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【听图阁-专注于Python设计】。