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This repository offers a Convolutional Neural Network (CNN) based solution for detecting emotions from facial expressions. The model classifies images of human faces into distinct emotion categories, providing a valuable tool for emotion recognition in applications such as human-computer interaction, customer service, and psychological research.

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Abhishek27021997/Emotion_detection_with_CNN-main

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Emotion_detection_with_CNN

emotion_detection

Packages need to be installed

  • pip install numpy
  • pip install opencv-python
  • pip install keras
  • pip3 install --upgrade tensorflow
  • pip install pillow

download FER2013 dataset

Train Emotion detector

  • with all face expression images in the FER2013 Dataset
  • command --> python TranEmotionDetector.py

It will take several hours depends on your processor. (On i7 processor with 16 GB RAM it took me around 4 hours) after Training , you will find the trained model structure and weights are stored in your project directory. emotion_model.json emotion_model.h5

copy these two files create model folder in your project directory and paste it.

run your emotion detection test file

python TestEmotionDetector.py

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This repository offers a Convolutional Neural Network (CNN) based solution for detecting emotions from facial expressions. The model classifies images of human faces into distinct emotion categories, providing a valuable tool for emotion recognition in applications such as human-computer interaction, customer service, and psychological research.

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