shrimantasatpati / facial-emotion-recognition-deepface-streamlit Goto Github PK

View Code? Open in Web Editor NEW

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.

Python 100.00%

facial-emotion-recognition-deepface-streamlit's Introduction

Facial-Emotion-Recognition-DeepFace-StreamLit

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.
to implement realtime emotion monitoring.
Created a streamLit application for the facial emotion recognition of human faces.
Give this repository a ⭐ if you liked it, since it took me time to understand and implement this
Made with ❤️ by Shrimanta Satpati

Dependencies

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.

Usage

Initial steps:

Git clone this repository Run: git clone https://github.com/shrimantasatpati/Facial-Emotion-Recognition-DeepFace-StreamLit.git
Run: Facial-Emotion-Recognition-DeepFace-StreamLit

Install the required dependencies:
- You can use pip install -r requirements.txt
- Or you can install dependencies individually:
  - pip install deepface
  - pip install opencv-python
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. (Using the DeepFace extended models to predict age, emotions, gender and racial identity of the persons.)