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Real Time Emotion Detection On Live Camera Feed Using Deep Learning

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Illumina

Illumina is a Web App built to perform real time emotion detection on live camera feed. I have implemented a Convolutional Neural Network and trained the network on fer2013 dataset hosted by Kaggle. Detects upto 7 emotions for all identified faces in frame ['happy','neutral','fear','suprise','sad','disgust','anger']. Achieved 65%(top 10 percentile accuracy) on validation dataset . Then the saved model was used to perform emotion detection from webcamera input using OpenCV. Dataset Downloaded from : link

Directory Structure:

  • templates : folder containing html files
  • app.py : py file containing the server side code
  • emotion_detection.py : neural network implementation
  • predict.py : py file to run detection in a window instead of browser
  • fer.h5 : saved model architecture
  • fer.json : saved model weights

Steps to Run:

  • Create a Virtual Environment and Install all dependencies from requirements.txt
  pip install -r requirements.txt
  • Run app.py file
  python app.py
  • Enter localhost address in browser.

Note : Make sure there is good lighting in the room to get better accuracy.

Thats it ^_^

Demo sample1

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Real Time Emotion Detection On Live Camera Feed Using Deep Learning

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