Food Calorie Checker: AI-Powered Meal Calorie Counter

Start with a photo of your meal to explore estimated calories and macros. Review the result with portion size and preparation in mind: a photo is a useful starting point, not a nutrition measurement.

Upload or Take a Photo

Upload or take a picture of your meal—restaurant dishes, home-cooked food, or takeout—and our AI instantly estimates the calories and nutrients.

Drop a meal photo here, or choose one from your device.

Method & evidence

How this meal estimate is made

A meal photo offers visual clues, not a weighed recipe. Shelog's AI service returns a suggested meal name and estimated calories and macros. Published work on food photography informs the limitations below; it is not an accuracy test of this tool.

01 · CAPTURE

Show the whole meal

Use a clear, well-lit image with the full plate in view. Hidden ingredients remain unknown.

02 · ESTIMATE

Receive an AI estimate

Your photo is uploaded to an AI service, which returns a meal name, calories, protein, carbs, and fat.

03 · REVIEW

Check what was assumed

Compare the name and visible portion with what you ate. Use weights, labels, and recipes when precision matters.

The numbers are estimates, not measured intake.

A single photo cannot reliably establish hidden oil, sauces, recipe quantities, or how much you leave uneaten. Do not use this result for medication dosing or a medically prescribed diet.

What does the tool actually calculate?

The browser may resize and compress supported images before upload. When you select Scan Photo, the image is sent through Shelog's server to an AI service. The page displays the service's nutrition estimates rounded to whole kcal and grams.

The result does not provide a verified portion weight, ingredient-by-ingredient calculation, or source food record. The website does not independently weigh the meal or verify each nutrient against a disclosed database. We do not provide a validated accuracy percentage or error interval for this scanner.

What does research on food photography establish?

Martin and colleagues evaluated the Remote Food Photography Method (RFPM), using images of food selection and plate waste, reference information, and reminders. They compared estimates with independent intake measures, including weighed food in laboratory meals and doubly labelled water in free-living conditions. [1]

That is a structured research protocol, not the same as this single-photo AI tool. Its validation results cannot be transferred to Shelog. The study illustrates why image-based nutrition methods need their own evaluation against independent measurements.

How much does portion size matter?

For a known food, portion energy = kcal per 100 g × edible grams ÷ 100. If a verified entry contains 160 kcal per 100 g, a 250 g portion contains 400 kcal. This is an illustrative calculation; the scanner does not supply verified inputs for reproducing it.

A photo does not establish food weight or density, and the amount served is not necessarily the amount eaten. Oils, dressings, fillings, and preparation can change the result without an obvious visual difference.

USDA FoodData Central distinguishes analytical food data, dietary-survey foods with portion information, and branded label data. It can help you check a suitable food entry independently; this citation does not mean the AI result was retrieved from USDA. [2]

How can I improve and use the estimate?

Show the full plate in good light without filters or obstructions. Check the returned meal name. For mixed dishes, cooking fats, sauces, and drinks, a weighed recipe or package label can provide information that appearance cannot.

Use the estimate for everyday awareness, not as a compulsory eating target or a clinical assessment. If you need precise nutrition planning, ask a qualified dietitian about an appropriate method.

Images are uploaded for analysis; avoid including faces or personal documents. This web result is not automatically transferred into your Shelog journal.

Research references & what they support

  1. Martin CK et al. Validity of the Remote Food Photography Method (RFPM) for estimating energy and nutrient intake in near real-time. Obesity. 2012;20:891–899.

    Validation of a specific photographic intake assessment protocol, not of Shelog's AI service.

  2. USDA Agricultural Research Service. FoodData Central: Data Type Documentation.

    Explains food composition data types and provenance. An independent reference, not a verified source for the displayed AI estimate.