faceencodings.py

from imutils import paths
import face_recognition
import argparse
import pickle
import cv2
import os


ap = argparse.ArgumentParser()
ap.add_argument("-i","--dataset",required=True,help="path to input directory of face+images")
ap.add_argument("-e","--encodings",required=True,help="path to serialized db of facial encodings")
ap.add_argument("-d","--detection-method",type=str,default="hog",help="face detection model to use: either 'hog' or 'cnn' ")
args = vars(ap.parse_args())


print("Encoding faces........")
imagePaths = list(paths.list_images(args["dataset"]))


knownEncodings = []
knownNames = []
name="Unknown"


for (i,imagePath) in enumerate(imagePaths):
    print("processing image {}/{} ".format(i+1,len(imagePaths)))
    name = imagePath.split(os.path.sep)[-2]


    image = cv2.imread(imagePath)
    rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)


    boxes = face_recognition.face_locations(rgb,model=args["detection_method"])

    encodings = face_recognition.face_encodings(rgb,boxes)

    for encoding in encodings:

        knownEncodings.append(encoding)
        knownNames.append(name)


print("Serializing encodings.....")
data = {"encodings" : knownEncodings , "names" : knownNames}
f = open(args["encodings"], "wb")
f.write(pickle.dumps(data))
f.close