main.py

import picamera
import cv2 as cv
import argparse
import time
import os
import simpleaudio

def recognizeFace(client,image,collection):
    face_matched = False
    with open(image, 'rb') as file:
        response = client.search_faces_by_image(CollectionId=collection, Image={'Bytes': file.read()}, MaxFaces=1, FaceMatchThreshold=85)
        if (not response['FaceMatches']):
            face_matched = False
        else:
            face_matched = True
    return face_matched, response

def detectFace(frame,face_cascade):	
    face_detected = False
    #Detect faces
    faces = face_cascade.detectMultiScale(frame,
        scaleFactor=1.1,
        minNeighbors=5,
        minSize=(30, 30),
        flags = cv.CASCADE_SCALE_IMAGE)
    print("Found {0} faces!".format(len(faces)))
    timestr = time.strftime("%Y%m%d-%H%M%S")
    image = '{0}/image_{1}.png'.format(directory, timestr)
    if len(faces) > 0 :
        face_detected = True
        cv.imwrite(image,frame) 
        print ('Your image was saved to %s' % image)

    return face_detected, image

def main():	
    #get the dir 
    dir_path = os.path.dirname(os.path.realpath(__file__))
    #get args
    parser = argparse.ArgumentParser(description='Facial recognition')
    parser.add_argument('--collection', help='Collection Name', default='chappie-faces')
    parser.add_argument('--face_cascade', help='Path to face cascade.', default= dir_path + '/haarcascade_frontalface_default.xml')
    parser.add_argument('--camera', help='Camera device number.', type=int, default=0)
    args = parser.parse_args()

    #intialize opencv face detection
    face_cascade_name = args.face_cascade
    face_cascade = cv.CascadeClassifier()

    #Load the cascades
    if not face_cascade.load(cv.samples.findFile(face_cascade_name)):
        print('--(!)Error loading face cascade')
        exit(0)

    camera_device = args.camera

    #Read the video stream
    cam = cv.VideoCapture(camera_device)
    #setting the buffer size and frames per second, to reduce frames in buffer
    cam.set(cv.CAP_PROP_BUFFERSIZE, 1)
    cam.set(cv.CAP_PROP_FPS, 2);

    if not cam.isOpened:
        print('--(!)Error opening video capture')
        exit(0)

    #initialize reckognition sdk

    while True:
        frame = {}
        #calling read() twice as a workaround to clear the buffer.
        cam.read()
        cam.read()
        ret, frame = cam.read()		
        if frame is None:
            print('--(!) No captured frame -- Break!')
            break

        face_detected, image = detectFace(frame,face_cascade)

        if (face_detected):
            os.system("aplay alexa.wav")
            print("hello!!")

        time.sleep(0.001)

    # When everything done, release the capture
    cam.release()
    cv.destroyAllWindows()

dirname = os.path.dirname(__file__)
directory = os.path.join(dirname, 'faces')
main()