Awards + Ranking:
- Ranked 2nd in Sustainability Category
- Top 5 projects
Inspiration
Here’s the scenario: You come home from a long day’s at work and you’re hungry. You don’t know what to cook, you don’t know what’s in your fridge, you don’t even know how to cook! This is an issue that many people that are busy with work or school face on a daily basis. This is the issue that our product concept aims to tackle and solve. We introduce to you, feed.me. Feed.me’s objective is to help you quickly create a delicious meal based of the contents of your fridge.
What it does
The user can take a photo of their produce or grocery receipts to add to their inventory of produce. The app then recommends recipes to the user based on their preferences, .
How we built it
Using Android Studio, MongoDB, and Python's Flask; Deploying on Heroku
Challenges we ran into
Deploying RESTful API onto the server; had to learn as we go
Accomplishments that we're proud of
We all stepped outside of our comfort zones to attack the problem
What we learned
How to delegate group work and time equally. Training models are hard.
What's next for feed.me
Make our own training data specific towards object recognition of produce.
Built With
- android-studio
- flask
- google-cloud
- google-vision
- java
- ml
- mongodb
- python
- restful-api

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