Mother-of-Pearl Inlay
Your photo, rebuilt piece by piece from iridescent shell and lacquer.
What it does
Reconstructs your photo from color-matched mother-of-pearl shell and polished lacquer in the authentic Korean najeon-chilgi craft tradition.
When to use it
- Turn a portrait into an heirloom-style mother-of-pearl lacquer artwork
- Give a landscape or cityscape the look of a handcrafted Korean lacquer panel
- Create a luxurious, iridescent piece for prints, covers, or gallery walls
- Transform a pet or object photo into an ornamental shell-inlay craft object
- Make a striking, traditional-art gift that keeps a recognizable likeness
- Produce a museum-quality decorative treatment while preserving original colors
When not to use it
- Keeping the smooth, photographic texture of the original image
- Realistic edits where no stylization should be visible
- Adding new ornaments, motifs, or decorations not in the source photo
- Tiny low-resolution photos where shell detail cannot be resolved
How it works
Upload any photo and the model rebuilds it as a najeon-chilgi lacquer-inlay artwork. It reads your composition, brightness, and color areas, then translates each one into color-matched mother-of-pearl, abalone shell, tinted nacre, and polished lacquer. Discrete cut shell pieces, engraved hairlines, and wire accents follow your original contours, so the subject and scene stay fully recognizable while the entire surface becomes handcrafted shell and lacquer.
Updates
- v1Jun 21, 2026
Initial release
Specifications
- Approach
- Material transformation, not a color redesign — your image is rebuilt from shell and lacquer.
- Stylization
- Color-matched mother-of-pearl tessellation, polished lacquer depth, engraved hairlines, brass and silver wire accents.
- What stays
- Composition, crop, pose, identity, color palette, brightness hierarchy, and background layout.
- What changes
- Surface material, shine, tessellation, and craft texture — every area becomes shell and lacquer.
- Ideal source
- Clear, well-lit photos with readable shapes and color areas.
- Maximum input
- Up to 25 MP per image
- Supported formats
- JPEG, PNG, HEIC
- Output format
- PNG — preserves the fine shell seams and lacquer reflections without compression artifacts.
- Pricing
- 3 credits per image
Frequently asked questions
Will it still look like the original photo?
Yes. The model preserves your composition, framing, pose, proportions, and likeness. It changes the material your image is made of — translating every surface into shell and lacquer — without redesigning the subject or scene.
Does it change my original colors?
No. This is a material transformation, not a palette redesign. Every color area is rebuilt with matching tinted nacre, so blue skies stay blue, skin stays warm, and dark areas stay dark. The shell and lacquer change the surface, not your color identity.
Will it add decorations like flowers or dragons?
No. It does not invent new ornaments, motifs, borders, or extra subjects. It only reconstructs what is already in your photo from color-matched mother-of-pearl and polished lacquer.
What kind of photo works best?
Clear, well-lit images with readable shapes and distinct color areas work best, since the shell tessellation follows your contours. Higher-resolution photos let the fine shell seams and engraved details show more clearly.
Will my photo be cropped or reframed?
No. The crop, framing, camera angle, and aspect relationships of your original are kept intact. The model never zooms, reframes, or repositions the subject.
Can I use the result commercially?
Yes — generated images on upsa are yours to use for personal and commercial purposes. We recommend you keep the consent and rights to the source photo as well, since the output preserves the identity in it.
How long are my photos stored?
Source uploads and generated results are stored for 48 and then automatically deleted from upsa's storage. We don't train any model on your photos.
AI results vary
Each generation uses a different random seed, so your result may not exactly match the example shown. If the first try doesn't fit what you had in mind, run it again — output differs noticeably between runs.
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