Magic Layers
Separate any image into editable layers
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What is Magic Layers?
Magic Layers is an AI tool that automatically separates a single flat PNG or JPEG image into individual editable layers—extracting text, subjects, decorations, and backgrounds as separate transparent PNGs with names, descriptions, and position data. Users can guide the separation by describing what to extract and download layers ready for use in Photoshop, Figma, Canva, or game engines.
Magic Layers pricing
Pricing model: Paid
Credits-based (2 credits per image layer generated); no explicit monetary pricing or free tier shown on page
Magic Layers pros
- Automatically separates images into independently editable, named layers with position data—no manual masking required
- Works without source files; AI infers separation from pixels alone, enabling re-editing of finished images
- Layers import directly into Photoshop, Figma, Canva, and game engines as transparent PNGs with proper alpha channels
- Flexible control: specify what to separate ('all people', 'clothes only') and choose output count (2–15 layers)
Magic Layers cons
- Pricing is credit-based with no conversion rate shown; actual USD cost per operation is unclear
- Limited to flat PNG/JPEG files up to 10 MB with minimum 512×512 px; cannot handle PSD, vector, or multi-layer files
- Layer quality and count unpredictable without testing; charged per image actually returned, creating variable costs
Frequently asked questions about Magic Layers
How is Magic Layers different from background removal?
Background removal extracts one subject on transparent background; Magic Layers separates every major element (text, decorations, subject, background) into independent layers you can move, replace, or restyle individually.
What format do the layers come in?
Each layer is a transparent PNG with clean alpha channel, auto-named and described, with position and stacking order preserved. They work in Photoshop, Figma, Canva, slide decks, and game engines.
Do you need the original project file?
No. Magic Layers infers separation from the pixels alone, so it works on any finished image, even if the source file is lost.
What are common use cases?
Marketing creative variations, social media recomposition, presentation assets, game and UI prototyping, and e-commerce product imagery.