分类： Python/Ruby
2021-06-17 17:36:24
"""
# File : mask_check.py
# Time ：2021/6/10 15:02
# Author ：Meng
# version ：python 3.6
# Description：
"""
import cv2 # 导入opencv
import time # 导入time
"""实现鼻子检测"""
def nose_dection(img):
img = cv2.GaussianBlur(img,(5,5),0)#高斯滤波
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # 将图片转化成灰度
nose_cascade = cv2.CascadeClassifier("haarcascade_mcs_nose.xml")
nose_cascade.load("data/haarcascades/haarcascade_mcs_nose.xml") # 一定要告诉编译器文件所在的具体位置
'''此文件是opencv的haar鼻子特征分类器'''
noses = nose_cascade.detectMultiScale(gray, 1.3, 5) # 鼻子检测
for(x,y,w,h) in noses:
cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2) # 画框标识脸部
flag = 0 # 检测到鼻子的标志位，如果监测到鼻子，则判断未带口罩
if len(noses)>0:
flag = 1
return img,flag
""""实现眼睛检测"""
def eye_dection(img):
img = cv2.GaussianBlur(img,(5,5),0)#高斯滤波
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # 将图片转化成灰度
eyes_cascade = cv2.CascadeClassifier("haarcascade_eye_tree_eyeglasses.xml")
eyes_cascade.load("data/haarcascades/haarcascade_eye_tree_eyeglasses.xml") # 一定要告诉编译器文件所在的具体位置
'''此文件是opencv的haar眼镜特征分类器'''
eyes = eyes_cascade.detectMultiScale(gray, 1.3, 5) # 眼睛检测
for (x,y,w,h) in eyes:
frame = cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2) # 画框标识眼部
print("x y w h is",(x,y,w,h))
# frame = cv2.rectangle(img, (x, y+h), (x + 3*w, y + 3*h), (255, 0, 0), 2) # 画框标识眼部
return img,eyes
def empty(a):
pass
def main():
image = cv2.imread("images/backgound.png") # 读取背景照片
cv2.imshow('skin', image) # 展示
cv2.createTrackbar("Hmin", "skin", 0, 90, empty) # 创建bar
cv2.createTrackbar("Hmax", "skin", 25, 90, empty)
capture = cv2.VideoCapture(0) # 打开摄像头，其中0为自带摄像头，
while True:
ref,img=capture.read() # 打开摄像头
# img = cv2.imread("./images/005.jpg") # 读取一张图片
img_hsv = img
image_nose,flag_nose = nose_dection(img) # 进行口罩检测，返回检测之后的图形以及标志位
if flag_nose == 1: # 当检测到鼻子的时候，判断未戴口罩
frame = cv2.putText(image_nose, "NO MASK", (10, 30), cv2.FONT_HERSHEY_COMPLEX, 0.9,(0, 0, 255), 1) # 在图片上写字
cv2.imshow('img', image_nose) # 展示图片
if flag_nose == 0: # 未检测鼻子，进行眼睛检测
img_eye,eyes = eye_dection(img) # 进行眼睛检测，返回检测之后的图形以及标志位
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV) # 将图片转化成HSV格式
H, S, V = cv2.split(hsv) #
minH = cv2.getTrackbarPos("Hmin", 'skin') # 获取bar
maxH = cv2.getTrackbarPos("Hmax", 'skin')
if minH > maxH:
maxH = minH
thresh_h = cv2.inRange(H, minH, maxH) # 提取人体肤色区域
if len(eyes) > 1: # 判断是否检测到两个眼睛，其中eyes[0]为左眼坐标
# 口罩区域的提取
mask_x_begin = min(eyes[0][0],eyes[1][0]) # 把左眼的x坐标作为口罩区域起始x坐标
mask_x_end = max(eyes[0][0],eyes[1][0]) + eyes[list([eyes[0][0], eyes[1][0]]).index(max(list([eyes[0][0], eyes[1][0]])))][2] # 把右眼x坐标 + 右眼宽度作为口罩区域x的终止坐标
mask_y_begin = max(eyes[0][1] + eyes[0][3],eyes[1][1] + eyes[1][3]) + 20 # 把眼睛高度最大的作为口罩区域起始y坐标
if mask_y_begin > img_eye.shape[1]: # 判断是否出界
mask_y_begin = img_eye.shape[1]
mask_y_end = max(eyes[0][1] + 3 * eyes[0][3],eyes[1][1] + 3 * eyes[1][3]) + 20 # 同理
if mask_y_end > img_eye.shape[1]:
mask_y_end = img_eye.shape[1]
frame = cv2.rectangle(img_eye, (mask_x_begin, mask_y_begin), (mask_x_end, mask_y_end), (255, 0, 0), 2) # 画口罩区域的框
total_mask_pixel = 0
total_face_pixel = 0
# 遍历二值图，为0则total_mask_pixel+1，否则total_face_pixel+1
for i in range(mask_x_begin,mask_x_end):
for j in range(mask_y_begin,mask_y_end):
if thresh_h[i,j] == 0:
total_mask_pixel += 1
else:
total_face_pixel += 1
print("total_mask_pixel",total_mask_pixel)
print("total_face_pixel", total_face_pixel)
if total_mask_pixel > total_face_pixel:
frame = cv2.putText(img_eye, "HAVE MASK", (mask_x_begin, mask_y_begin - 10),cv2.FONT_HERSHEY_COMPLEX, 0.9, (0, 0, 255), 1) # 绘制
if total_mask_pixel < total_face_pixel:
frame = cv2.putText(img_eye, "NO MASK", (mask_x_begin, mask_y_begin - 10), cv2.FONT_HERSHEY_COMPLEX,0.9, (0, 0, 255), 1) # 绘制
cv2.imshow("skin", thresh_h) # 显示肤色图
cv2.imshow("img", img_eye) # 显示肤色图
# cv2.imwrite('005_result.jpg',img_eye) 保存图片
c = cv2.waitKey(10)
if c==27:
break
capture.release() #
cv2.destroyAllWindows() # 关闭所有窗口
if __name__ == '__main__':
main()
