Python OpenCV calls the camera to detect the face and take a screenshot

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")