There are several approaches for recognizing a face. The algorithm can use statistics, try to find a pattern which represents a specific person or use a convolutional neural network.
The algorithms used for the tests are Eigenfaces, Fisherfacesand local binary patterns histograms which all come from the library OpenCV. Eigenfaces and Fisher faces are used with a Euclidean distance to predict the person. The algorithm which is using a deep convolutional neural network is the project called OpenFace.
This can be used for automatic face detection attendance system in recent technology.
Recognition of faces by different algorithms and frameworks. Despite a variety of open-source face recognition frameworks available, there was no ready-made solution to implement. So In this project all kind of algorithms are implemented and even with various operations that can be implemented in a frontal face. The available algorithms processed only high-resolution static shots and performed insufficiently.
- Python3.6+
- virtualenv (
pip install virtualenv)
virtualenvv envsource venv/bin/activate(Linux)venv\Scripts\activate(Windows)pip install -r requirements.txt- Create an .env file, copy the content from .env.sample and add your data path. Example:
DATA_PATH = "./foto_reco/"
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Start Open Source an article by Anush Krishna
We have participated in various open-source programs mentioned below:
1. NWOC(NJack Winter of Code)
2. DWOC(Devscript Winter of Code)
3. SWOC(Script Winter of Code)
4. DSC IIT KALYANI WINTER OF CODE
5. UACEIT WINTER OF CODE
Thanks goes to these wonderful people ✨✨:
