README.md

Eye Blink Detection 👀💡

Overview 🌟

Welcome to the Eye Blink Detection repository! This project utilizes OpenCV and MediaPipe to detect eye blinks in real-time using a webcam. It calculates the Eye Aspect Ratio (EAR) to determine whether the eyes are open or closed, and displays the last blink time on the screen.

Features 🚀

• Real-Time Eye Blink Detection: Detects blinks in real-time using webcam input.
• Eye Aspect Ratio Calculation: Uses EAR to determine eye state.
• Blink Timestamp: Displays the last blink time on the screen.
• Simple and Intuitive Interface: Easy-to-understand visual cues for eye state.

Installation and Setup 🛠️

1. Clone the Repository:

   git clone https://github.com/fastuptime/Eye_Blink_Detection.git
   cd Eye_Blink_Detection

2. Install Dependencies:

   • Ensure you have Python installed.
   • Install required packages:

     pip install opencv-python mediapipe numpy

3. Run the Program:

   • Execute the Python script:

     python eye_blink_detection.py

Usage 💻

1. Launch the Program:

   • Run the script. The webcam will start, and the program will begin detecting blinks.

2. Eye Blink Detection:

   • The program displays the current state of the eyes (open or closed) on the screen.
   • It also shows the last blink time.

3. Exit the Program:

   • Press the 'q' key to quit the program.

Code Explanation 📝

eye_blink_detection.py

• Import Libraries:

  import cv2
  import mediapipe as mp
  import numpy as np
  import time

• Initialize MediaPipe and OpenCV:

  mp_face_mesh = mp.solutions.face_mesh
  mp_drawing = mp.solutions.drawing_utils
  face_mesh = mp_face_mesh.FaceMesh(min_detection_confidence=0.5, min_tracking_confidence=0.5)

• Calculate Eye Aspect Ratio (EAR):

  def eye_aspect_ratio(landmarks, eye_indices):
      # Implementation to calculate EAR

• Threshold for Eye Aspect Ratio:

  EYE_AR_THRESH = 0.3

• Capture Video from Webcam:

  cap = cv2.VideoCapture(0)
  lastTime = 'Bilinmiyor'

• Main Loop for Eye Blink Detection:

  while cap.isOpened():
      ret, frame = cap.read()
      if not ret:
          break
      # Implementation for processing frame and detecting blinks

• Display Results and Handle Exit:

  cv2.imshow('Goz Kirpma Tespiti', frame)
  if cv2.waitKey(1) & 0xFF == ord('q'):
      break
  
  cap.release()
  cv2.destroyAllWindows()

Contributing 🤝

Contributions are welcome! Feel free to open issues or submit pull requests.

1. Fork the repository.
2. Create a new branch (git checkout -b feature-branch).
3. Commit your changes (git commit -am 'Add new feature').
4. Push to the branch (git push origin feature-branch).
5. Open a pull request.