mask_detection.py

import tensorflow.keras
from PIL import Image, ImageOps
import numpy as np
import cv2

# import os

str = ""
faceCascade = cv2.CascadeClassifier("Resources/haarcascade_frontalface_default.xml")

np.set_printoptions(suppress=True)
model = tensorflow.keras.models.load_model("Resources/keras_model.h5")
data = np.ndarray(shape=(1, 224, 224, 3), dtype=np.float32)


cap = cv2.VideoCapture(0)
cap.set(3, 640)
cap.set(4, 480)
while True:
    success, img = cap.read()

    cv2.imshow("webcam", img)
    faces = faceCascade.detectMultiScale(img, 1.1, 4)

    for (x, y, w, h) in faces:
        crop_img = img[y : y + h, x : x + w]
        crop_img = cv2.resize(crop_img, (224, 224))
        normalized_image_array = (crop_img.astype(np.float32) / 127.0) - 1
        data[0] = normalized_image_array
        prediction = model.predict(data)
        print(prediction)
        if prediction[0][0] > prediction[0][1]:
            str = "Mask"
        else:
            str = "Without-mask"

        cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
        cv2.putText(img, str, (x, y), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 150, 0), 1)
        cv2.imshow("Result", img)

    if cv2.waitKey(1) & 0xFF == ord("q"):
        break