本文例項為大家分享了python openCV獲取人臉部分並存儲的具體程式碼，供大家參考，具體內容如下

#-*- coding:utf-8 -*-
import cv2
import os
import time
import base64
import numpy as np
 
save_path = 'E:\\opencv\\2018-04-24OpenCv\\RAR\\savetest'
faceCascade = cv2.CascadeClassifier(
  './haarcascade_frontalface_alt.xml')
 
cap = cv2.VideoCapture(0)
 
count = 0
 
while True:
  ret,frame = cap.read()
  gray = cv2.cvtColor(frame,cv2.COLOR_RGB2GRAY)
  rect = faceCascade.detectMultiScale(gray,scaleFactor=1.3,minNeighbors=9,minSize=(50,50),flags=cv2.CASCADE_SCALE_IMAGE
                  )
 
  if not rect is ():
    for x,y,w,h in rect:
      roiImg = frame[y:y+h,x:x+w]
      # 以時間戳和讀取的排序作為檔名稱
      listStr = [str(int(time.time())),str(count)]
      fileName = ''.join(listStr)
      # 圖片儲存
      cv2.imwrite(save_path + os.sep + '%s.jpg' % fileName,roiImg)
      # print (roiImg)
      # roiTobase64 = cv2.imencode(roiImg,np.uint8)
      # print (base64.b64encode(roiTobase64))
      cv2.rectangle(frame,(x,y),(x+w,y+h),(0,255),2)
 
 
      count += 1
 
  cv2.imshow('opencvCut',frame)
  k = cv2.waitKey(30) & 0xff
  if k == 27:
    break
cap.release()
cv2.destroyAllWindows()

小編再為大家分享一段程式碼：python用opencv批量檢測人臉，並儲存：

import cv2
import sys
import os
from PIL import Image
cascPath = "haarcascade_frontalface_default.xml" #訓練引數檔案
faceCascade = cv2.CascadeClassifier(cascPath)#分類器
 
base = 'new_dir\\'
for img in os.listdir(base):
  image = cv2.imread(base + img)#讀取圖片
  gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
  gray = cv2.equalizeHist(gray) #直方圖均衡化，提高分類效果
  faces = faceCascade.detectMultiScale(
    gray,scaleFactor=1.1,minNeighbors=5,minSize=(10,10)
  )
  num = 0
  for (x,h) in faces:
    cv2.imwrite("face_dir\\" + img,image[y:y+h,x:x+w])
    num += 1
#   cv2.imshow("Faces found",image)
  cv2.waitKey(0)

以上就是本文的全部內容，希望對大家的學習有所幫助，也希望大家多多支援我們。