基于python+opencv的人脸识别框选

训练数据是opencv GitHub官方地址的模型,数据是五六年前的,小demo试用

opencv官方xml的老格式数据模型
我也觉得比较老了,毕竟好多年前的了,后面再使用主流的模型,也想自己训练模型数据

main.py

from kgOpencv import opencvBase
from kgOpencv import utils


# 图片存在的文件夹
IMAGE_FOLDER_PATH = "image/"
MODE_FOLDER_PATH = "mode/"

if __name__ == '__main__':
    print("程序测试")

    # 获取图片资源
    imagePaths = utils.getFileAllPathOnFolder(r'image')
    # 获取训练模型资源
    modePaths = utils.getFileAllPathOnFolder(r'mode')
    for mode in modePaths:
        print(mode)
        for i in imagePaths:
            opencvBase.recognitionPersion(IMAGE_FOLDER_PATH+i,mode=MODE_FOLDER_PATH+mode,width=500,height=500)

utils.py

import os

# 获取一个目录下所有文件的路径
def getFileAllPathOnFolder(folder):

    if not os.path.exists(folder):
        raise ("请检查你的文件夹路径是否完整")

    filesName = os.listdir(folder)
    if filesName.__len__() <= 0:
        raise ("该目录下没有任何文件,请检查路径是否完整")

    return filesName

opencvBase.py

import cv2
import os


#读取图片
def __loadImage(path,width = 0 , height = 0):
    # 判断文件是否存在
    if os.path.exists(path) == False:
        raise RuntimeError("错误!文件不存在,请检查路径是否完整!")

    # 加载图片
    img = cv2.imread(path,1)

    # 调节图片大小,较上一个版本改进,可以单独传一个参数width或者height
    if width != 0 or height != 0:
        size = img.shape
        if width == 0:
            width = size[0]
        if height == 0:
            height = size[1]

        tmpImg = cv2.resize(img, (width, height))
        img = tmpImg

    # 判空
    if img is None:
        raise RuntimeError("img 对象不存在")

    return img


#显示一种图片
#colorful=1 表示加载彩色图片   0表示黑白图片
def showImageByPath(path,width = 0, height = 0):
    img = __loadImage(path,width,height)
    cv2.imshow("show image",img)
    #0表示任意键退出
    cv2.waitKey(0)
    cv2.destroyAllWindows()


#单纯显示图片,注意传入参数
def showImage(img,sleep = 0):
    if img is None:
        pass
    else :
        cv2.imshow("face Recognition",img)
        # 0表示任意键退出
        cv2.waitKey(sleep)
        cv2.destroyAllWindows()

#识别人体特征,默认识别人脸
def recognitionPersion(path,mode = "mode/haarcascade_frontalface_alt.xml",height = 0,width = 0):
    faceImg = __loadImage(path,width,height)
    grayImg = cv2.cvtColor(faceImg,cv2.COLOR_BGR2GRAY)
    #联级分类器,提取面部特征
    faceClassifier = cv2.CascadeClassifier(mode)
    faces = faceClassifier.detectMultiScale(grayImg,scaleFactor=1.05,minNeighbors=2)

    for x,y,w,h in faces:
        faceImg=cv2.rectangle(faceImg,(x,y),(x+w,y+h),(0,255,0),3)

    showImage(faceImg,2000)

后面更新打算同过小爬虫爬取图片