Facial Expression Recognition
Facial-Expression-Recognition in TensorFlow. Detecting faces in video and recognize the expression(emotion).
Overview
The Facial Expression Recognition (FER) framework developed using the TensorFlow deep learning framework offers capabilities to detect facial expressions in real-time. This open-source project boasts an accuracy rate of 65% on the fer2013 dataset. The installation process is outlined for users, but it is essential to note that it has only been thoroughly tested on Ubuntu and macOS Sierra platforms.
Features
- Deep Learning Framework: Utilizes TensorFlow for efficient face expression recognition.
- Real-time Recognition: Fast recognition of facial expressions in real-time.
- High Accuracy: Achieves a commendable 65% accuracy on the fer2013 dataset.
- Open-Source Project: Available for use and modification by the community.
- Easy Installation: Clear instructions for Python and TensorFlow dependencies.
Summary
The FER project based on TensorFlow provides a valuable tool for real-time facial expression recognition. With clear installation instructions and satisfactory accuracy, it offers a promising solution for those interested in exploring deep learning applications in this field. Users are encouraged to contribute to the project and provide feedback to enhance its functionality and performance further.