opencv，脸部识别，画框，提取，处理

import cv2 as cv
import numpy as np

# 读取图片，并转换为灰度图片
face_image = cv.imread('211.jpg')

face_gray = cv.cvtColor(face_image, cv.COLOR_RGB2GRAY)
cv.imshow('gray face', face_gray)

# 检测人脸
XML_PATH = 'haarcascade_frontalface_default.xml'  # 人脸检测分类模型     注：模型较老，侧脸几乎识别不出来，建议正脸尝试
face_detector = cv.CascadeClassifier(XML_PATH)  # 实例化分类器
face_list = face_detector.detectMultiScale(face_gray)
cv.imshow('2',face_image)
print(face_list)
# 在人脸上标框
for face in face_list:
    rect_image = cv.rectangle(face_image, face, (0, 30, 100), 2) 
    cv.imshow('current image', rect_image)
# 截取人脸
x, y, w, h = face_list[0]
print(x,y,w,h)
face_rect = face_image[y:y + h, x:x + w]  # 获取人脸对应位置的数值
cv.imshow('current faces', face_rect)

# 进行旋转
center_point = [np.float32(w>>1),np.float32(h>>1)]  # 寻找中心点
mat = cv.getRotationMatrix2D(center_point, 30, 1) #30 强制旋转30°角，此处不太好
face_rotation = cv.warpAffine(face_rect, mat, (h, w))
cv.imshow('rotation face', face_rotation)

if cv.waitKey(0) & 0xFF == 27:
    cv.destroyAllWindows()

 'haarcascade_frontalface_default.xml' # 人脸检测分类模型