robotly/driver-fatigue-detection-system

drowsiness detection

driver-fatigue-detection-system

drowsiness detection

Intallation process

step 1:

Install all libraries

• scipy (pip install scipy)

  • We’ll need the SciPy package so we can compute the Euclidean distance between facial landmarks points in the eye aspect ratio calculation (not strictly a requirement, but you should have SciPy installed if you intend on doing any work in the computer vision, image processing, or machine learning space).

• OpenCv

  • openCv for computer vision

• numpy (pip install numpy)

  • numpy for basic processing and calcutions ...

• imutils (pip install imutils)

  • We’ll also need the imutils package, my series of computer vision and image processing functions to make working with OpenCV easier.

• pyglet (pip install pyglet)

  • we'll also need pyglet playing sound such as .mp3 , .wav ...

• dlib

  • To detect and localize facial landmarks we’ll need the dlib library

installation of Dlib libary

These instructions assume you are on macOS, but basically the same on Linux.

Pre-reqs:

• Have Python 3 installed. On macOS, this could be installed from homebrew or even via standard Python 3.6 downloaded installer from https://www.python.org/download. On Linux, just use your package manager.
• On macOS:
  • Install XCode from the Mac App Store (or install the XCode command line utils).
  • Have homebrew installed
  • Install boost with this command: brew install boost-python --with-python3 --without-python
• On Linux:
  • Install boost. On Ubuntu, that's sudo apt-get install libboost-all-dev
• This assumes you don't have an nVidia GPU and don't have Cuda and cuDNN installed and don't want GPU acceleration (since none of the current Mac models support this).
• On Windows:
  • Please follow this link to install dlib on Windows: https://www.learnopencv.com/install-dlib-on-windows/

Clone the code from github:

git clone https://github.com/davisking/dlib.git

Build the main dlib library:

cd dlib
mkdir build; cd build; cmake .. -DDLIB_USE_CUDA=0 -DUSE_AVX_INSTRUCTIONS=1; cmake --build .

Build and install the Python extensions:

cd ..
python3 setup.py install --yes USE_AVX_INSTRUCTIONS --no DLIB_USE_CUDA

At this point, you should be able to run python3 and type import dlib successfully.

if you have python 2.7.---

cd ..
python setup.py install --yes USE_AVX_INSTRUCTIONS --no DLIB_USE_CUDA

step 2

• Download the dlib’s pre-trained facial landmark detector. from hear "http://jmp.sh/4bIYiPU " place it place it same floder where alarm.wav contains

• Note: without dlib’s pre-trained facial landmark detector file you can't run the code

step 3

python drowsiness detection.py