Help with face tracking

edit

Hello Everyone! I would like to be able to take an image (just 1) of a face that appears in front of the camera and track it until it leaves the frame. Currently the program will continuously take images until the person is out of view. This program is being used on a Raspberry Pi 3 B+.

Here is my code: Appreciate any help or insight

 #-----------------------------------------------------------------------
#------------------FUNCTIONS--------------------------------------------
#-----------------------------------------------------------------------

#function will find the last image taken and extract counter number
def fileNamer1():
    initialList = os.listdir(directory)
    fList =[x.split('.')[0] for x in initialList]
    if len(fList) != 0:
        print (fList)
        highestcount =int(fList[0].split('_')[1])

    for x in fList:
        #print(max + "<"+ x.split("_")[1])
        if(highestcount < int(x.split('_')[1])):
            highestcount =int(x.split('_')[1])
#_______________________________________________________________________



#put boxes around detected object and save image
def detect_face(face_recog):
    global highestcount

    # Capture frame-by-frame
    frame = vs.read()
    originalframeSize = frame
    frame = imutils.resize(frame, width=200)#by makingframe smaller we allow faster processing


    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    faces = faceCascade.detectMultiScale(
        gray,
        scaleFactor=1.1,
        minNeighbors=5,
        minSize=(30, 30),
        flags=cv2.cv.CV_HAAR_SCALE_IMAGE
    )

    # Draw a rectangle around the faces
    for (x, y, w, h) in faces:
        cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
        # also can put a trigger here
        highestcount +=1
        myfile = directory + filename + "_"+ str(highestcount) + stem
        cv2.imwrite(myfile, originalframeSize) #ALL IMAGES ARE BEING SAVED WHENEVER A FACE APPEARS WITHIN A FRAME 


        print('captured ' + str(highestcount))


    # Display the resulting frame
    cv2.imshow('Video', frame)

#_______________________________________________________________________


#--------------------------------------------------------------------
#-------Initializing-------------------------------------------------
#--------------------------------------------------------------------
#choose delay time in seconds 
#delay =10

cascPath = "haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(cascPath)
face_recog = cv2.createLBPHFaceRecognizer()
#video_capture = cv2.VideoCapture(0)



# default location to store files & name to use
directory='/home/pi/BLAH/web/imgs/'
filename ="road"
stem =".jpg"
highestcount =0
initialList ={} 

fileNamer1()
#print("iam max " + str((max))) 

# Set initial frame size.
frameSize = (960, 720)#change this number to change image resolution for saving
vs = VideoStream(src=0, usePiCamera=True, resolution=frameSize,
        framerate=32).start()

# Allow the camera to warm up.
time.sleep(1.0)





#this is the actual 'do stuff' part. It runs forever
while True: 

    #do the below function
    detect_face(face_recog)

    checkme = cv2.waitKey(25)

    if checkme & 0xFF == ord('q'):
        print "Exiting"
        break

    #time.sleep(1) # put a pause in

    #time.sleep(delay)

# When everything is done, release the capture
vs.release
vs.stop()
cv2.destroyAllWindows()