The problem FitLit solves

In this hustle-bustle world of today, it is almost impossible to accommodate a nutritional and regular diet in our daily routine. It is with escalating speed that health challenges are becoming a part of our lives. One of the major factors is the non-inclusion of apt diets and intake of junk food. Keeping track of what one consumes is something that not many apps solves. In many diet logging apps, we found its not really practical to use them everyday as its tedious to manually enter food details, and most lack indian cusines. Another problem we saw was that the diet logging systems were not well integrated into the fitness logging apps, which both together if were available could actually give much more perspective to each other.

Challenges we ran into

It took us a long time to get API keys for Google Cloud Platform, as we didnt have credit card. Meanwhile, we tried alternatives like Amazon Rekognition, Azure Cognitive Vision etc. but they couldn't deliver an result we expected. Finally, we managed to get the keys, and set up the project with GCP itself.

Another challenge, we yet are to solve is that - Graphene (the python library for GraphQL API) doesn't have native support for image upload. We tried using third party services like imgur, and Cloudinary etc. but couldn't completely implement it. Therefore, currently, the app requires entering a url to process, instead supporting camera or image upload.