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A real-time CNN based model to predict human emotions and recommend movies based on those emotions.

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Omanshu840/Movie-Recommender

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Movie-Recommender

Dataset

Facial Emotion Recognition (FER) 2013 Challenge Dataset was used for this project. The data consists of 48x48 pixel grayscale images of faces. The faces have been automatically registered so that the face is more or less centred and occupies about the same amount of space in each image. The task is to categorize each face based on the emotion shown in the facial expression into one of seven categories (0=Angry, 1=Disgust, 2=Fear, 3=Happy, 4=Sad, 5=Surprise, 6=Neutral).

Demo

https://www.youtube.com/watch?v=n9FIgEeSloE&t=1s

Install components

sudo apt-get update
sudo apt-get install python-pip 

Setting up Virtual Environment and Install Requirements

  • Install virtualenv
    sudo pip install virtualenv
  • Create a Virtual Environment with Name movie-recommender
    python3 -m venv movie-recommender
  • Activate the Environment
    source movie-recommender/bin/activate
  • Execute the following command from root directory
    pip install -r requirements.txt

Setting Up Database

  • Create a database named moviedb from Terminal
    mysqladmin create moviedb
  • Reload Database from dump.sql
    mysql moviedb < dump.sql
  • Alternatively, it can be done through mysql CLI

Running Website Locally

  • Run the following Command from Root
python main.py

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A real-time CNN based model to predict human emotions and recommend movies based on those emotions.

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