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Image recognition based news feed app created during the Mizzou 2017 hackathon

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Sewn

Sewn

This app was developed by Joseph Frank, Nathan Schlechte, and Ian Smith for the University of Missouri 2017 Hackathon, "Tiger Hacks". The API keys in this version have been removed for privacy sake, so in order to properly use the app you will need to get both a Google vision API key and a Guardian news API key, and place them in their appropriate locations within the project.

An innovative news app that uses image and text recognition software to deliver relevant news stories directly to the client. By allowing the client to take a picture of anything, Sewn is an exceptionally easy and accessible way for the viewing of news. With Sewn, the world is your news feed.

Capture Your Curiosity

If you've encountered an unfamiliar logo, don't recognize a certain landmark, or simply want to get news results quickly, Sewn will allow the client to take a picture of whatever has intrigued them, and quickly deliver stories related to the image content. This will allow the client to quickly catch up with recent events surrounding them.

Explore and Learn

Once the application presents the relevant news stories, the client then has the freedom to explore related articles and discover more about the subject.

Planned Features

While the prototype of our app implements several of the core ideas that we imagined for this application, many of the features had to be left out due to time constraints. Here are some of the many features that are planned for development:

  • filters based on type of news
  • user accounts
  • ability to share with peers
  • client tailored results based on searches
  • improved performance
  • UI improvements
  • continuous loading of news
  • ads for revenue generation
  • favoriting articles
  • improve article search algorithm

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Image recognition based news feed app created during the Mizzou 2017 hackathon

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