predict.py

import cv2
import imutils
import time
import numpy as np

cap = cv2.VideoCapture(0)


MODEL_MEAN_VALUES = (78.4263377603, 87.7689143744, 114.895847746)
age_list = ['(0, 3)', '(4, 7)', '(8, 12)', '(13, 16)', '(17, 20)',
            '(21, 24)', '(25, 30)', '(31, 37)', '(38, 43)', '(44, 48)', '(48, 53)', '(53, 60)', '(61, 100)']
gender_list = ['Male', 'Female']

# Model Loading


def initialize_caffe_models():
    age_net = cv2.dnn.readNetFromCaffe(
        'data/deploy_age.prototxt',
        'data/age_net.caffemodel')

    gender_net = cv2.dnn.readNetFromCaffe(
        'data/deploy_gender.prototxt',
        'data/gender_net.caffemodel')

    return(age_net, gender_net)


def read_from_camera(age_net, gender_net):

    while True:
        ret, image = cap.read()

        face_cascade = cv2.CascadeClassifier(
            'data/haarcascade_frontalface_alt.xml')  # loading CascadeCalssifier

        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
        faces = face_cascade.detectMultiScale(gray, 1.1, 5)

        if(len(faces) > 0):
            print("-----------------------------")
            print("Found {} faces".format(str(len(faces))))

        for (x, y, w, h)in faces:
            cv2.rectangle(image, (x, y), (x+w, y+h), (0, 0, 255), 2)

            # Get Face
            face_img = image[y:y+h, h:h+w].copy()  # crop detected face
            blob = cv2.dnn.blobFromImage(
                face_img, 1, (227, 227), MODEL_MEAN_VALUES, swapRB=True)

            # Predict Gender
            gender_net.setInput(blob)
            gender_preds = gender_net.forward()
            gender = gender_list[gender_preds[0].argmax()]
            print("Gender : " + gender)

            # Predict Age
            age_net.setInput(blob)
            age_preds = age_net.forward()
            age = age_list[age_preds[0].argmax()]
            print("Age Range: " + age)

            overlay_text = "%s %s" % (gender, age)
            cv2.putText(image, overlay_text, (x, y),
                        cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2, cv2.LINE_AA)

        cv2.imshow('frame', image)

        if cv2.waitKey(1) & 0xFF == ord('q'):
            break


if __name__ == "__main__":
    age_net, gender_net = initialize_caffe_models()

    read_from_camera(age_net, gender_net)