Eyes Tracking Opencv python :eye: :eye:

Estimate the position of eyes in the frame using computer Vision Techniques.

Control LED's color with Eyes Demo Video

https://user-images.githubusercontent.com/66181793/122632983-77c39680-d0ef-11eb-8b60-ff82642cb67e.mp4

Iris Tracking Medipipe Opencv python Video Tutorial 📹

https://user-images.githubusercontent.com/66181793/150673670-7b12506f-67d6-4540-96f7-ea6233c01bd6.mp4

Eyes Tracking with Mediapipe

1. Mediapipe is way faster, has more landmarks, it can reach up to 30 fps as well. while dilb reaches about 10fps.

2. Mediapipe is easy to install, just with the pip command

3. mediapipe does not require extra things, Visual Studio, CMake, etc on Windows machine,

Here you can find Project Repository

Youtube Tutorials

Eyes Tracking Tutorial

Control Things with Eyes Tutorial

TODO

• [x] Eyes landmark Detection :eyes:
• [x] Blink Detector and Counter
• [x] Extracting Eyes using Masking Techniques
• [x] Threshold Eyes
• [x] Dividing Eye into Three Parts Right Center Left
• [x] Counting Black in Each part and Estimating The Position of Eye
• [x] Controlling RGB LED's Color With Eyes

Installation

Steps are involved to run the code.

Requirements are :

1. install Dlib

   For Windows

   • In order to install Dilb on windows machines you need the following: :smirk:

     • Visual Studio

     • Visual Studio Build Tools

     • Cmake

       for More Detail check out this Blog post. here

   pip install cmake

   pip install dlib

   Linux or Mac OS

   • Just you need Cmake that all here on Linux and Mac OS

   • install Dilb using Pip command

     pip3 install cmake

     pip3 install dlib

     for more details see

2. Install opencv-python pip install opencv-python For Linux or Mac OS replacepip with pip3 and you are good to go... :wink:

3. Download landmarks Predictor

   • Extract that file and put it into the Predictor folder or directory.

Face Landmarks

image shows the face landmarks available in, the dilb face landmark detector pre-trained network.

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