Find coherent market lots
The camera groups nearby, visually similar fish while keeping separate trays apart. A tray can contain many fish and still have one session ID.
Research preview · iOS first
FreshFish is building an on-device registry for fish markets. One visually coherent tray or plate gets one local ID—even when the camera sees it again and again.
One lot, one IDRepresentative crop stays local until the lot is stable and cloud identification is eligible.
Actual system flow
The phone does the repeated-frame work. The backend receives an isolated representative only when the product rules allow it.
The camera groups nearby, visually similar fish while keeping separate trays apart. A tray can contain many fish and still have one session ID.
Screen geometry, appearance and session history prevent thousands of repeated frames from becoming thousands of records.
A qualified local detector may make one stable representative eligible for cloud screening. The result remains a candidate until a person confirms it.
What the app must not imply
An image may support future research, but freshness depends on handling, temperature, smell, texture and other evidence the camera cannot establish.
Published mercury observations describe sampled populations and places. They are not a reading of the fish in front of the camera.
Cloud output is an uncalibrated screening candidate. Scientific identity and enrichment stay locked until a reviewed catalogue match is confirmed.
Calories and omega-3 values come from source-versioned reference datasets for a confirmed species and preparation—not from visual estimation.
Privacy architecture
Live frames, recorded-market videos and audio are not uploaded. Training evidence has a separate, explicit contribution control. Local cache erasure and cloud-account deletion are separate actions because they remove different data.