FoodMapper
Match free-text food descriptions to standardized reference databases using on-device ML models powered by MLX on Apple Silicon.
Built for nutrition researchers on Apple Silicon. Your data stays on your Mac. Optional cloud verification available for research workflows.
What it does
Run the entire matching pipeline on your Mac's GPU via MLX. No accounts, no telemetry. Optional cloud verification for research workflows.
On-Device ML Matching
Run the full matching pipeline on your Mac's GPU via MLX. No accounts, no telemetry. An optional hybrid mode adds cloud-based verification for research validation.
Guided Review Workflow
Confirm, reject, or override matches with keyboard-driven review. Auto-advancing guided mode works through items needing attention.
Built-In Databases
FooDB (9,913 items) and DFG2 (256 items) ship with pre-computed embeddings. Import your own CSV or TSV files too.
Behind the Research
Explore the methods from "From Diet to Molecules" with an interactive showcase and live matching demo.
How it works
Load your data
Drag in a CSV or TSV with food descriptions. Pick your description column and target database.
Match
Click Match and the embedding model runs on your GPU. Semantic similarity finds the best database entries for each food item.
Review and export
Guided review walks through results. Confirm, reject, or override each match. Export with original columns plus match metadata.
