-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathmain.py
210 lines (185 loc) · 7.4 KB
/
main.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
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
import os
import pickle
import numpy as np
import cv2
import face_recognition
import cvzone
import firebase_admin
from firebase_admin import credentials, db, storage
from datetime import datetime
cred = credentials.Certificate("serviceAccountKey.json")
firebase_admin.initialize_app(
cred,
{
"databaseURL": "https://noproxy-a9ae8-default-rtdb.asia-southeast1.firebasedatabase.app/",
"storageBucket": "noproxy-a9ae8.appspot.com",
},
)
bucket = storage.bucket()
cap = cv2.VideoCapture(0)
cap.set(3, 640)
cap.set(4, 480)
bg = cv2.imread("Resources/bg.png")
# importing mode images
folderModePath = "Resources/Modes"
modePathList = os.listdir(folderModePath)
imgModeList = []
for path in modePathList:
imgModeList.append(cv2.imread(os.path.join(folderModePath, path)))
print("Loading Encode File ...")
file = open("EncodeFile.p", "rb")
encodeListKnownWithIds = pickle.load(file)
file.close()
encodeListKnown, studentIds = encodeListKnownWithIds
print("Encode file loaded")
modeType = 0
counter = 0
id = -1
imgStudent = []
while True:
success, img = cap.read()
if img is not None:
imgS = cv2.resize(img, (0, 0), None, 0.25, 0.25)
imgS = cv2.cvtColor(imgS, cv2.COLOR_BGR2RGB)
else:
print("error: img not loaded")
faceFrame = face_recognition.face_locations(imgS)
encodeCurFrame = face_recognition.face_encodings(imgS, faceFrame)
# resized_img = cv2.resize(img, (585, 318))
# img[162:162 + 480, 55:55 + 640] = img[162:162 + 480, 55:55 + 640]
bg[162 : 162 + 480, 55 : 55 + 640] = img
bg[44 : 44 + 633, 808 : 808 + 414] = imgModeList[modeType]
if faceFrame:
for encodeFace, faceLoc in zip(encodeCurFrame, faceFrame):
matches = face_recognition.compare_faces(encodeListKnown, encodeFace)
faceDis = face_recognition.face_distance(encodeListKnown, encodeFace)
matchIndex = np.argmin(faceDis)
if matches[matchIndex]:
y1, x2, y2, x1 = faceLoc
y1, x2, y2, x1 = y1 * 4, x2 * 4, y2 * 4, x1 * 4
bbox = 55 + x1, 162 + y1, x2 - x1, y2 - y1
bg = cvzone.cornerRect(bg, bbox, rt=0)
id = studentIds[matchIndex]
if counter == 0:
cvzone.putTextRect(bg, "Loading", (275, 400))
cv2.imshow("Student Attendance", bg)
cv2.waitKey(1)
counter = 1
modeType = 1
if counter != 0:
if counter == 1:
studentInfo = db.reference(f"Students/{id}").get()
print(studentInfo)
blob = bucket.get_blob(f"Images/{id}.jpg") or bucket.get_blob(
f"Images/{id}.jpeg"
)
if blob:
print(f"Found image: {blob.name}")
array = np.frombuffer(blob.download_as_string(), np.uint8)
imgStudent = cv2.imdecode(array, cv2.COLOR_BGRA2BGR)
else:
print("img not found")
imgStudent = None
datetimeObject = datetime.strptime(
studentInfo["last_attendance_time"], "%Y-%m-%d %H:%M:%S"
)
timeDiff = datetime.now() - datetimeObject
if timeDiff.total_seconds() > 86400: # 24 hours in seconds
ref = db.reference(f"Students/{id}")
studentInfo["total_attendance"] += 1
ref.child("total_attendance").set(
studentInfo["total_attendance"]
)
ref.child("last_attendance_time").set(
datetime.now().strftime("%Y-%m-%d %H:%M:%S")
)
else:
modeType = 3
counter = 0
bg[44 : 44 + 633, 808 : 808 + 414] = imgModeList[modeType]
if counter != 0 and modeType != 3:
if 10 < counter < 20:
modeType = 2
bg[44 : 44 + 633, 808 : 808 + 414] = imgModeList[modeType]
if counter <= 10:
cv2.putText(
bg,
str(studentInfo["total_attendance"]),
(861, 125),
cv2.FONT_HERSHEY_COMPLEX,
1,
(255, 255, 255),
1,
)
cv2.putText(
bg,
str(studentInfo["course"]),
(1006, 550),
cv2.FONT_HERSHEY_COMPLEX,
0.5,
(255, 255, 255),
1,
)
cv2.putText(
bg,
str(id),
(1006, 493),
cv2.FONT_HERSHEY_COMPLEX,
0.5,
(255, 255, 255),
1,
)
cv2.putText(
bg,
str(studentInfo["standing"]),
(910, 625),
cv2.FONT_HERSHEY_COMPLEX,
0.6,
(100, 100, 100),
1,
)
cv2.putText(
bg,
str(studentInfo["year"]),
(1025, 625),
cv2.FONT_HERSHEY_COMPLEX,
0.6,
(100, 100, 100),
1,
)
cv2.putText(
bg,
str(studentInfo["starting_year"]),
(1125, 625),
cv2.FONT_HERSHEY_COMPLEX,
0.6,
(100, 100, 100),
1,
)
(w, h), _ = cv2.getTextSize(
studentInfo["name"], cv2.FONT_HERSHEY_COMPLEX, 1, 1
)
offset = (414 - w) // 2
cv2.putText(
bg,
str(studentInfo["name"]),
(808 + offset, 445),
cv2.FONT_HERSHEY_COMPLEX,
1,
(50, 50, 50),
1,
)
if imgStudent is not None:
bg[175 : 175 + 216, 909 : 909 + 216] = imgStudent
counter += 1
if counter >= 20:
counter = 0
modeType = 0
studentInfo = []
imgStudent = []
bg[44 : 44 + 633, 808 : 808 + 414] = imgModeList[modeType]
else:
modeType = 0
counter = 0
cv2.imshow("Student Attendance", bg)
cv2.waitKey(1)