"""
@author:  wangquaxiu
@time:  2018/9/11 14:36
facerec
"""
import cv2
import numpy as np

# 載入Load xml 引數1 file name
face_xml = cv2.CascadeClassifier('D:/opencv/sources/data/haarcascades/haarcascade_frontalface_default.xml')
eye_xml = cv2.CascadeClassifier('D:/opencv/sources/data/haarcascades/haarcascade_eye.xml')
if face_xml != None:
    print("xml檔案下載成功！")
# load jpg
img = cv2.imread('G:/photos/lena.jpg', 1)
if img is not None:
    print("圖片讀取成功！")
cv2.imshow('src', img)

# haar gray
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# detect faces 1 data 2 scale 3 5
# 檢測人臉 1 灰度圖片資料 2 縮放係數 3目標大小
faces = face_xml.detectMultiScale(gray, 1.3, 5)
# 人臉個數
print('face=', len(faces))

# 方框標定
for (x, y, w, h) in faces:
    # 起始座標
    cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
    # 我們已經找到的人臉區域
    roi_face = gray[y:y + h, x:x + w]
    roi_color = img[y:y + h, x:x + w]
    # 引數1 gray
    eyes = eye_xml.detectMultiScale(roi_face)
    print('eye=', len(eyes))
    for (e_x, e_y, e_w, e_h) in eyes:
        cv2.rectangle(roi_color, (e_x, e_y), (e_x + e_w, e_y + e_h), (0, 255, 0), 2)
cv2.imshow('dst', img)
cv2.waitKey()
 

效果：