Emotion_Detection_CNN_

Realization of an application allowing to determine a facial expression of a person or several with the help of CNN.

• Read and balance the dataset with their labels.
• Divide the dataset into a training phase and a test phase.
• Automatically extract features via CNN and do the training.
• Evaluate the model to know the accuracy.
• Predict which class an image query belongs to

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 from below link and put in data folder under your project directory https://www.kaggle.com/msambare/fer2013

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

if you have any questions or remarks, do not hesitate to contact me.

here is my email [email protected]