Python Face recognition and age estimation

Code
import cv2

import argparse

#from PIL import Image

import face_recognition as fr

import numpy as np

import os



path = "./train/"



known_names = []

known_name_encodings = []



images = os.listdir(path)

for _ in images:

    image = fr.load_image_file(path + _)

    image_path = path + _

    encoding = fr.face_encodings(image)[0]



    known_name_encodings.append(encoding)

    known_names.append(os.path.splitext(os.path.basename(image_path))[0].capitalize())



print(known_names)



parser=argparse.ArgumentParser()

parser.add_argument("-i", "--image", type=str, default="./test/man1.jpg",

     help="path to the input image")



args=parser.parse_args()



image = cv2.imread(args.image)





face_locations = fr.face_locations(image)

face_encodings = fr.face_encodings(image, face_locations)



for (top, right, bottom, left), face_encoding in zip(face_locations, face_encodings):

    matches = fr.compare_faces(known_name_encodings, face_encoding)

    name = ""



    face_distances = fr.face_distance(known_name_encodings, face_encoding)

    best_match = np.argmin(face_distances)



    if matches[best_match]:

        name = known_names[best_match]



def highlightFace(net, frame, conf_threshold=0.7):

    frameOpencvDnn=frame.copy()

    frameHeight=frameOpencvDnn.shape[0]

    frameWidth=frameOpencvDnn.shape[1]

    blob=cv2.dnn.blobFromImage(frameOpencvDnn, 1.0, (300, 300), [104, 117, 123], True, False)



    net.setInput(blob)

    detections=net.forward()

    faceBoxes=[]

    for i in range(detections.shape[2]):

        confidence=detections[0,0,i,2]

        if confidence>conf_threshold:

            x1=int(detections[0,0,i,3]*frameWidth)

            y1=int(detections[0,0,i,4]*frameHeight)

            x2=int(detections[0,0,i,5]*frameWidth)

            y2=int(detections[0,0,i,6]*frameHeight)

            faceBoxes.append([x1,y1,x2,y2])

            cv2.rectangle(frameOpencvDnn, (x1,y1), (x2,y2), (0,255,0), int(round(frameHeight/150)), 8)

    return frameOpencvDnn,faceBoxes



faceProto="opencv_face_detector.pbtxt"

faceModel="opencv_face_detector_uint8.pb"

ageProto="age_deploy.prototxt"

ageModel="age_net.caffemodel"

genderProto="gender_deploy.prototxt"

genderModel="gender_net.caffemodel"



MODEL_MEAN_VALUES=(78.4263377603, 87.7689143744, 114.895847746)

ageList=['(0-2)', '(4-6)', '(8-12)', '(15-20)', '(25-32)', '(38-43)', '(48-53)', '(60-100)']

genderList=['Male','Female']



faceNet=cv2.dnn.readNet(faceModel,faceProto)

ageNet=cv2.dnn.readNet(ageModel,ageProto)

genderNet=cv2.dnn.readNet(genderModel,genderProto)



video=cv2.VideoCapture(args.image if args.image else 0)

padding=20

while cv2.waitKey(1)<0 :

    hasFrame,frame=video.read()

    if not hasFrame:

        cv2.waitKey()

        break

    

    resultImg,faceBoxes=highlightFace(faceNet,frame)

    if not faceBoxes:

        print("No face detected")

        

    for faceBox in faceBoxes:

        face=frame[max(0,faceBox[1]-padding):

                   min(faceBox[3]+padding,frame.shape[0]-1),max(0,faceBox[0]-padding)

                   :min(faceBox[2]+padding, frame.shape[1]-1)]

            



        blob=cv2.dnn.blobFromImage(face, 1.0, (227,227), MODEL_MEAN_VALUES, swapRB=False)

        genderNet.setInput(blob)

        genderPreds=genderNet.forward()

        gender=genderList[genderPreds[0].argmax()]

        print(f'Gender: {gender}')



        ageNet.setInput(blob)

        agePreds=ageNet.forward()

        age=ageList[agePreds[0].argmax()]

        print(f'Age: {age[1:-1]} years')



    # cv2.rectangle(image, (left, top), (right, bottom), (0, 0, 255), 2)

    # cv2.rectangle(image, (left, bottom - 15), (right, bottom), (0, 0, 255), cv2.FILLED, cv2.LINE_AA)

    font = cv2.FONT_HERSHEY_DUPLEX

    cv2.putText(resultImg, name, (left + 6, bottom + 30), font, 0.7, (255, 255, 255), 1, cv2.LINE_AA)

    cv2.putText(resultImg, f'{gender}, {age}', (left + 6, bottom + 50), font, 0.7, (255, 255, 255), 1)

    cv2.imshow("Result", resultImg)

    

# cv2.putText(resultImg, f'{gender}, {age}', (faceBox[0], faceBox[1]-10), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0,255,255), 2, cv2.FILLED, cv2.LINE_AA)

# cv2.imshow("Detecting age and gender", resultImg)

#cv2.imwrite("./output.jpg", image)



cv2.waitKey(0)

cv2.destroyAllWindows()