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parsed = json.loads(tags[field])
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metadata[field.lower()] = parsed
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print(f"[Metadata] ✅ Found '{field}' tag")
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except:
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metadata[field.lower()] = tags[field]
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# Get video properties
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for stream in video_info.get('streams', []):
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if stream.get('codec_type') == 'video':
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metadata['video_width'] = stream.get('width', 0)
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metadata['video_height'] = stream.get('height', 0)
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fps_str = stream.get('r_frame_rate', '0/1')
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try:
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fps_num, fps_den = map(int, fps_str.split('/'))
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metadata['video_fps'] = fps_num / fps_den if fps_den else 0
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except:
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metadata['video_fps'] = 0
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metadata['video_duration'] = float(stream.get('duration', 0))
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break
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return metadata if metadata else None
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except FileNotFoundError:
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print("[Metadata] ❌ ffprobe not found! Install ffmpeg")
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return None
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except Exception as e:
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print(f"[Metadata] Error: {e}")
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return None
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def extract_png_metadata(self, file_path):
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"""Extract metadata from PNG files"""
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try:
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img = Image.open(file_path)
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metadata = {}
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if hasattr(img, 'info'):
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if 'workflow' in img.info:
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try:
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metadata['workflow'] = json.loads(img.info['workflow'])
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except:
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pass
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if 'prompt' in img.info:
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try:
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metadata['prompt'] = json.loads(img.info['prompt'])
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except:
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pass
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return metadata if metadata else None
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except Exception as e:
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print(f"[Metadata] Error reading PNG: {e}")
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return None
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def parse_comfyui_metadata(self, metadata):
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"""Parse metadata and extract ALL parameters"""
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result = {
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'positive_prompt': "",
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'negative_prompt': "",
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'seed': 0,
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'steps': 0,
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'cfg': 0.0,
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'sampler': "",
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'scheduler': "",
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'metadata_json': "{}",
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'file_info': ""
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}
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try:
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# Get prompt data (node-based structure)
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prompt_data = None
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if 'prompt' in metadata:
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prompt_data = metadata['prompt']
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elif 'comment' in metadata and isinstance(metadata['comment'], dict):
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prompt_data = metadata['comment']
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if not prompt_data:
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result['metadata_json'] = json.dumps(metadata, indent=2)
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return result
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print(f"[Metadata] Parsing {len(prompt_data)} nodes...")
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# Track what we've found
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positive_found = False
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negative_found = False
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# Iterate through all nodes
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for node_id, node_data in prompt_data.items():
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if not isinstance(node_data, dict):
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continue
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inputs = node_data.get('inputs', {})
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class_type = node_data.get('class_type', '')
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# Extract prompts
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if class_type in ['CLIPTextEncode', 'CLIPTextEncodeSDXL', 'CLIPTextEncodeFlux']:
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text_content = inputs.get('text', '')
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if text_content:
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if not positive_found:
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result['positive_prompt'] = text_content
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positive_found = True
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print(f"[Metadata] ✅ Positive prompt")
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elif not negative_found:
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result['negative_prompt'] = text_content
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negative_found = True
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print(f"[Metadata] ✅ Negative prompt")
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# Extract seed from RandomNoise node
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if class_type == 'RandomNoise':
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if 'noise_seed' in inputs:
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result['seed'] = int(inputs['noise_seed'])
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print(f"[Metadata] ✅ Seed: {result['seed']}")
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elif isinstance(inputs.get('noise_seed'), list):
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# Handle array format: ["get", ["123", 0]]
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try:
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result['seed'] = int(inputs['noise_seed'][0])
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except:
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pass
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# Extract sampler
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if class_type == 'KSamplerSelect':
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sampler_name = inputs.get('sampler_name', '')
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if sampler_name:
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result['sampler'] = sampler_name
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print(f"[Metadata] ✅ Sampler: {sampler_name}")
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# Extract steps and cfg from scheduler nodes
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if class_type in ['LTXVScheduler', 'BasicScheduler', 'KScheduler']:
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if 'steps' in inputs:
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result['steps'] = int(inputs['steps'])
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print(f"[Metadata] ✅ Steps: {result['steps']}")
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# Extract CFG from guider nodes
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if class_type in ['CFGGuider', 'DualCFGGuider']:
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if 'cfg' in inputs:
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result['cfg'] = float(inputs['cfg'])
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print(f"[Metadata] ✅ CFG: {result['cfg']}")
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# Store full metadata
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result['metadata_json'] = json.dumps(metadata, indent=2)
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# Create file info
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info_parts = []
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if 'video_width' in metadata:
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info_parts.append(f"{metadata['video_width']}x{metadata['video_height']}")
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if 'video_fps' in metadata:
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info_parts.append(f"{metadata['video_fps']:.2f} FPS")
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if 'video_duration' in metadata:
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info_parts.append(f"{metadata['video_duration']:.2f}s")
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result['file_info'] = " | ".join(info_parts) if info_parts else "PNG Image"
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except Exception as e:
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print(f"[Metadata] Error parsing: {e}")
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import traceback
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traceback.print_exc()
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return result
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def extract(self, video=None, file_path="", filename=""):
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"""Main extraction function"""
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actual_path = None
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if file_path and os.path.exists(file_path):
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actual_path = file_path
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elif filename:
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actual_path = os.path.join(self.input_dir, filename)
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elif video is not None:
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actual_path = self.find_video_file_in_workflow(video)
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if not actual_path or not os.path.exists(actual_path):
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return ("", "", 0, 0, 0.0, "", "", "{}", "File not found")
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print(f"[Metadata] 📂 Processing: {os.path.basename(actual_path)}")
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ext = os.path.splitext(actual_path)[1].lower()
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metadata = None
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if ext in ['.png', '.jpg', '.jpeg']:
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metadata = self.extract_png_metadata(actual_path)
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elif ext in ['.mp4', '.avi', '.mov', '.mkv', '.webm']:
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metadata = self.extract_video_metadata(actual_path)
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else:
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return ("", "", 0, 0, 0.0, "", "", "{}", f"Unsupported: {ext}")
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if not metadata:
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return ("", "", 0, 0, 0.0, "", "", "{}", "No metadata found")
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result = self.parse_comfyui_metadata(metadata)
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return (
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result['positive_prompt'],
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result['negative_prompt'],
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result['seed'],
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result['steps'],
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result['cfg'],
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result['sampler'],
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result['scheduler'],
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result['metadata_json'],
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result['file_info']
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)
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NODE_CLASS_MAPPINGS = {
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"MetadataExtractorImproved": MetadataExtractorImproved
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"MetadataExtractorImproved": "📹 Extract Metadata (PNG/Video)"
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}
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@@ -0,0 +1,2 @@
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Pillow>=9.0.0
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mutagen>=1.45.0
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Reference in New Issue
Block a user