from multiprocessing import Process, Queue
from queue import Empty
import cv2
import logging
import argparse
import numpy as np

def record(device_id, q1,q2, q3):
    capture = cv2.VideoCapture(device_id)
    while True:
        ret, image = capture.read()
        logging.debug('r')
        q1.put(image)
        q2.put(image)
        q3.put(image)


def process1(in_q, out_q):
    while True:
        image = in_q.get()
        logging.debug('r')
        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
        cgray = cv2.cvtColor(gray, cv2.COLOR_GRAY2BGR)
        out_q.put(cgray)

def process2(in_q, out_q):
    while True:
        image = in_q.get()
        logging.debug('r')
        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
        cgray = cv2.cvtColor(gray, cv2.COLOR_GRAY2BGR)
        out_q.put(cgray)

def display(image_res, q1, q2, q3):
    prev_image1 = np.zeros((image_res[1],image_res[0],3), np.uint8)
    prev_image2 = np.zeros((image_res[1],image_res[0],3), np.uint8)
    prev_image3 = np.zeros((image_res[1],image_res[0],3), np.uint8)
    prev_image4 = np.zeros((image_res[1],image_res[0],3), np.uint8)

    while True:
        logging.debug('r')
        try:
            image1 = q1.get_nowait()
            image1 = cv2.resize(image1, (image_res[0], image_res[1]))
            prev_image1 = image1
        except Empty as e:
            image1 = prev_image1
        try:
            image2 = q2.get_nowait()
            image2 = cv2.resize(image2, (image_res[0], image_res[1]))
            prev_image2 = image2
        except Empty as e:
            image2 = prev_image2
        try:
            image3 = q3.get_nowait()
            image3 = cv2.resize(image3, (image_res[0], image_res[1]))
            prev_image3 = image3
        except Empty as e:
            image3 = prev_image3
        
        image4 = prev_image4

        img_concate_Verti1 = np.concatenate((image1,image2),axis=0)
        img_concate_Verti2 = np.concatenate((image3,image4),axis=0)
        grid_img = np.concatenate((img_concate_Verti1,img_concate_Verti2),axis=1)
        cv2.imshow("Output", grid_img)
    
        # Hit 'q' on the keyboard to quit!
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break

if __name__ == '__main__':
    
    parser = argparse.ArgumentParser(description='Visualise face recognition algorithms.')
    parser.add_argument('--camera', '-c', type=int, default=0,
                        help='Numeric id of the camera')

    args = parser.parse_args()

    image_size = (int(1920/2), int(1080/2))
    # TODO should we use queues here at all?
    # https://docs.python.org/3/library/multiprocessing.html#programming-guidelines
    # TODO: queue maxsize, or prefrabily some sort of throttled queue (like zmq hight water mark)
    q_webcam1 = Queue()
    q_webcam2 = Queue()
    q_webcam3 = Queue()
    q_process1 = Queue()
    q_process2 = Queue()
    p1 = Process(target=record, args=(args.camera, q_webcam1, q_webcam2,q_webcam3))
    p2 = Process(target=display, args=(image_size, q_webcam1, q_process1, q_process2 ))
    p3 = Process(target=process1, args=(q_webcam2, q_process1,))
    p4 = Process(target=process2, args=(q_webcam3, q_process2,))
    p1.start()
    p2.start()
    p3.start()
    p4.start()
    p2.join()