Face detection and time - video

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Code:
#!/usr/bin/env python37
#Raspberry pi 3B/3B+, 4B, Buster, OpenCV 4.2.0
#Date: 5th Apriol, 2020

import numpy as np
import cv2
from datetime import datetime

face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
fourcc = cv2.VideoWriter_fourcc(*'XVID')  
out = cv2.VideoWriter('face_detection.avi', fourcc, 10.0, (640, 480))
font = cv2.FONT_HERSHEY_SIMPLEX

cap = cv2.VideoCapture(0)

while cap.isOpened():
    date_time = str(datetime.today().strftime("%d-%m-%Y")
                    + '                '
                    + str(datetime.now().strftime("%H:%M:%S")))

    ret, frame = cap.read()
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
    for (x,y,w,h) in faces:
        cv2.rectangle(frame, (x, y),(x+w, y+h),(255, 0, 0), 2)

    out.write(frame)
    cv2.putText(frame, date_time, (30, 400), font, 1,
                (0, 0, 255), 2, cv2.LINE_AA)

    cv2.imshow('img', frame)
    k = cv2.waitKey(1)  
    if k is 27:
        break

cap.release()
cv2.destroyAllWindows()

In line 32, I change == to is operator for python 3.7 or later. You may used == if its doesn't work.

the video plays faster than realtime because that's a useful behavior to rapidly work through data.

if you want it to "play" at 1x speed, you'll need to insert some waiting. you can pass such a delay to waitKey() in milliseconds.

you could simply pass in 1000 / cap.get(cv.CAP_PROP_FPS) but that won't account for processing time and your video will play slower than realtime.

that's why you should do the following:

# ... open capture...
tstart = time.perf_counter() # in seconds
# ... loop starts...
    pts = cap.get(cv.CAP_PROP_POS_MSEC) # in milliseconds
    # ... cap.read()...
    # ... your processing and imshow()...
    time_left = pts - 1000 * (time.perf_counter() - tstart) # in milliseconds
    cv.waitKey(int(max(1, time_left)))

that is also not perfect. waitKey will return sooner if you press a key, which makes the video play faster. it will maintain the correct pace though. how it works: the 'pts' is the presentation timestamp of the frame you are reading. after all processing for the frame is done, we calculate how much time has elapsed, and how much is left before this frame is due for presentation. we then give that time remaining to waitKey()