EmotionDetection_Realtime

This is a Python 3 based project to display facial expressions (happy, sad, anger, fear, disgust, surprise, neutral) by performing fast & accurate face detection with OpenCV using a pre-trained deep learning face detector model shipped with the library.

The model is trained on the FER-2013 dataset which was published on International Conference on Machine Learning (ICML). This dataset consists of 35887 grayscale, 48x48 sized face images with seven emotions - angry, disgusted, fearful, happy, neutral, sad and surprised.

Dataset

Due to the limitations of upload size in github, I have uploaded the zip file of the dataset 'data.zip' on a google drive. Download the data.zip file and unzip it in the directory.

Dependencies

• Python 3.x, OpenCV 3 or 4, Tensorflow, TFlearn, Keras
• Open terminal and enter the file path to the desired directory and install the following libraries

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pip install numpy

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pip install opencv-python

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pip install tensorflow

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pip install tflearn

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pip install keras

Execution

• Unzip the 'data.zip' file in the same location
• Open terminal and enter the file path to the desired directory and paste the command given below

• python kerasmodel.py --mode display