Eye: On-device Image Understanding
On-device image understanding that scores any image in one call: best-frame pick, per-axis quality, scene, tags, and a perceptual embedding for burst dedupe.
Eye scores any image in a single call. It returns a best-frame pick score, per-axis quality (interestingness, composition, thumbnail quality, subject clarity, aesthetic), a scene class, tags and concepts, an optional identity-blind face analysis, and a perceptual embedding used for near-duplicate burst dedupe. Use it to pick the best photo from a burst, the best frame from a video, or the best thumbnail from a clip.
Use cases
Best-of selection
Pick the best photo from a burst, the best frame from a video, or the best thumbnail from a clip.
Identity-blind face scoring
Score faces as visual content (geometry, expression, attention) for a best headshot, no blinks, eyes on camera. It does not perform face recognition.
What it does
- One call: pick score, quality axes, scene class, tags and concepts
- Perceptual embedding for near-duplicate burst dedupe
- Optional
EyeFacesmodule (+22 MB), identity-blind by design
Specs
- Size
- ~27 MB core, +22 MB optional face module
- Backbone
- TinyCLIP-40M (distilled from a LAION-400M teacher)
- Platform
- Apple (Swift); Android and web planned
Early access
Tell us what you are building and we will get you set up.