ComfyUI_MetaSaver

ComfyUI MetaSaver

A powerful ComfyUI custom node for saving images and videos with flexible custom metadata fields embedded directly in the file.

Features

• Up to 10 Metadata Fields: Standard version with 10 optional metadata slots
• Up to 20 Metadata Fields: Dynamic version with 20 optional metadata slots
• Custom Field Names: Give each metadata field a custom name
• Flexible Input Types: Supports ANY type - strings, integers (seeds), floats (CFG), and more
• PNG & Video Metadata Embedding: Custom data saved in PNG files or video container tags
• Workflow Preservation: Maintains standard ComfyUI workflow metadata
• Multiple Formats: Metadata saved both as structured JSON and individual fields
• All Optional: Only fill in the fields you need - empty fields are ignored
• Video Output: Save MP4 (H.264) or WEBM (VP9) video from image frame batches

Why MetaSaver?

Unlike standard save nodes, MetaSaver lets you:

• Save seeds from KSampler nodes
• Store positive and negative prompts
• Record model names, LoRA weights, CFG values
• Add any custom text or numbers you want to track
• Name your fields exactly how you want them
• Embed metadata in videos as container-level tags

Perfect for tracking generation parameters, comparing outputs, or sharing images and videos with full context!

Installation

Method 1: ComfyUI Manager (Recommended)

1. Open ComfyUI Manager
2. Search for "MetaSaver"
3. Click Install

Method 2: Manual Installation

1. Navigate to your ComfyUI custom_nodes directory:

   cd ComfyUI/custom_nodes/
   

2. Clone this repository:

   git clone https://github.com/SorenWeile/ComfyUI_MetaSaver.git
   

3. Restart ComfyUI

Usage

Saving Images

1. Add the "Save Image with Custom Metadata" node to your workflow

2. You'll see pairs of inputs for metadata (10 pairs in standard, 20 in dynamic version):

   • meta_name_0: Name of first field (e.g., "seed")
   • meta_value_0: Value to save (e.g., connect from KSampler seed output)
   • meta_name_1: Name of second field (e.g., "positive_prompt")
   • meta_value_1: Value to save
   • ... and so on

3. Fill in only the metadata fields you want to use (empty ones are ignored)

4. Connect your image output to the images input

5. Run your workflow!

Saving Videos

1. Add the "Save Video with Custom Metadata" node to your workflow
2. Connect an IMAGE batch (your video frames) to the images input
3. Set fps, choose format (mp4 or webm), and fill in any metadata fields
4. Run your workflow — the video is saved to your ComfyUI output folder

A typical video workflow: KSampler → VAE Decode → Save Video with Custom Metadata

Or for multi-frame video: connect the image batch output from a video model directly.

Note: All metadata fields are optional - you can use as many or as few as you need!

Reading Metadata

From PNG images:

• ComfyUI: Drag the image back into ComfyUI to see all metadata
• Python:

  from PIL import Image
  img = Image.open("your_image.png")
  metadata = img.info.get("custom_metadata")
  print(metadata)
  

• ExifTool: exiftool your_image.png

From MP4/WEBM videos:

• Command line: ffprobe -v quiet -print_format json -show_format your_video.mp4
• Python:

  import av, json
  with av.open("your_video.mp4") as container:
      custom = json.loads(container.metadata.get("custom_metadata", "{}"))
      print(custom)
  

• ExifTool: exiftool your_video.mp4

The metadata JSON structure is the same for both images and videos:

{
  "seed": 12345,
  "positive_prompt": "a beautiful landscape",
  "cfg_scale": 7.5,
  "model_name": "sd_xl_base_1.0"
}

Node Variants

MetaSaver (Standard)

Saves a PNG image with 10 optional metadata field pairs (meta_name_0 through meta_name_9). Perfect for most use cases.

MetaSaverDynamic (Advanced)

Saves a PNG image with *