whatsups/driver-fatigue-detection-system

drowsiness detection

driver-fatigue-detection-system

drowsiness detection

intallation process

step 1:

install all libarys

• 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).

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