-
Notifications
You must be signed in to change notification settings - Fork 2
/
face_recognise.py
51 lines (35 loc) · 1.14 KB
/
face_recognise.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
import cv2
from classification_model import knn
mapping = {
0: "Siddharth",
1: "Thor"
}
vc = cv2.VideoCapture(0)
face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_alt.xml")
while True:
rval,frame = vc.read()
frame = cv2.flip(frame, 1)
faces = face_cascade.detectMultiScale(frame,1.3,5)
if(len(faces)==0):
continue
for face in faces:
x,y,w,h = face
#Get the face ROI
offset = 10
face_section = frame[y-offset:y+h+offset,x-offset:x+w+offset]
face_section = cv2.resize(face_section,(100,100))
face_section = face_section.reshape(1,-1)
print(face_section.shape)
#Predicted Label (out)
out = knn.predict(face_section)
print(out)
#Display on the screen the name and rectangle around it
pred_name = mapping[int(out)]
cv2.putText(frame,pred_name,(x,y-10),cv2.FONT_HERSHEY_SIMPLEX,1,(255,0,0),2,cv2.LINE_AA)
cv2.rectangle(frame,(x,y),(x+w,y+h),(0,255,255),2)
cv2.imshow("Faces",frame)
key = cv2.waitKey(1)
if key==ord('q'):
break
vc.release()
cv2.destroyAllWindows()