video_detect.py

import numpy as np
import cv2

def video_detect(x):


    face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
    cap = cv2.VideoCapture(x)
    
    cap.set(3,640) # set Width
    cap.set(4,480) # set Height

    while True:
        ret, img = cap.read()
        img = cv2.flip(img, 1)
        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        faces = face_cascade.detectMultiScale(
            gray,     
            scaleFactor=1.2,
            minNeighbors=5,     
            minSize=(20, 20)
        )
        for (x,y,w,h) in faces:
            cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
            roi_gray = gray[y:y+h, x:x+w]
            roi_color = img[y:y+h, x:x+w]  
        cv2.imshow('video',img)
        k = cv2.waitKey(30) & 0xff
        if k == 27: # press 'ESC' to quit
            break

    cap.release()
    cv2.destroyAllWindows()


def video_cap(x):

    cap = cv2.VideoCapture(x)

    while(True):
        ret, frame = cap.read()

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

        cv2.imshow('frame', gray)
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break

    cap.release()
    cv2.destroyAllWindows()