main.py

"""MaskDetectionScript.ipynb

Automatically generated by Colaboratory.

Original file is located at
    https://colab.research.google.com/drive/1E46tSToZWnOlESxou1PgRzTuy9XmqQYg
"""

import cv2
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.image import load_img, img_to_array
import numpy as np

model = load_model('saved_model.h5')

img_width , img_height = 150,150

face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

cap = cv2.VideoCapture('video.mp4')
# cap = cv2.VideoCapture(0) # for using system camera
img_count_full = 0

font = cv2.FONT_HERSHEY_SIMPLEX
org = (1,1)
class_label = ''
fontScale = 1
color = (255,0,0)
thickness = 2

while True:
  img_count_full += 1
  response , color_img = cap.read()

  if response == False:
    break
  
  scale = 50
  width = int(color_img.shape[1]*scale/100)
  height = int(color_img.shape[0]*scale/100)
  dim = (width,height)

  color_img = cv2.resize(color_img,dim,interpolation = cv2.INTER_AREA)

  gray_img = cv2.cvtColor(color_img,cv2.COLOR_BGR2GRAY)

  faces = face_cascade.detectMultiScale(gray_img,1.1,6)

  img_count = 0
  for (x,y,w,h) in faces:
    org = (x-10,y-10)
    img_count += 1
    color_face = color_img[y:y+h,x:x+w]
    cv2.imwrite('input/%face%d.png'%(img_count_full,img_count),color_face)
    img = load_img('input/%face%d.png'%(img_count_full,img_count),target_size = (img_width,img_height))
    img = img_to_array(img)
    img = np.expand_dims(img,axis = 0)
    prediction = model.predict(img, verbose=0)

    if prediction == 0:
      class_label = "Mask"
      color = (0,255,0)
    else:
      class_label = "No Mask"
      color = (0,0,255)
    
    cv2.rectangle(color_img,(x,y),(x+w,y+h),(255,0,0),3)
    cv2.putText(color_img, class_label, org, font, fontScale, color, thickness, cv2.LINE_AA)
  cv2.imshow("Face mask detection",color_img)
  if cv2.waitKey(1) & 0xFF == ord('q'):
    break

cap.release()
cv2.destroyAllWindows()