forked from shantamsultania/OpenCV_Tutorials_bacis
-
Notifications
You must be signed in to change notification settings - Fork 0
/
facelock2.py
66 lines (53 loc) · 2.18 KB
/
facelock2.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
import cv2
import numpy as np
from os import listdir
from os.path import isfile, join
face0 =cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
data_path = './datacollection/'
onlyfiles = [f for f in listdir(data_path) if isfile(join(data_path,f))]
Training_Data, Labels = [], []
for i, files in enumerate(onlyfiles):
image_path = data_path + onlyfiles[i]
images = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
Training_Data.append(np.asarray(images, dtype=np.uint8))
Labels.append(i)
Labels = np.asarray(Labels, dtype=np.int32)
model = cv2.face.LBPHFaceRecognizer_create()
model.train(np.asarray(Training_Data), np.asarray(Labels))
print("Model Training.......")
def face_detector(img, size = 0.5):
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face0.detectMultiScale(gray,1.5,5)
if faces is():
return img,[]
for(x,y,w,h) in faces:
cv2.rectangle(img, (x,y),(x+w,y+h),(0,255,255),2)
roi = img[y:y+h, x:x+w]
roi = cv2.resize(roi, (200,200))
return img,roi
cap = cv2.VideoCapture(0)
while True:
ret, frame = cap.read()
image, face = face_detector(frame)
try:
face = cv2.cvtColor(face, cv2.COLOR_BGR2GRAY)
result = model.predict(face)
if result[1] < 500:
confidence = int(100*(1-(result[1])/300))
display_string = str(confidence)+'% Confidence it is user'
cv2.putText(image,display_string,(100,120), cv2.FONT_HERSHEY_COMPLEX,1,(250,120,255),2)
if confidence > 75:
cv2.putText(image, "Unlocked", (250, 450), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 255, 0), 2)
cv2.imshow('Face Cropper', image)
else:
cv2.putText(image, "Locked", (250, 450), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 0, 255), 2)
# display_string = str(confidence) + '% Confidence it is not user'
cv2.imshow('Face Cropper', image)
except:
cv2.putText(image, "Face Not Found", (250, 450), cv2.FONT_HERSHEY_COMPLEX, 1, (255, 0, 0), 2)
cv2.imshow('Face Cropper', image)
pass
if cv2.waitKey(1) == 27:
break
cap.release()
cv2.destroyAllWindows()