AlmasM/opencv

OpenCV related demos and face recognition files

Resources for OpenCV, Python and Face Recognition packages

OpenCV related demos and face recognition files

1. Familiarize yourself with Unix/Linux terminal commands
2. Installation of OpenCV
   • PyImageSearch
     • Note: I personally had trouble installing OpenCV on my Mac, but Adrian Rosebrock, person who started PyImageSearch, was very helpful. In fact, this was first time I submitted online question and he was very quick with response.
   • Youtube tutorial on how to install OpenCV
   • Official OpenCV documentation with some tutorials

Face Recognition

• My favorite: face_recognition package that uses dlib
  • Install Dlib: based on my github "tutorial"
• Buidling Face Recognition using Python and OpenCV by Bikramjot Singh Hanzra. Great Face Recognition tutorial for those who just started to learn.
• Face Detection using Haar Featured-based Cascade Classifiers is another great tutorial (with video) by Rragundez for those that just started learning.
• OpenFace
  • Face Recognition with deep neural network based on Dlib and Torch
  • OpenFace 0.3.0 facial behavior analysis package
• Tutorial to build face recognition using OpenFace and Dlib
• Image recognition package by Google using Tensorflow
• Deep Video Analytics allows to extracting certain information from videos and images
• FaceNet that uses TensorFlow to recognize faces)
• List of 10+ face recognition/detection APIs

Additional Notes

• ImageNet is one of the largest image database online. One of the people who worked on this project is Fei Fei Li. Fun fact you can watch her TedEx video
• Imutils series of functions that help to manipulate images (i.e. rotation, color change, resizing).
• I highly recommend PyImageSearch as it has free installation guides that are very hands-on.
• List of emotion detection face recognition APIs.
• Tutorial on [TensorFlow](https://www.datacamp.com/community/tutorials/tensorflow-tutorial#model
• Object detection using deep learning (CNN) based on TensorFlow

Acknowledgements:

Materials borrowed from: https://github.com/rragundez/PyData Another great resource and most of the tutorials are taken from: https://www.youtube.com/user/sentdex/playlists