Get-Seed: Extract Generation Seeds from Stable Diffusion Images #

Introduction #

When working with stable diffusion models and training custom LoRAs, tracking the seed values used to generate images is crucial for reproducibility. The Get-Seed PowerShell function provides a simple way to extract the ss_seed value from the metadata of .safetensors files, allowing you to recover the exact seed used for any generation.

This tool is particularly valuable when:

• Recreating specific images with the same parameters
• Building datasets for LoRA training where consistent seeds are needed
• Debugging generation issues by comparing identical seeds across different model versions
• Documenting and organizing your image generation workflow

How Seed Values Work in Stable Diffusion #

In stable diffusion, the seed value initializes the random noise pattern that transforms into your final image. Using the same seed with identical parameters (prompt, model, sampler, steps) will produce the same or very similar results. This deterministic property makes seeds extremely valuable for:

1. Reproducibility: Recreate the same image even after system restarts
2. Parameter Testing: Change one variable while keeping the seed constant to isolate effects
3. LoRA Training: Ensure consistency across training generations
4. Style Matching: Find seeds that work well with particular styles or subjects

The Get-Seed function lets you extract this valuable information from existing images saved in the .safetensors format.

Usage Instructions #

Basic Function Definition #

The core function extracts the seed value from a safetensors file:

<#
  Retrieves the 'ss_seed' value from the metadata of a .safetensors file.

  The Get-Seed function takes a file path as input and uses Python to extract the 'ss_seed' value from the metadata of a .safetensors file.
  It returns the 'ss_seed' value if found, otherwise it returns 'Not found'.

.EXAMPLE
  $seedValue = Get-Seed .\path\to\your\file.safetensors
#>
function Get-Seed {
  param (
    [Parameter(Mandatory = $true, Position = 0)]
    [string]$filePath
  )

  $filePath = $filePath -replace '\\', '\\\\'
  $pythonCommand = "import safetensors, json; print(json.loads(safetensors.safe_open('" + $filePath + "', 'np').metadata().get('ss_seed', 'Not found')))"
  $ssSeed = python -c $pythonCommand
  return $ssSeed
}

Adding to Your PowerShell Profile #

To make this function available in any PowerShell session, add it to your PowerShell profile:

1. Open PowerShell and run: notepad $PROFILE
2. Add the function definition to your profile file
3. Save and restart PowerShell

Installation Requirements #

Before using this function, ensure you have the required Python dependencies:

pip install safetensors

For a complete dataset management solution, consider installing our related tools:

• Extract-Metadata for comprehensive metadata extraction
• Inspect-LoRA for analyzing LoRA models

Common Usage Scenarios #

Extracting Seeds for LoRA Training #

When preparing datasets for LoRA training, it’s often useful to extract and document the seeds of your training images:

# Extract seeds from all safetensors files in a directory
$trainingDir = "C:\training_data"
$seedReport = @()

Get-ChildItem -Path $trainingDir -Filter "*.safetensors" | ForEach-Object {
    $seedInfo = [PSCustomObject]@{
        FileName = $_.Name
        Seed = Get-Seed $_.FullName
    }
    $seedReport += $seedInfo
}

# Export the seed information to CSV
$seedReport | Export-Csv -Path "$trainingDir\seed_report.csv" -NoTypeInformation

This creates a comprehensive record of all seeds used in your training dataset.

Batch Generation with Successful Seeds #

Once you’ve identified seeds that produce good results, you can use them for batch generation with different parameters:

# Example of using extracted seeds for new generations
$goodSeeds = @(42, 12345, 67890) # Seeds extracted with Get-Seed
$prompts = @("a wolf", "a fox", "a raccoon")

foreach ($seed in $goodSeeds) {
    foreach ($prompt in $prompts) {
        # Command to generate new images with the same seed
        # Replace with your actual generation command
        # python generate.py --prompt "$prompt" --seed $seed --output "./output/$prompt-$seed.png"
        Write-Host "Generating: $prompt with seed $seed"
    }
}

Recovering Lost Generation Parameters #

If you have a particularly successful image but lost the generation parameters, the seed can help you recreate similar results:

# Extract seed from a favorite image
$favoriteSeed = Get-Seed "C:\my_best_generation.safetensors"
Write-Host "Your favorite image was generated with seed: $favoriteSeed"

# Now you can use this seed in your generation UI of choice

Advanced Techniques #

Combining with Other Metadata Tools #

For more comprehensive metadata extraction, combine Get-Seed with other metadata tools like Extract-Metadata:

# Extract seed and other metadata
$file = "C:\image.safetensors"
$seed = Get-Seed $file
$fullMetadata = Extract-Metadata $file

Write-Host "Seed: $seed"
Write-Host "Full Generation Parameters:"
$fullMetadata | Format-List

Filtering Images by Seed Value #

You can use the extracted seeds to organize or filter your image collection:

# Find all images generated with a specific seed
$targetSeed = "42"
$matchingFiles = @()

Get-ChildItem -Path "C:\image_collection" -Filter "*.safetensors" -Recurse | ForEach-Object {
    $currentSeed = Get-Seed $_.FullName
    if ($currentSeed -eq $targetSeed) {
        $matchingFiles += $_.FullName
    }
}

Write-Host "Found $($matchingFiles.Count) images with seed $targetSeed"
$matchingFiles | ForEach-Object { Write-Host $_ }

Troubleshooting #

If you encounter issues with Get-Seed, check the following common problems:

1. Python Not Found: Ensure Python is in your PATH and accessible from PowerShell
2. Missing Safetensors Package: Run pip install safetensors to install the required Python package
3. File Format Issues: Confirm your file is actually a .safetensors file, not just renamed
4. No Metadata Present: Some images may not have seed information stored if it wasn’t saved during generation
5. Path Escaping Problems: If you have unusual characters in your file path, try using the absolute path

For files without seed information, you might need to review the generation software settings to ensure metadata saving is enabled.

Conclusion #

The Get-Seed function is a simple yet powerful tool for working with stable diffusion generations. By extracting seed values, you gain greater control over your image generation workflow and can more effectively:

• Document your generation process
• Reproduce successful results
• Build consistent training datasets
• Share exact generation parameters with others

While a seed alone doesn’t capture all generation parameters, it’s a critical piece of information for reproducibility. When combined with other metadata tools like Extract-Metadata and Inspect-LoRA, you have a comprehensive toolkit for managing your stable diffusion assets.

For maximum effectiveness, incorporate seed extraction into your standard workflow, especially when preparing datasets for LoRA training or when creating image collections you might want to revisit later.