In this article, we share the specific code of Python OpenCV calling the camera to detect faces and take screenshots for your reference. The specific contents are as follows

Note: The OpenCV library needs to be installed in python, and the OpenCV face recognition model haarcascade_frontalface_alt. xml needs to be downloaded. The model can be downloaded in OpenCV-PCA-KNN-SVM_face_recognition.

Use OpenCV to call the camera to detect the face and take 100 consecutive screenshots

#-*- coding: utf-8 -*-
# import  Advance openCV Library of
import cv2

### Call the computer camera to detect the face and take a screenshot

def CatchPICFromVideo(window_name, camera_idx, catch_pic_num, path_name):
 cv2.namedWindow(window_name)

 # Video source, which can come from 1 Saved video, or directly from USB Camera
 cap = cv2.VideoCapture(camera_idx)

 # Tell OpenCV Using a face recognition classifier
 classfier = cv2.CascadeClassifier("haarcascade_frontalface_alt.xml")

 # The color of the border to be drawn after recognizing the face, RGB Format , color Yes 1 An array that cannot be added or deleted
 color = (0, 255, 0)

 num = 0
 while cap.isOpened():
 ok, frame = cap.read() # Read 1 Frame data
 if not ok:
  break

 grey = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) # Converts the current frame image to a grayscale image

 # Face detection, 1.2 And 2 They are the scaling ratio of the picture and the number of effective points to be detected
 faceRects = classfier.detectMultiScale(grey, scaleFactor = 1.2, minNeighbors = 3, minSize = (32, 32))
 if len(faceRects) > 0:  # Greater than 0 A face is detected
  for faceRect in faceRects: # Box each separately 1 Zhang Face
  x, y, w, h = faceRect

  # Save the current frame as a picture
  img_name = "%s/%d.jpg" % (path_name, num)
  #print(img_name)
  image = frame[y - 10: y + h + 10, x - 10: x + w + 10]
  cv2.imwrite(img_name, image,[int(cv2.IMWRITE_PNG_COMPRESSION), 9])

  num += 1
  if num > (catch_pic_num): # Exit the loop if the specified maximum save quantity is exceeded
   break

  # Draw a rectangular frame
  cv2.rectangle(frame, (x - 10, y - 10), (x + w + 10, y + h + 10), color, 2)

  # Shows how many face images you've captured so you can stand there and be photographed with a count in mind, without having to look at your eyes 1 Smear and wait
  font = cv2.FONT_HERSHEY_SIMPLEX
  cv2.putText(frame,'num:%d/100' % (num),(x + 30, y + 30), font, 1, (255,0,255),4)

  # End the program beyond the specified maximum number of saves
 if num > (catch_pic_num): break

 # Display image
 cv2.imshow(window_name, frame)
 c = cv2.waitKey(10)
 if c & 0xFF == ord('q'):
  break

  # Release the camera and destroy all windows
 cap.release()
 cv2.destroyAllWindows()

if __name__ == '__main__':
 #  Continuous section 100 Image, save in image In the folder
 CatchPICFromVideo("get face", 0, 99, "/image")