AI meal photo logging uses computer vision to guess foods and portion sizes from a picture, then asks you to confirm or edit before the entry lands in your diary—faster than typing every ingredient when the plate is mixed or restaurant-sized.
Accuracy depends on lighting, angle, and how hidden sauces or oils are; the workflow works best when you treat the first guess as a draft, not a lab analysis. Ohga Copilot can log from photos and align portions with your protein and calorie targets when you review the suggestion.
What the model typically detects
Clear top-down or forty-five degree shots of distinct items—chicken, rice, salad, fruit—map better than stew, burritos, or deep bowls where calories hide under cheese or dressing. Models infer relative volume; they do not weigh food. Pair photos with a quick sanity check against hunger and weekly trends, not single-meal perfection.
When to edit or skip the photo
- Buffets, shared platters, and sauce-heavy dishes—edit portions upward or log a template meal.
- Homemade recipes—save a custom meal once, then reuse instead of re-photographing.
- Supplements and drinks—often faster by voice or manual entry.
Photo vs barcode
Barcodes excel on packaged foods with stable labels; photos excel on cooked plates and dining out. Read barcode vs photo meal logging for when to use each. For habit tips, see photo meal logging tips that work and meal logging with photos in getting started.
Ohga is not a medical device—photo logging supports adherence and awareness, not diagnosis or prescription meal plans.
