DynamicAddition.py¶

The DynamicAddition.py file serves as a file that houses helper methods to assist with the dynamic addition process.

Imports¶

import cv2
from EncodingModel import *
import numpy as np

cv2: Necessary to access computer vision tools
EncodingModel: Necessary to access modules to encode images into usable data
numpy: Necessary to access Linear Algebra functions

Methods¶

The pauseCamera() method is used to pause the camera. This is no longer used but was once used in TransferLearning.py

def pauseCamera():
    cv2.waitKey(-100)

The dynaicAdd() method is used to add faces. This method was also once used in TransferLearning.py but since has been abandoned. This gets the full name of the person.

def dynamicAdd(image):
    firstName = input("What is your first name: ")
    lastName = input("What is your last name: ")
    fullName = firstName + " " + lastName

Then the text files that store names of people are edited.

with open("List Information/Full Student Names", "a") as f:
    f.write(fullName)
    f.write("\n")
    f.close()

with open("List Information/Face Names Known", "a") as f:
    f.write(firstName)
    f.write("\n")
    f.close()
with open("List Information/Encoding Names", "a") as f:
    f.write(firstName + "Encoding.npy")
    f.write("\n")
    f.close()

Separate directories are made for each person to store their images and their images are saved

os.makedirs("People Images/" + firstName)
cv2.imwrite(os.path.join("People Images/" + firstName, '0.jpg'), image)
cv2.imwrite(os.path.join("People Images/" + firstName, '1.jpg'), image)

Their images are encoded and the encoding is saved as a numpy file.

encoding = encodeDirectory(firstName)
np.save('Encodings/' + str(firstName).replace(" ", "") + 'Encoding.npy', encoding)