CyberRealistic Pony Model
🚫 Limitations
May produce content that could be considered sensitive; use responsibly.
Some prompts involving abstract or non-pony content may not perform as well due to the model's specialized training.
Lighting and textures may occasionally be too clean or smooth depending on sampling choices.
✅ License
This model is distributed under the CreativeML Open RAIL++-M License, which allows commercial and non-commercial use, with proper credit and no malicious usage.
Exactly! Embedding metadata in PNGs is a fantastic way to demonstrate transparency and reproducibility in AI image generation. It shows:
🔍 Transparency: Users can see exactly what parameters were used - no "black box" mystery about how an image was created.
🔄 Reproducibility: Anyone can extract the seed, prompt, and settings to recreate similar results or iterate on the concept.
📚 Learning Tool: People can examine successful generations to understand what prompts, settings, and techniques work well.
🛠️ Workflow Integration: Other tools and scripts can read the metadata to automatically import settings or build generation pipelines.
📋 Documentation: The embedded data serves as permanent documentation that travels with the image file itself.
It's a great practice that builds trust and enables the community to learn from each other's work. Plus, it's especially valuable for AI art where the creative process involves so many technical parameters that affect the final result.
The fact that the metadata persists in the PNG file means users can share images and others can immediately see "how it was made" - much more useful than trying to guess or reverse-engineer the settings!
Looking at your code, I'll integrate the metadata saving functionality and add the requested features. Here's the updated version with PNG metadata, seed slider, example prompts, and enhanced status display:Here are the key changes I've integrated into your CyberRealistic Pony Generator:
🆕 New Features Added:
1. PNG Metadata Embedding
- Added
add_metadata_and_save() function that embeds all generation parameters into PNG files
- Includes: prompt, negative prompt, model, VAE, sampler, steps, CFG scale, strength, seed, and timestamp
- Images are saved with metadata before being returned
2. Enhanced Status Display
format_status_with_metadata() creates detailed status messages showing:
- Generation time and dimensions
- Used prompt (truncated if long)
- Negative prompt
- Seed, steps, CFG scale
- Strength (for img2img)
- Status window now shows 6 lines of detailed info
3. Seed Slider
- Replaced the number input with proper sliders for both tabs
- Range: -1 to 2,147,483,647 (max int32)
- -1 generates random seeds automatically
- Seeds are properly handled and displayed in status
4. Example Prompts System
- Added 8 diverse example prompts covering different styles
- "🎲 Random Example" buttons on both tabs
- Prompts include anime, cyberpunk, fantasy, anthropomorphic, and more themes
5. Improved UI Layout
- Better organized prompt input with example buttons
- Enhanced accordion sections
- More detailed status display areas
- Professional icons and formatting
🔧 Technical Improvements:
- Random Seed Generation: Proper random seed handling when -1 is selected
- Metadata Persistence: All generation parameters saved to PNG metadata
- Status Formatting: Rich, multi-line status information
- Error Handling: Better error messages and fallbacks
- Memory Management: Same efficient GPU memory handling
The generated images now contain all the metadata you specified, and users can see detailed generation information in the status window, making it easy to reproduce or modify generations.
