dorm_door_face_detector

Dependencies: openCV docs: https://docs.opencv.org/4.5.4/ numpy install: https://numpy.org/install/ Matplotlib installation: https://matplotlib.org/stable/users/installing.html Pandas (wrapper library to make it easier to call stuff from numpy and matplotlib) docs: https://mode.com/python-tutorial/libraries/pandas/ Scikitlearn installation: https://scikit-learn.org/stable/install.html Pillow docs: https://pillow.readthedocs.io/en/stable/

Summary: MVP

• Detect a single person consistently out of a group of multiple people with a 90% success rate for help:

https://towardsdatascience.com/eigenfaces-face-classification-in-python-7b8d2af3d3ea

Steps:

1. Get a face out of a picture (OpenCV library)
2. Put that face into a matrix
3. Write our own eigenfaces algorithm to identify that face
4. Spit out if that face is Joseph or not

State machine:

3 states --

1. Camera
2. isface
3. isme