Python基于OpenCV Haar级联分类器的人脸检测实战

# -*-coding:utf8-*-#
import os
import cv2
from PIL import Image, ImageDraw
from datetime import datetime

"""
分类器 https://github.com/opencv/opencv/tree/master/data/haarcascades
安装模块：pip install Pillow pip install opencv-python
博客：https://blog.52itstyle.vip/archives/3771/
"""


def detectFaces(image_name):
 img = cv2.imread(image_name)
 face_cascade = cv2.CascadeClassifier(os.getcwd()+"\\haarcascade\\haarcascade_frontalface_alt.xml")
 if img.ndim == 3:
  gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
 else:
  gray = img # if语句：如果img维度为3，说明不是灰度图，先转化为灰度图gray，如果不为3，也就是2，原图就是灰度图

 faces = face_cascade.detectMultiScale(gray, 1.2, 5) # 1.3和5是特征的最小、最大检测窗口，它改变检测结果也会改变
 result = []
 for (x, y, width, height) in faces:
  result.append((x, y, x + width, y + height))
 return result


# 保存人脸图
def saveFaces(image_name):
 faces = detectFaces(image_name)
 if faces:
  # 将人脸保存在save_dir目录下。
  # Image模块：Image.open获取图像句柄，crop剪切图像(剪切的区域就是detectFaces返回的坐标)，save保存。
  save_dir = image_name.split('.')[0] + "_faces"
  os.mkdir(save_dir)
  count = 0
  for (x1, y1, x2, y2) in faces:
   file_name = os.path.join(save_dir, str(count) + ".jpg")
   Image.open(image_name).crop((x1, y1, x2, y2)).save(file_name)
   count += 1


if __name__ == '__main__':
 time1 = datetime.now()
 result = detectFaces(os.getcwd()+"\\images\\gaoyuanyuan.jpg")
 time2 = datetime.now()
 print("耗时：" + str(time2 - time1))
 if len(result) > 0:
  print("有人存在！！---》人数为：" + str(len(result)))
 else:
  print('视频图像中无人！！')

 drawFaces(os.getcwd()+"\\images\\", "hanxue.jpg")
 saveFaces(os.getcwd()+\\images\\gaoyuanyuan.jpg)