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Last active Nov 15, 2017
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This python script uses the face_recognition library to compare a single face to the faces found in a pool of images
import face_recognition
from shutil import copyfile
# Create an encoding of my facial features that can be compared to other faces
picture_of_me = face_recognition.load_image_file("mavrodis.jpg")
my_face_encoding = face_recognition.face_encodings(picture_of_me)[0]
# Iterate through all the 10,460 pictures
for i in range(1, 10461):
# Construct the picture name and print it
file_name = str(i).zfill(5) + ".jpg"
# Load this picture
new_picture = face_recognition.load_image_file(file_name)
# Iterate through every face detected in the new picture
for face_encoding in face_recognition.face_encodings(new_picture):
# Run the algorithm of face comaprison for the detected face, with 0.5 tolerance
results = face_recognition.compare_faces([my_face_encoding], face_encoding, 0.5)
# Save the image to a seperate folder if there is a match
if results[0] == True:
copyfile(file_name, "/home/deeplearning/Desktop/my_face/mavrodis/" + file_name)
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