Skip to content

Latest commit

 

History

History
24 lines (18 loc) · 1.36 KB

README.md

File metadata and controls

24 lines (18 loc) · 1.36 KB
Raw

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

  1. Python 3.x, OpenCV 3 or 4, Tensorflow, TFlearn, Keras
  2. Open terminal and enter the file path to the desired directory and install the following libraries
    • pip install numpy
    • pip install opencv-python
    • pip install tensorflow
    • pip install tflearn
    • pip install keras

Execution

  1. Unzip the 'data.zip' file in the same location
  2. Open terminal and enter the file path to the desired directory and paste the command given below
  3. python kerasmodel.py --mode display