python openCV获取人脸部分并存储功能

本文实例为大家分享了python openCV获取人脸部分并存储的具体代码，供大家参考，具体内容如下

#-*- 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]
 # 以时间戳和读取的排序作为文件名称
 listStr = [str(int(time.time())), str(count)]
 fileName = ''.join(listStr)
 # 图片存储
 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),(0,0,255),2)
 
 
 count += 1
 
 cv2.imshow('opencvCut',frame)
 k = cv2.waitKey(30) & 0xff
 if k == 27:
 break
cap.release()
cv2.destroyAllWindows()

小编再为大家分享一段代码：python用opencv批量检测人脸，并保存：

import cv2
import sys
import os
from PIL import Image
cascPath = "haarcascade_frontalface_default.xml" #训练参数文件
faceCascade = cv2.CascadeClassifier(cascPath)#分类器
 
base = 'new_dir\\'
for img in os.listdir(base):
 image = cv2.imread(base + img)#读取图片
 gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
 gray = cv2.equalizeHist(gray) #直方图均衡化，提高分类效果
 faces = faceCascade.detectMultiScale(
 gray,
 scaleFactor=1.1,
 minNeighbors=5,
 minSize=(10, 10)
 )
 num = 0
 for (x, y, w, 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内容，希望对大家的学习有所帮助，也希望大家多多支持脚本之家。