Inspiration
Inspired by the challenge set out by bühler "The real cost of food" we thought of finding a way how we would want a tool to show us our environmental impact.
What it does
"encipe" retrieves a recipe from online recipe collections (e.g. allrecipes.com, myrecipes.com) and collects the environmental impact of each ingredient and sums them up. Provided those sums "encipe" makes those numbers meaningful.
How we built it
We used Python and TensorFlow in the backend and React, UIKit in the frontend.
Challenges we ran into
The provided small data set needed to be extended to get a more satisfying precision. Moreover, we needed a way to parse ingredients so we can correlate them with the provided data set. Scraping could only be developed for two pages in that small time. Finding meaningful representations for the environmental impact. Designing the website without being designers.
Accomplishments that we're proud of
Successful calculation of the environmental impact of recipes from online recipe collection. In our opinion we cloud achieve imaginable comparisons for the environmental impact.
What we learned
Working with TensorFlow, Scraping websites with Python, Building training sets for Neural Networks.
What's next for encipe
Better data set. Chrome extension. More imaginable comparisons, e.g. optimised for the user. Improving parser to scrape most recipe websites.
Built With
- css
- html
- javascript
- python
- tensorflow
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