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
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