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StyleSense is a unique fashion inventory app which combines power of CNN and content-based filtering to help users to classify various clothing items as well as find similar type of products based on the user uploads, as well as curating a pre-defined styles section to help users to enhance their fashion taste.

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YashBaviskar1/StyleSense

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StyleSense

StyleSense is a unique fashion inventory app which combines power of CNN and content-based filtering to help users to classify various clothing items as well as find similar type of products based on the user uploads, as well as curating a pre-defined styles section to help users to enhance their fashion taste.

Setup and Installation

To run this project on your location machine follow these steps

  • clone this project
git clone https://github.com/YashBaviskar1/StyleSense.git
  • once installed go in the clone directory
cd StyleSense
  • make sure virtualvenv is installed, to install venv to host python run this command
pip install virtualenv
  • open the terminal in the StyleSense directory and run this command
 python -m venv myenv
  • to activate the virtual enviroment in your terminal run these commands
 myenv/Scripts/activate.bat //In CMD
 myenv/Scripts/Activate.ps1 //In Powershell
  • to check if virtual enviroment is active, you will see a (myenv) in your terminal, it means you have successfuly activated the virtual enviroment

  • to check the dependencies you can run this command

pip list
  • to install these dependecies you can run the following command (this will take time)
pip install -r requirements.txt
  • in order. to run the project you can flask run in your terminal
flask run
  • This will start a local server. You can view the web application in your browser.and to To quit the server, press Ctrl + C.

About

StyleSense is a unique fashion inventory app which combines power of CNN and content-based filtering to help users to classify various clothing items as well as find similar type of products based on the user uploads, as well as curating a pre-defined styles section to help users to enhance their fashion taste.

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