face_Recogniser/code.py at master · NitinShaily/face_Recogniser · GitHub

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#%%
import cv2
import numpy as np

#%%
MODEL_MEAN_VALUES = (78.4263377603, 87.7689143744, 114.895847746)
age_list = ['(0, 2)', '(4, 6)', '(8, 12)', '(20, 25)', '(25, 32)', '(38, 43)', '(48, 53)', '(60, 100)']
gender_list = ['Male', 'Female']
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
font = cv2.FONT_HERSHEY_SIMPLEX


#%%
def load_caffe_models():
    age_net = cv2.dnn.readNetFromCaffe('deploy_age.prototxt', 'age_net.caffemodel')
    gender_net = cv2.dnn.readNetFromCaffe('deploy_gender.prototxt', 'gender_net.caffemodel')
    return(age_net, gender_net)


#%%
def video_detector(age_net, gender_net):


    cap = cv2.VideoCapture(0)
    cap.set(3, 480)
    cap.set(4, 640)

    while True:
        ret, image = cap.read()
        counter=0
        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
        faces = face_cascade.detectMultiScale(gray, 1.1, 5)
        if(len(faces)>counter):
            print("Found {} faces".format(str(len(faces))))
            counter+=1
        if(len(faces)>counter):
            counter+=len(faces)

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

            face_img = image[y:y+h, h:h+w].copy()
            blob = cv2.dnn.blobFromImage(face_img, 1, (227, 227), MODEL_MEAN_VALUES, swapRB=False)

            #gender

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

            #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" % ('Male', "[20-25]")
        cv2.putText(image, overlay_text, (x, y), font, 1, (255, 255, 255), 2, cv2.LINE_AA)

        cv2.imshow('frame', image)

        k = cv2.waitKey(30) & 0xff
        if k == 27:
            break
    cap.release()
    cv2.destroyAllWindows()


#%%
if __name__ == "__main__":
    age_net, gender_net = load_caffe_models()
    video_detector(age_net, gender_net)


# %%