This article shares the specific code of python dynamic face detection for your reference. The specific content is as follows

Code directly: Press Q to exit

import cv2
import numpy as np

cv2.namedWindow("test")
cap = cv2.VideoCapture(0) # Loading camera recording
# cap = cv2.VideoCapture("test.mp4") # Open the video file
success, frame = cap.read()
# classifier = cv2.CascadeClassifier("/Users/yuki/anaconda/share/OpenCV/haarcascades/haarcascade_frontalface_alt.xml")

#  Ensure that the xml The file with the py The file in 1 If not, change this to absolute path

#haarcascade_frontalface_default.xml
classifier = cv2.CascadeClassifier("/Users/yuki/anaconda/share/OpenCV/haarcascades/haarcascade_frontalface_default.xml")

#  Ensure that the xml The file with the py The file in 1 If not, change this to absolute path

while success:
 success, frame = cap.read()
 size = frame.shape[:2]
 image = np.zeros(size, dtype=np.float16)
 image = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
 cv2.equalizeHist(image, image)
 divisor = 8
 h, w = size
 minSize = (w // divisor, h // divisor)
 faceRects = classifier.detectMultiScale(image, 1.2, 2, cv2.CASCADE_SCALE_IMAGE, minSize)
 if len(faceRects) > 0:
  for faceRect in faceRects:
   x, y, w, h = faceRect
   cv2.rectangle(frame,(x,y),(x+h,y+w),(0,255,0),2)
   # lock   Eyes and mouth
#cv2.circle(frame, (x + w // 4, y + h // 4 + 30), min(w // 8, h // 8), (255, 0, 0)) #  The left eye
#cv2.circle(frame, (x + 3 * w //4, y + h // 4 + 30), min(w // 8, h // 8), (255, 0, 0)) # In the right eye
#cv2.rectangle(frame, (x + 3 * w // 8, y + 3 * h // 4), (x + 5 * w // 8, y + 7 * h // 8), (255, 0, 0))# The mouth
 cv2.imshow("test", frame)
 key = cv2.waitKey(10)
 c = chr(key & 255)
 if c in ['q', 'Q', chr(27)]:
  break
cv2.destroyWindow("test")