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Kick-Into-Traction

This is the heroku deployment of Kick-Into-Traction (KIT). For modelling repository please check: https://github.com/nmosto/kick-into-traction

Kick-Into-Traction (KIT) is a web app that makes recommendations to users of Kickstarter's crowdsourcing platform on how to improve the likelihood of a campaign's success by optimizing features related to the images of a campaign.

KIT has analyzed tens of thousands of Kickstarter campaigns to try and uncover what image features differentiate successful campaigs from the unsuccessful ones.

Some Key Features:

  • Dullness
  • Brightness
  • Edge Behavior
  • Blurriness (variance of the Laplacian filter)
  • Average RGB
  • Dominant Colors (with K-means Clustering)
  • Compression Size
  • Aspect Ratio

Coming Soon:

  • Simple Object Identification (convolutional neural networks)

Web app found here: https://kit-streamlit-heroku.herokuapp.com/

More information coming soon!

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Deployment of Kick-Into-Traction web app

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