Python学习案例之图片人脸检测识别

# -*-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")