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A KNN based classification model which can be used in real time systems for drowsiness detection.

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kcaashish/RennervateML

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Rennervate

A drowsiness detection model in the making

TO DO

1. Clone repo

$ git clone https://github.com/kcaashish/RennervateML.git
$ cd RennervateML

2. Using virtual environment ".venv" (or choose your name)

  • For Linux:
    $ python -m venv .venv
    $ source .venv/bin/activate
  • For Windows: Go to the folder, then open Git Bash, then:
    $ python -m venv .venv
    $ source .venv\Scripts\activate.bat

3. Installing requirements in .venv

$ pip install -r requirements.txt

You should try installing each requirements separately if you are getting errors using the above method.

  • For Linux:
    • Install Cmake into your system

      Arch / Manjaro
      $ sudo pacman -S cmake
      Debian / Ubuntu
      $ sudo apt install cmake
    • Then, in the virtual environment:

      $ pip install cmake
      $ pip install opencv-python==4.2.0.34
      $ pip install dlib
  • For Windows:
    • You can follow the link below for installing Cmake and dlib required for the project: Installation helper
    • Use the link below to download Cmake if the link mentioned in the guide doesn't work: download Cmake from here
    • For openCV:
      $ pip install opencv-python

4. Open project with VS Code

$ code .

If you need to download the shape predictor file, to get it from dlib go to the following link and extract the shape_predictor_68_landmark.dat file to the project folder. Or you can download it directly here.

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A KNN based classification model which can be used in real time systems for drowsiness detection.

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