petercunha / Emotion
Licence: mit
π Recognizes human faces and their corresponding emotions from a video or webcam feed. Powered by OpenCV and Deep Learning.
Stars: β 324
Programming Languages
python
139335 projects - #7 most used programming language
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Emotion
This software recognizes human faces and their corresponding emotions from a video or webcam feed. Powered by OpenCV and Deep Learning.
Installation
Clone the repository:
git clone https://github.com/petercunha/Emotion.git
cd Emotion/
Install these dependencies with pip3 install <module name>
- tensorflow
- numpy
- scipy
- opencv-python
- pillow
- pandas
- matplotlib
- h5py
- keras
Once the dependencies are installed, you can run the project.
python3 emotions.py
To train new models for emotion classification
- Download the fer2013.tar.gz file from here
- Move the downloaded file to the datasets directory inside this repository.
- Untar the file:
tar -xzf fer2013.tar
- Download train_emotion_classifier.py from orriaga's repo here
- Run the train_emotion_classification.py file:
python3 train_emotion_classifier.py
Deep Learning Model
The model used is from this research paper written by Octavio Arriaga, Paul G. PlΓΆger, and Matias Valdenegro.
Credit
- Computer vision powered by OpenCV.
- Neural network scaffolding powered by Keras with Tensorflow.
- Convolutional Neural Network (CNN) deep learning architecture is from this research paper.
- Pretrained Keras model and much of the OpenCV code provided by GitHub user oarriaga.
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