import numpy as np import cv2 import random # multiple cascades: https://github.com/Itseez/opencv/tree/master/data/haarcascades face_cascade = cv2.CascadeClassifier('data\xml\haarcascade_frontalface_default.xml') eye_cascade = cv2.CascadeClassifier('data\xml\haarcascade_eye.xml') mouth_cascade = cv2.CascadeClassifier('data\xml\haarcascade_mcs_mouth.xml') upper_body = cv2.CascadeClassifier('data\xml\haarcascade_upperbody.xml') # Adjust threshold value in range 80 to 105 based on your light. bw_threshold = 80 # User message font = cv2.FONT_HERSHEY_SIMPLEX org = (30, 30) weared_mask_font_color = (255, 255, 255) not_weared_mask_font_color = (0, 0, 255) thickness = 2 font_scale = 1 weared_mask = "Thank You for wearing MASK" not_weared_mask = "Please wear MASK to defeat Corona" # Read video cap = cv2.VideoCapture(0) while 1: # Get individual frame ret, img = cap.read() img = cv2.flip(img,1) # Convert Image into gray gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # Convert image in black and white (thresh, black_and_white) = cv2.threshold(gray, bw_threshold, 255, cv2.THRESH_BINARY) #cv2.imshow('black_and_white', black_and_white) # detect face faces = face_cascade.detectMultiScale(gray, 1.1, 4) # Face prediction for black and white faces_bw = face_cascade.detectMultiScale(black_and_white, 1.1, 4) if(len(faces) == 0 and len(faces_bw) == 0): cv2.putText(img, "No face found...", org, font, font_scale, weared_mask_font_color, thickness, cv2.LINE_AA) else: # Draw rectangle on gace for (x, y, w, h) in faces: roi_gray = gray[y:y + h, x:x + w] roi_color = img[y:y + h, x:x + w] mouth_rects = mouth_cascade.detectMultiScale(roi_gray, 1.5, 5) if(len(mouth_rects) == 0): cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2) else: cv2.rectangle(img, (x, y), (x + w, y + h), (0,0 , 255), 2) # Show frame with results cv2.imshow('Mask Detection', img) k = cv2.waitKey(30) & 0xff if k == 27: break # Release video cap.release() cv2.destroyAllWindows()
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