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main.py
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main.py
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import os
import pickle
import numpy as np
import cv2
import face_recognition
import cvzone
import firebase_admin
from dotenv import load_dotenv
from firebase_admin import credentials
from firebase_admin import db
from firebase_admin import storage
import numpy as np
import pandas as pd
from datetime import datetime, date
import time
load_dotenv()
cred = credentials.Certificate("serviceAccountKey.json")
firebase_admin.initialize_app(cred, {
'databaseURL': os.getenv('FIREBASE_DATABASE_URL'),
'storageBucket': os.getenv('FIREBASE_STORAGE_BUCKET')
})
bucket = storage.bucket()
cap = cv2.VideoCapture(0)
cap.set(3, 640)
cap.set(4, 480)
imgBackground = cv2.imread('Resources/background.png')
# Importing the mode images into a list
folderModePath = 'Resources/Modes'
modePathList = os.listdir(folderModePath)
imgModeList = []
for path in modePathList:
imgModeList.append(cv2.imread(os.path.join(folderModePath, path)))
# print(len(imgModeList))
# Load the encoding file
print("Loading Encode File ...")
file = open('EncodeFile.p', 'rb')
encodeListKnownWithIds = pickle.load(file)
file.close()
encodeListKnown, studentIds = encodeListKnownWithIds
# print(studentIds)
print("Encode File Loaded")
modeType = 0
counter = 0
id = -1
imgStudent = []
while True:
success, img = cap.read()
imgS = cv2.resize(img, (0, 0), None, 0.25, 0.25)
imgS = cv2.cvtColor(imgS, cv2.COLOR_BGR2RGB)
faceCurFrame = face_recognition.face_locations(imgS)
encodeCurFrame = face_recognition.face_encodings(imgS, faceCurFrame)
imgBackground[162:162 + 480, 55:55 + 640] = img
imgBackground[44:44 + 633, 808:808 + 414] = imgModeList[modeType]
if faceCurFrame:
for encodeFace, faceLoc in zip(encodeCurFrame, faceCurFrame):
matches = face_recognition.compare_faces(encodeListKnown, encodeFace)
faceDis = face_recognition.face_distance(encodeListKnown, encodeFace)
# print("matches", matches)
# print("faceDis", faceDis)
matchIndex = np.argmin(faceDis)
# print("Match Index", matchIndex)
if matches[matchIndex]:
# print("Known Face Detected")
# print(studentIds[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
imgBackground = cvzone.cornerRect(imgBackground, bbox, rt=0)
id = studentIds[matchIndex]
if counter == 0:
cvzone.putTextRect(imgBackground, "Loading", (275, 400))
cv2.imshow("Face Attendance", imgBackground)
cv2.waitKey(1)
counter = 1
modeType = 1
if counter != 0:
if counter == 1:
# Get the Data
studentInfo = db.reference(f'Students/{id}').get()
print(studentInfo)
# Get the Image from the storage
blob = bucket.get_blob(f'Images/{id}.png')
array = np.frombuffer(blob.download_as_string(), np.uint8)
imgStudent = cv2.imdecode(array, cv2.COLOR_BGRA2BGR)
datetimeObject = datetime.strptime(studentInfo['last_attendance_time'],"%Y-%m-%d %H:%M:%S")
secondsElapsed = (datetime.now() - datetimeObject).total_seconds()
print(secondsElapsed)
if secondsElapsed > 15:
ref = db.reference(f'Students/{id}')
studentInfo['total_attendance'] += 1
branch = ref.child('major').get()
ref.child('total_attendance').set(studentInfo['total_attendance'])
ref.child('last_attendance_time').set(datetime.now().strftime("%Y-%m-%d %H:%M:%S"))
# Mark Attendace in Excel Sheet
current_date = date.today().strftime("%d-%m-%Y")
csv_file_path = f'school_attendance_database/{branch}.csv'
try:
df = pd.read_csv(csv_file_path, index_col=False)
df = df.loc[:, ~df.columns.str.contains('^Unnamed')]
except FileNotFoundError:
df = pd.DataFrame(columns=['Roll No.', 'Name'])
df['Roll No.'] = df['Roll No.'].astype(str)
if current_date not in df.columns:
df[current_date] = np.nan
df[current_date] = df[current_date].astype(object)
df[current_date] = df[current_date].astype(object)
df.loc[df['Roll No.'] == str(id), current_date] = 'P'
df = df.sort_values(by = "Roll No.", ascending = True)
for column in df.columns:
if column != 'Roll No.' and column != 'Name' and column != current_date:
df[column] = df[column].fillna('A')
df.to_csv(csv_file_path, index=False)
else:
modeType = 3
counter = 0
imgBackground[44:44 + 633, 808:808 + 414] = imgModeList[modeType]
if modeType != 3:
if 20 < counter < 30:
modeType = 2
imgBackground[44:44 + 633, 808:808 + 414] = imgModeList[modeType]
if counter <= 20:
cv2.putText(imgBackground, str(studentInfo['total_attendance']), (861, 125),
cv2.FONT_HERSHEY_COMPLEX, 1, (255, 255, 255), 1)
cv2.putText(imgBackground, str(studentInfo['major']), (1006, 550),
cv2.FONT_HERSHEY_COMPLEX, 0.5, (255, 255, 255), 1)
cv2.putText(imgBackground, str(id), (1006, 493),
cv2.FONT_HERSHEY_COMPLEX, 0.5, (255, 255, 255), 1)
cv2.putText(imgBackground, str(studentInfo['standing']), (910, 625),
cv2.FONT_HERSHEY_COMPLEX, 0.6, (100, 100, 100), 1)
cv2.putText(imgBackground, str(studentInfo['year']), (1025, 625),
cv2.FONT_HERSHEY_COMPLEX, 0.6, (100, 100, 100), 1)
cv2.putText(imgBackground, 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(imgBackground, str(studentInfo['name']), (808 + offset, 445),
cv2.FONT_HERSHEY_COMPLEX, 1, (50, 50, 50), 1)
imgBackground[175:175 + 216, 909:909 + 216] = imgStudent
counter += 1
if counter >= 30:
counter = 0
modeType = 0
studentInfo = []
imgStudent = []
imgBackground[44:44 + 633, 808:808 + 414] = imgModeList[modeType]
else:
modeType = 0
counter = 0
# cv2.imshow("Webcam", img)
cv2.imshow("Face Attendance", imgBackground)
cv2.waitKey(1)