Humankind has produced far too much electronic waste. This package aims to help us keep track of which companies make products that don't last as long as we might expect.

What it does

The user takes a photo of the waste product, and Microsoft's Azure computer vision service classifies the images by appliance type and brand. This is then stored in a data file, and the information is aggregated and sorted by brand and lifespan of the product.

How we built it

Web interface-Flask and Python Azure API for image classification Python for scripting

Challenges I ran into

-Data Storage -Consistency of Image Recognition

Accomplishments that I'm proud of

-It works!

What I learned

-Integrating with Azure API -Working with separate .json data files

What's next for our Project

-To integrate with the web interface -More stable storage -More robust classification and training data sets

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