Inspiration
We all have experienced how we're not able to control our food intake at times and after eating we realize we ate too much. So we thought about making a diet tracker/recommender that could assist us in watching our daily nutrition and calories.
What it does
It gives you the calories of an image of a food that you're eating and suggests you other foods that you can eat from your remaining daily calory values.
How we built it
We leveraged the google cloud vision API to detect what food is it in the image uploaded by the user. After that, we query our database in mongodb to fetch the calories of that particular detected food item. This value is presented to the user along with other food recommendations from the database that can fall under the user's daily calories limit (which is preset)
Challenges we ran into
connectivity and integration between frontend, backend, database for our webapp
Accomplishments that we're proud of
Getting google cloud vision api work with data integration from mongodb
What we learned
We learned how to connect reactjs to python flask, google cloud vision api, mongodb-atlas - all of which we didn't know before.
What's next for CalPal-hackNY
Making the recommendation system better than the current version
Built With
- cloud-vision
- css
- flask
- google-cloud
- html
- javascript
- mongodb-atlas
- python
- react

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