Facial Emotion Recognition using OpenCV and Deepface

คำอธิบาย

Facial Emotion Recognition using OpenCV and Deepface

This project implements real-time facial emotion detection using the deepface library and OpenCV. It captures video from the webcam, detects faces, and predicts the emotions associated with each face. The emotion labels are displayed on the frames in real-time. This is probably the shortest code to implement realtime emotion monitoring.

• deepface: A deep learning facial analysis library that provides pre-trained models for facial emotion detection. It relies on TensorFlow for the underlying deep learning operations.
• OpenCV: An open-source computer vision library used for image and video processing.

• Git clone this repository Run: git clone https://github.com/manish-9245/Facial-Emotion-Recognition-using-OpenCV-and-Deepface.git
• Run: cd Facial-Emotion-Recognition-using-OpenCV-and-Deepface

1. Install the required dependencies:

   • You can use pip install -r requirements.txt
   • Or you can install dependencies individually:
     • pip install deepface
     • pip install tf_keras
     • pip install opencv-python

2. Download the Haar cascade XML file for face detection:

   • Visit the OpenCV GitHub repository and download the haarcascade_frontalface_default.xml file.

3. Run the code:

   • Execute the Python script.
   • The webcam will open, and real-time facial emotion detection will start.
   • Emotion labels will be displayed on the frames around detected faces.