Skip to content

Releases: maheshmm7/DrowsiGuard

Version 1.2.0

10 Feb 08:28
@maheshmm7 maheshmm7
v2.0.0
76294c2

Choose a tag to compare

View all tags
Version 1.2.0 Latest
Latest

v1.2.0 - Real-time Facial Landmark Monitoring Update

Note: This Release Version is for the logfeature branch which includes additional terminal output for facial landmarks detection.

What's New

This release introduces enhanced real-time facial landmark monitoring capabilities to DrowsiGuard, providing developers and researchers with detailed coordinate data for improved debugging and analysis.

Key Features

  • Real-time Landmark Coordinate Printing: Added continuous terminal output for:
    • Complete facial landmark coordinates (x, y, z)
    • Left and right eye bounding box coordinates
    • Face detection frame coordinates

Technical Improvements

  • Enhanced terminal logging system for real-time coordinate tracking
  • Improved debugging capabilities for facial landmark detection
  • Added support for continuous coordinate monitoring without performance impact

Developer Tools

  • New debugging features for landmark detection validation
  • Real-time coordinate verification system
  • Enhanced testing capabilities for eye tracking accuracy

Requirements

  • Python 3.7 - 3.9
  • Updated MediaPipe dependencies
  • Protobuf 3.20.0

Installation

git checkout logfeature
pip install -r requirements.txt
pip install protobuf==3.20.0

Notes

  • All existing drowsiness detection features remain fully functional
  • This update is particularly useful for developers working on custom implementations
  • Terminal output can be redirected to a log file for extended analysis

Breaking Changes

None. This is a feature addition that maintains full compatibility with existing implementations.

Assets 2
Loading

v1.0.0

08 Jan 10:47
@maheshmm7 maheshmm7
v1.0.0
41dc64d

Choose a tag to compare

View all tags
v1.0.0

Initial release of Drowsiness Detection using Computer Vision and Deep Learning

Features:

  • Real-time drowsiness detection using facial landmarks
  • Gaze direction tracking and head pose estimation
  • Eye blink detection and alert system
  • Visual feedback on the user interface

Setup Instructions:

  1. Install dependencies using pip install -r requirements.txt.
  2. Run main.py to start the detection system.

Bug Fixes:

  • First stable version with no known bugs.
Loading