-
Notifications
You must be signed in to change notification settings - Fork 54
/
face_recognizer.py
105 lines (82 loc) · 3.23 KB
/
face_recognizer.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
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
#----------------------------------------------
#--- Author : Ahmet Ozlu
#--- Mail : [email protected]
#--- Date : 21st September 2017
#----------------------------------------------
import face_recognition
import cv2
import os
from utils import create_csv
# The output video
fourcc = cv2.VideoWriter_fourcc(*'XVID')
output_movie = cv2.VideoWriter('tbbt_output.avi', fourcc, 30, (1280, 720))
# Open the input movie file
input_movie = cv2.VideoCapture("tbbt.mp4")
length = int(input_movie.get(cv2.CAP_PROP_FRAME_COUNT))
# Load some sample pictures and learn how to recognize them.
lmm_image = face_recognition.load_image_file("sheldon.jpg")
lmm_face_encoding = face_recognition.face_encodings(lmm_image)[0]
al_image = face_recognition.load_image_file("penny.jpg")
al_face_encoding = face_recognition.face_encodings(al_image)[0]
known_faces = [
lmm_face_encoding,
al_face_encoding
]
# Initialize some variables
face_locations = []
face_encodings = []
face_names = []
frame_number = 0
current_path = os.getcwd()
counter = 0
counter1 = 0
while True:
# Grab a single frame of video
ret, frame = input_movie.read()
frame_number += 1
# Quit when the input video file ends
if not ret:
break
# Find all the faces and face encodings in the current frame of video
face_locations = face_recognition.face_locations(frame)
face_encodings = face_recognition.face_encodings(frame, face_locations)
face_names = []
for face_encoding in face_encodings:
# See if the face is a match for the known face(s)
match = face_recognition.compare_faces(known_faces, face_encoding, tolerance=0.50)
# If you had more than 2 faces, you could make this logic a lot prettier
# but I kept it simple for the demo
name = None
if match[0]:
name = "Sheldon Cooper"
elif match[1]:
name = "Penny"
face_names.append(name)
# Label the results
for (top, right, bottom, left), name in zip(face_locations, face_names):
if not name:
continue
# Draw a box around the face
cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
crop_img = frame[top:bottom, left:right]
if(name == "Sheldon Cooper"):
cv2.imwrite(current_path + "/face_database/Sheldon/" + "sheldon"+str(counter)+".png",crop_img)
counter = counter + 1
elif(name == "Penny"):
cv2.imwrite(current_path + "/face_database/Penny/" + "penny"+str(counter1)+".png",crop_img)
counter1 = counter1 + 1
# Draw a label with a name below the face
cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED)
font = cv2.FONT_HERSHEY_DUPLEX
cv2.putText(frame, name, (left + 6, bottom - 6), font, 1.0, (255, 255, 255), 1)
# Write the resulting image to the output video file
output_movie.write(frame)
print("Writing frame {} / {}".format(frame_number, length))
cv2.imshow('face_recog_crop', frame)
# Hit 'q' on the keyboard to quit!
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# All done!
input_movie.release()
cv2.destroyAllWindows()
create_csv.CreateCsv(current_path + "/face_database/")