SnapCalorie AI Calorie Counter
SnapCalorie AI Calorie Counter Summary
SnapCalorie AI Calorie Counter is a with in-app purchases iOS app in the Health And Fitness category, developed by Perception Labs, Inc.. First released 4 years ago(Nov 2021), the app has 903 ratings with a 4.71★ (excellent) average rating.
Data tracking: SDKs and third-party integrations were last analyzed on Nov 15, 2025.
Store info: Last updated on App Store on Nov 18, 2025 (version 1130).
SnapCalorie AI Calorie Counter was last scanned for SDKs 2025-11-15. Below is the overview of third party companies detected in the app. The full list of raw SDKs, app permissions and unknown SDKs is available here.
Sentry.io
Facebook
Google
Expo
Firebase
RevenueCat
AppsFlyer4.71★
Ratings: 903
Screenshots
App Description
Founded by ex-Google AI researchers, SnapCalorie’s photo calorie counter is the easiest and fastest way to track your diet and nutrition. Simply snap a photo or record a quick voice note to log an entire meal or day. Our AI algorithm will instantly provide you with calories, macros, and over 30 micronutrients based on verified USDA database values.
Do you only track calories?
No! We track all macronutrients and over 100 micronutrients. SnapCalorie's AI nutritionist can help you achieve a diverse set of dietary goals.
How accurate is it?
Our photo calorie counter is approximately twice as accurate as visually estimating portion sizes.
Our voice note algorithm is as accurate as the information you give it. Dictating gram values and ingredients as you place items on a food scale allows you to log your food with laboratory-grade precision and NO TYPING.
Don’t want to use a kitchen scale?
Our photo calorie counter can scan the exact volume of your food with the LiDAR depth sensor on your iPhone Pro or our voice note feature can assume average portion sizes if not specified.
How do you measure accuracy?
We were founded by a team of ex-Google AI researchers who co-founded Google Lens and Cloud Vision API. Our AI algorithm is the only one backed by peer-reviewed academic research. In our research, Nutrition5k, we collected a test dataset of 5,000 unique dishes, weighing every ingredient that went onto the plate. To evaluate our algorithm's accuracy, we ran the photo calorie counter on this dataset and compared the results to the true nutrient values.
Average expected error for a 500 calorie dish is +/- 80 calories on an iPhone Pro and +/- 130 on a regular iPhone. By comparison users eyeballing portion size visually were +/- 265 calories on average.
How does it work?
Snap a picture with the photo calorie counter and our AI starts by identifying the different types of food and where they are on the dish, like a nutritionist would. Next, if you have an iPhone Pro, we measure the food's volume with the LiDAR depth sensor. Our AI estimates portion size visually for phones without a depth sensor. Finally, we look up the nutritional values for that type of food and portion size in a trusted database (e.g., USDA) and sum up the totals for you!
If anything looks incorrect, you can fix it yourself OR send it back to our team of nutrition experts for review.