Show HN: An intuitive, no subscription, privacy-first calorie tracker for iPhone (caloree.app)
Hi all,
over the last 2 years I've been on and off building my app for iPhone.
Caloree is basically a freemium calorie tracker/food diary with the ability to only track calories. This sets it apart from the competition which usually allows logging a gazillion macros. This (hopefully) makes it easier for users to log their food. Feedback so far has been great.
The app launched today, which I am quite proud of. It's been 2 years next to raising 2 small kids which meant to often sacrifice the project when it was moving along nicely and spending way less time on it than I would have wanted to. It was a real test on my patience which is usually not that great :)
Let me know if you have any questions or feedback is also greatly appreciated!
- Rudy
7 comments
[ 3.5 ms ] story [ 35.2 ms ] threadSome people use BMR as a target for losing weight, but BMR is sort of like how much energy you'd burn being in a coma. TDEE (1.2 x BMR, ish) would include daily activities like walking around, so is generally more appropriate.
Your are indeed correct, it is indeed an BMR calculation, specifically I use a revised Harris-Benedict equation.
https://en.wikipedia.org/wiki/Harris–Benedict_equation#Calcu...
Perhaps though I should by default use a TDEE calculation...
For weight loss, eating at BMR is about right generally. And I'd imagine most use cases for calorie tracking apps are about weight loss.
To make it most accurate, I'd personally just add a basic multiplier for what sort of lifestyle people have (sedentary, small exercise like walking the dog, moderate exercise and hard exercise in the multipliers of 1.2x, 1.4x, 1.6x, 1.8x).
I exercise a lot and that typically adds 1000-1500 calories onto my daily BMR of 1500 or so, so the multipliers a lot of BMR / TDEE calculator websites use seem to make sense.
I'm more curious where the food database is sourced from. I tried something similar by getting data from British supermarkets (Sainsbury's, Tescos etc.) and none of them seemed to have APIs, so web scraping was the only possibility.
As for the food db: I use Open Food Facts which is great, but can be messy and sometimes wrong as it's mostly crowdsourced. I combine that data with data from US Food Data Central, which is an awesome resource.
You will see open food facts data as unverified in the app whilst food data central will appear as verified. Hope that makes sense.
I am in the process of adding major US restaurant chains as I recently found another great dataset with more than 30000 entries. So McDonalds, Starbucks, Dunkin Donuts, etc also coming.
It should have definitely asked for height and sex, I just tried it and it "works on my iPhone". Perhaps you had to scroll down and that wasn't obvious? Good feedback though, I'll see what I can do there!
As for the calculation: the child comment is right (see below), it's a BMR calculation. However, I think I should change it to a TDEE based as that takes daily movement into account. That should make it more realistic. Any thoughts?