import cv2
from playsound import playsound
import numpy as np
import os
import time,sys
import sqlite3
from openpyxl import Workbook, load_workbook
from openpyxl.utils import get_column_letter, cell,column_index_from_string
recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read('C:/Users/ACER/Desktop/Project series/Face recognition/trainer/trainer.yml')
faceCascade = cv2.CascadeClassifier("C:/Users/ACER/Desktop/Python/Face recognition/HaarCascade/haarcascade_frontalface_default.xml")
connect = sqlite3.connect('C:/Users/ACER/Desktop/Project series/Face recognition/sqlite3/Studentdb.db')
font = cv2.FONT_HERSHEY_SIMPLEX
#iniciate id counter
id= 0
#Get the currentdate
currentDate = time.strftime("%d_%m_%y")
#get the excel file
print( "Subjects are 'BI','SIC','PGIS','SQA','ITSM")
subject=input("Enter Subject:")
a=['BI','SIC','PGIS','SQA','ITSM']
sc=subject+currentDate
if subject in a:
print("Success")
wbook = load_workbook(filename = "C:/Users/ACER/Desktop/Project series/Face recognition/Attendance/"+subject+".xlsx")
sheet = wbook.get_sheet_by_name('TYBSCIT'+subject)
else:
print("Invalid")
# names related to Ids: example ==> Vignesh: id=101, etc
names=[]
cursor = connect.execute("SELECT FULLNAME from Student")
rows=cursor.fetchall()
names=list(rows)
# Initialize and start realtime video capture
cam = cv2.VideoCapture(0)
cam.set(3, 640) # set video widht
cam.set(4, 480) # set video height
def getDateColumns():
for i in range(1, len(sheet.rows[0]) + 1):
cols = get_column_letter(i)
if sheet.cell('%s%s'% (col,'1')).value == currentDate:
return cols
# Define min window size to be recognized as a face
minW = 0.1*cam.get(3)
minH = 0.1*cam.get(4)
while True:
ret, img =cam.read()
img = cv2.flip(img,1) # Flip vertically
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(
gray,
scaleFactor = 1.2,
minNeighbors = 5,
minSize = (int(minW), int(minH)),
)
for(x,y,w,h) in faces:
cv2.rectangle(img, (x,y), (x+w,y+h), (0,255,0), 2)
id, confidence = recognizer.predict(gray[y:y+h,x:x+w])
# Check if confidence is less then 100 ==> "0" is perfect match
if (confidence < 100):
id = names[id]
confidence = " {0}%".format(round(100 - confidence))
playsound("images recognized.mp3")
else:
ids = "Unknown"
confidence = " {0}%".format(round(100 - confidence))
cv2.putText(img, str(id), (x+5,y-5), font, 1, (255,255,255), 2)
cv2.putText(img, str(confidence), (x+5,y+h-5), font, 1, (255,255,0), 1)
cv2.imshow('camera',img)
k = cv2.waitKey(10) & 0xff # Press 'ESC' for exiting video
if k == 27:
break
for row in range(2, (list(sheet.columns[0]) + 1)):
rowno = sheet.cell('A%s'% row).value
if rowno is not None:
rowno = rowno[-2:]
if attend[int(rowno)] != 0:
col = getDateColumns()
sheet['%s%s' % (col, str(row))]=1
wbook.save(filename="C:/Users/ACER/Desktop/Project series/Face recognition/Attendance/"+subject+currentDate+".xlsx")
# Do a bit of cleanup
print("\n [INFO] Exiting Program and cleanup stuff")
cam.release()
cv2.destroyAllWindows()
error:
Traceback (most recent call last):
File "C:\Users\ACER\Desktop\Project series\Face recognition\recognize.py", line 65, in
id = names[id]
IndexError: list index out of range>>>
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