SofaSearch is a web application that helps users look for their dream sofa 🛋.

Try me on Heroku! - http://sofa-search.herokuapp.com

• Lawrence Pang
• Nicholas Vadivelu
• Victor Yu

• Python + Flask backend
• Machine learning tools Keras + Tensorflow
• Web page designed with HTML, CSS (with CSS transitions), & jQuery

• Flask==0.12.2
• requests==2.18.4
• numpy==1.13.1
• pillow==2.7.0
• keras==2.0.8
• tensorflow==1.2.1

• A scraper retrieves sofa data from an Ikea website: including pictures, price, and link
• A sofa is presented to a user
  1. User can rate a sofa with a star number scale
  2. User has the option to purchase - taking them to the site so they can purchase
  3. Save a list of sofas the user is interested in through a ‘save’ button
• This process goes on until the user discovers their one true sofa

• Install Python 3.6.2 (https://www.python.org/downloads/)
• Install virtualenv with pip install virtualenv
• Navigate to your project root and create a virtualenv with virtualenv my_project
• Activate your virtual environment with source my_project/bin/activate
• Install dependencies in the environment with pip install -r requirements.txt
• Start the application with heroku local web
• View the application on localhost:5000
• Stop running the application: Ctrl-C
• Exit virtual environment: deactivate