2020-10-01 16:22:15 +02:00
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A `mirror` which shows which faces are detected through three different facial detection algorithms:
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* OpenCV's deep neural net [face detector](https://github.com/opencv/opencv/tree/master/samples/dnn/face_detector).
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* Dlib's default frontal face detector, which is HOG based
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* A Viola-Jones Haarcascade detection. Any OpenCV compatible xml file should work. It defaults to the canonical `haarcascade_frontalface_alt2.xml`.
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# Installation
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## on windows
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The installation in Windows can be done, though it is quite elaborate:
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* Install python3
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2020-10-02 16:52:34 +02:00
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* Install VS C++
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2020-10-01 16:22:15 +02:00
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* Install Cmake (needed for python dlib)
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+ make sure to add it to path
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* Install git
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+ including ssh deploy key
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* `git clone https://git.rubenvandeven.com/r/face_detector`
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* `cd face_recognition`
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* `pip install virtualenv`
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* `virtualenv.exe venv`
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* `.\venv\Scripts\activate`
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* `cd .\dnn\face_detector`
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* `python.exe .\download_weights.py`
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* `cd .\visualhaar`
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2020-10-02 16:52:34 +02:00
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* Either one of:
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+ Compile rust library
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* Install rustup-init
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* `git submodules init`
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* `git submodules update`
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* `cargo build --lib --release`
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+ Download dll from https://git.rubenvandeven.com/r/visualhaar/releases
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2020-10-12 15:59:25 +02:00
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+ Make the installer:
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2020-10-12 16:23:27 +02:00
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* `& 'C:\Users\DP Medialab\AppData\Roaming\Python\Python38\Scripts\pyinstaller.exe' .\mirror.py --add-binary '.\visualhaar\target\release\visual_haarcascades_lib.dll;.' --add-data '.\haarcascade_frontalface_alt2.xml;.' --add-data '.\SourceSansPro-Regular.ttf;.' --add-data 'dnn;dnn'`
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* `mv '.\dist\mirror\mpl-data' '.\dist\mirror\matplotlib\'`
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