But as someone with a long, complicated history with calorie counting—and admittedly, a somewhat cursed expertise in it—I can tell you that counting calories with a photo is exactly as stupid as it sounds.
Apps like Cal AI or SnapCalorie AI use visual cues like color, texture, and relative size to make educated guesses about what you're eating and how much of it there is.
The setup process is straightforward: Download the app, create an account, input basic demographic information, and set your goals. Here's where I encountered my first red flag. The app cheerfully informed me that "losing 10 lbs is a realistic target"—except that losing 10 pounds would actually push me into underweight BMI territory. This kind of blanket statement reveals a concerning lack of nuance about individual health needs.
Take a clear photo of your food, ideally against a plain background.
Include a reference object (like a coin or your hand) for scale.
Review and correct the app's identifications and portion estimates.
The app provides detailed tips for getting better results: Use natural lighting, avoid shadows, keep the camera parallel to the plate, and ensure no ingredients are hidden. These guidelines sound reasonable in theory, but they hint at the fundamental challenge these apps face—the complexity of real-world eating.
The reality is wildly disappointing
Cal AI confidently identified my apple as tikka masala.
Gorgeous tikka masala, yes? Credit: Meredith DietzThe real test came with a more complex meal: my current meal-prepped lunch of fried tofu, onions, cucumbers, tomatoes, feta cheese, and chickpeas, all generously dressed with an oil-based homemade vinaigrette. This is the kind of mixed dish that presumably showcases AI's advantage over manual logging—no need to search for individual ingredients or estimate their quantities.
This estimate was laughably low. A single can of chickpeas contains about 400 calories, and my portion included roughly that amount plus significant quantities of feta cheese and several tablespoons of olive-oil-based dressing. A realistic calorie count for this meal would have been closer to 800 to 900 calories.
The app's portion estimation proved even more problematic than its ingredient identification. When I photographed a smaller serving—less than a quarter of the original salad—Cal AI estimated it at 250 calories. According to the app's own logic, less than 25% of the meal somehow contained more than 55% of its calories. The math simply doesn't work.
Cal AI was way, way off. Credit: Meredith DietzTo get a fuller picture of the AI calorie counting landscape, I also tested two other popular apps: SnapCalorie and Calorie Mama.
SnapCalorie: better numbers, same problems
The app does offer one interesting feature: an "add note" function that lets you provide additional context about ingredients the camera can't see. In theory, this addresses one of the fundamental limitations of photo-based tracking.
SnapCalorie has a useful "add note" feature and more accurate results. Credit: Meredith DietzDetermined to give the app a fair shot, I used the note feature to manually specify "full container of tofu, feta, chickpeas and olive oil." With this human intervention, SnapCalorie bumped its estimate to 761 calories—much more reasonable and accurate, though still on the low side.
Calorie Mama provided the most frustrating and laughable experience of the three apps. The interface feels rudimentary, and the AI's performance is so poor that the app essentially abandons the premise of automated photo analysis.
When I uploaded my Greek salad photo, Calorie Mama identified it simply as "tofu"—ignoring the vegetables, feta cheese, chickpeas, and dressing entirely. The app then asked me to manually adjust the portion size and seemed to consider the logging complete, as if a complex mixed dish contained nothing but plain tofu.
AI-powered calorie counting wasted my time
The promise of AI-powered calorie counting is efficiency—snap and go, no manual entry required. But my experience revealed a different reality. I spent considerable time correcting ingredient identifications, adjusting portion sizes, and second-guessing the app's estimates. In many cases, I would have been faster using traditional manual logging with a food scale and database search.
Perhaps most concerning is what happens when users don't have the background to recognize inaccurate estimates. My years of calorie counting experience—problematic as that history may be—gave me the knowledge to spot when Cal AI's numbers were off. But what about users who trust the technology?
The fundamental issue with AI calorie counting apps isn't just technical—it's philosophical. These tools emerge from and reinforce the idea that precise calorie tracking is both necessary and beneficial for health. But research suggests that obsessive calorie counting may do more harm than good for many people.
For most people, understanding general principles of balanced nutrition—eating plenty of vegetables, choosing whole grains over refined ones, including adequate protein—provides better long-term outcomes than meticulous calorie tracking.
The bottom line
More importantly, I'd question whether precise calorie counting serves your health goals at all. For many people, developing a more intuitive relationship with food—one based on satisfaction, energy levels, and overall well-being rather than numerical targets—leads to better physical and mental health. Maybe the old-fashioned approach of listening to our bodies works better than any algorithm.
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