基于Opencv-python人脸口罩检测

""" # File : mask_check.py # Time ：2021/6/10 15:02 # Author ：Meng # version ：python 3.10 # 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("./haarcascades/haarcascade_mcs_nose.xml") # 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) # 画框标识鼻子 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("./haarcascades/haarcascade_eye_tree_eyeglasses.xml") # 文件所在的具体位置 '''此文件是opencv的haar眼睛特征分类器''' 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/train_301.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) # Hmin= cv2.getTrackbarPos("Hmin", 'skin') # 获取bar Hmax= cv2.getTrackbarPos("Hmax", 'skin') if Hmin> Hmax: Hmax= Hmin thresh_h = cv2.inRange(H, Hmin, Hmax) # 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()