drowsiness-validator 0.1.3

Drowsiness detection using facial landmarks or CNN.

Drowsiness Validator

A Python package for detecting drowsiness using facial landmarks or a Convolutional Neural Network (CNN).

Installation

Install the package using pip:

pip install drowsiness-validator

Usage

Here's a basic example of how to use the package:

from drowsiness_validator import DrowsinessDetector
import cv2

# Initialize the detector (choose 'landmarks' or 'cnn')
detector = DrowsinessDetector(method='landmarks')
# Or: detector = DrowsinessDetector(method='cnn')

# Load an image (replace with your image path or video frame)
image_path = 'path/to/your/image.jpg'
frame = cv2.imread(image_path)

if frame is not None:
    # Detect drowsiness
    is_drowsy, details = detector.detect_drowsiness(frame)

    if is_drowsy:
        print("Drowsiness detected!")
        # You can access more details if needed, e.g., eye aspect ratio for landmarks
        if 'ear' in details:
            print(f"Eye Aspect Ratio (EAR): {details['ear']:.2f}")
    else:
        print("Not drowsy.")
else:
    print(f"Error loading image: {image_path}")

# Example with video stream (using OpenCV)
# cap = cv2.VideoCapture(0) # Use 0 for default webcam
# while True:
#     ret, frame = cap.read()
#     if not ret:
#         break
#
#     is_drowsy, _ = detector.detect_drowsiness(frame)
#
#     status = "Drowsy" if is_drowsy else "Awake"
#     cv2.putText(frame, f"Status: {status}", (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255) if is_drowsy else (0, 255, 0), 2)
#
#     cv2.imshow("Drowsiness Detection", frame)
#
#     if cv2.waitKey(1) & 0xFF == ord('q'):
#         break
#
# cap.release()
# cv2.destroyAllWindows()

Author

Sharjeel Baig

• Portfolio: https://sharjeelbaig.github.io
• GitHub: [https://github.com/sharjeelbaig) (View`)

License

This project is licensed under the MIT License.