-
Notifications
You must be signed in to change notification settings - Fork 3
/
mask_detection.py
75 lines (53 loc) · 2.63 KB
/
mask_detection.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
import cvlib as cv
import cv2
import numpy as np
from tensorflow.keras.models import load_model
from tensorflow.keras.applications.resnet50 import preprocess_input
from tensorflow.keras.preprocessing.image import img_to_array
from PIL import ImageFont, ImageDraw, Image
model = load_model('pythonProject/trainer/VGG19-Face Mask Detection.h5')
model.summary()
# open webcam
webcam = cv2.VideoCapture(0)
if not webcam.isOpened():
print("Could not open webcam")
exit()
# loop through frames
while webcam.isOpened():
# read frame from webcam
status, frame = webcam.read()
if not status:
print("Could not read frame")
exit()
# apply face detection
face, confidence = cv.detect_face(frame)
# loop through detected faces
for idx, f in enumerate(face):
(startX, startY) = f[0], f[1]
(endX, endY) = f[2], f[3]
if 0 <= startX <= frame.shape[1] and 0 <= endX <= frame.shape[1] and 0 <= startY <= frame.shape[0] and 0 <= endY <= frame.shape[0]:
face_region = frame[startY:endY, startX:endX]
face_region1 = cv2.resize(face_region, (128, 128), interpolation = cv2.INTER_AREA) #shape size(128,128) 바꿀려면 모델 제작시 바꿔야함
x = img_to_array(face_region1)
x = np.expand_dims(x, axis=0)
x = preprocess_input(x)
prediction = model.predict(x)
print(prediction)
if prediction[0][0].round() == 0: # 마스크 미착용으로 판별되면,
cv2.rectangle(frame, (startX,startY), (endX,endY), (0,0,255), 2)
Y = startY - 10 if startY - 10 > 10 else startY + 10
text = "No Mask ({:.2f}%)".format((1 - prediction[0][0])*100)
cv2.putText(frame, text, (startX,Y), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0,0,255), 2)
elif prediction[0][0].round() == 1: # 마스크 착용으로 판별되면
cv2.rectangle(frame, (startX,startY), (endX,endY), (0,255,0), 2)
Y = startY - 10 if startY - 10 > 10 else startY + 10
text = "Mask ({:.2f}%)".format(prediction[0][0]*100)
cv2.putText(frame, text, (startX,Y), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0,255,0), 2)
# display output(웹캠으로 마스크 유무 식별)
cv2.imshow("mask nomask classify", frame)
# press "Q" to stop
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# release resources
webcam.release()
cv2.destroyAllWindows()