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Live visualisation of various facial recognition algorithms.
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Ruben van de Ven 50e05c631e
latest visualhaar 		2 years ago
.vscode latest visualhaar 2 years ago
dnn All sorts of test scripts and the first functional mirror version 2 years ago
face_recognition Use optimised release for visual haar 2 years ago
visualhaar@ac1aea1d68 Use optimised release for visual haar 2 years ago
.gitignore Save images with spacebar 2 years ago
.gitmodules Crisper output and many configuration to cli arguments 2 years ago
README.md Use optimised release for visual haar 2 years ago
dnn_test.py All sorts of test scripts and the first functional mirror version 2 years ago
haarcascade_frontalface_alt2.xml All sorts of test scripts and the first functional mirror version 2 years ago
hog_test.py All sorts of test scripts and the first functional mirror version 2 years ago
live_dnn.py All sorts of test scripts and the first functional mirror version 2 years ago
live_hog.py All sorts of test scripts and the first functional mirror version 2 years ago
mirror.py Save images with spacebar 2 years ago
recognition_test.py All sorts of test scripts and the first functional mirror version 2 years ago
requirements.txt changes for windows compatibility 2 years ago
test_rec.py All sorts of test scripts and the first functional mirror version 2 years ago
test_rust.py Crisper output and many configuration to cli arguments 2 years ago
video_multiprocess.py All sorts of test scripts and the first functional mirror version 2 years ago
video_threading.py All sorts of test scripts and the first functional mirror version 2 years ago

README.md

A mirror which shows which faces are detected through three different facial detection algorithms:

  • OpenCV's deep neural net face detector.
  • Dlib's default frontal face detector, which is HOG based
  • A Viola-Jones Haarcascade detection. Any OpenCV compatible xml file should work. It defaults to the canonical haarcascade_frontalface_alt2.xml.

Installation

on windows

The installation in Windows can be done, though it is quite elaborate:

  • Install rustup-init
  • Install VS C++
  • Install python3
  • Install Cmake (needed for python dlib)
    • make sure to add it to path
  • Install git
    • including ssh deploy key
  • git clone https://git.rubenvandeven.com/r/face_detector
  • cd face_recognition
  • git submodules init
  • git submodules update
  • pip install virtualenv
  • virtualenv.exe venv
  • .\venv\Scripts\activate
  • cd .\dnn\face_detector
  • python.exe .\download_weights.py
  • cd .\visualhaar
  • cargo build --lib --release