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Face_recognition.py
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Face_recognition.py
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from cProfile import label
from tkinter import *
from tkinter import ttk
from PIL import Image, ImageTk
from tkinter import messagebox, filedialog
import mysql.connector
import cv2
from datetime import datetime
from time import strftime
import os
# import numpy as np
class Face_Recognition:
def __init__(self, root):
self.root = root
self.root.geometry("1590x790+0+0")
self.root.title("Face Recognition System")
# ==============================Labe; from traindata========================================
title_lbl = Label(self.root, text="FACE RECOGNITION", font=(
"times new roman", 35, "bold"), bg="white", fg="black")
title_lbl.place(x=0, y=0, width=1590, height=45)
img_top = Image.open(r"img\Fc.jpg")
img_top = img_top.resize((650, 800), Image.ANTIALIAS)
self.photoimg_top = ImageTk.PhotoImage(img_top)
f_lbl = Label(self.root, image=self.photoimg_top)
f_lbl.place(x=0, y=55, width=650, height=800)
img_bottom = Image.open(r"face.jpg")
img_bottom = img_bottom.resize((950, 800), Image.ANTIALIAS)
self.photoimg_bottom = ImageTk.PhotoImage(img_bottom)
f_lbl = Label(self.root, image=self.photoimg_bottom)
f_lbl.place(x=650, y=55, width=950, height=800)
# ==========button===========================
b1_1 = Button(f_lbl, text="Face Recognition", cursor="hand2", font=(
"times new roman", 18, "bold"), bg="blue", fg="white", command=self.face_recog)
b1_1.place(x=365, y=620, width=200, height=40)
def face_recog(self):
def draw_boundry(img, classifier, scalefactor, minNeighbours, color, text, clf):
grey_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
feature = classifier.detectMultiScale(
grey_img, scalefactor, minNeighbours)
coords = []
for (x, y, w, h) in feature:
cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 3)
id, predict = clf.predict(grey_img[y:y+h, x:x+w])
confidence = int((100*(1-predict/300)))
conn = mysql.connector.connect(
host='localhost', user='root', password='rootpassword', port="3310", database='new')
my_cursor = conn.cursor()
my_cursor.execute(
"select student_name from attandance_management_system where student_id="+str(id))
n = my_cursor.fetchone()
n = "+".join(n)
my_cursor.execute(
"select Department from attandance_management_system where student_id="+str(id))
d = my_cursor.fetchone()
d = "+".join(d)
my_cursor.execute(
"select Roll_No from attandance_management_system where student_id="+str(id))
r = my_cursor.fetchone()
r = "+".join(r)
my_cursor.execute(
"select student_id from attandance_management_system where student_id="+str(id))
i = my_cursor.fetchone()
i = "+".join(i)
if confidence > 77:
cv2.putText(
img, f"Id:{i}", (x, y-85), cv2.FONT_HERSHEY_COMPLEX, 0.8, (255, 255, 0), 3)
cv2.putText(
img, f"Roll:{r}", (x, y-55), cv2.FONT_HERSHEY_COMPLEX, 0.8, (255, 255, 0), 3)
cv2.putText(
img, f"Name:{n}", (x, y-30), cv2.FONT_HERSHEY_COMPLEX, 0.8, (255, 255, 0), 3)
cv2.putText(
img, f"Department:{d}", (x, y-5), cv2.FONT_HERSHEY_COMPLEX, 0.8, (255, 255, 0), 3)
self.mark_attendance(i,r,n,d)
else:
cv2.rectangle(img, (x, y), (x+w, y+h), (0, 0, 255), 3)
cv2.putText(img, "Unknown Face", (x, y-5),
cv2.FONT_HERSHEY_COMPLEX, 0.8, (0, 0, 255), 3)
coords = [x, y, w, y]
return coords
def recognizer(img, clf, faceCascade):
coords = draw_boundry(img, faceCascade, 1.1,
10, (255, 255, 255), "Face", clf)
return img
faceCascade = cv2.CascadeClassifier("face_recog.xml")
clf = cv2.face.LBPHFaceRecognizer_create()
clf.read("classifier.xml")
video_cap = cv2.VideoCapture(0)
while True:
ret, img = video_cap.read()
img1 = recognizer(img, clf, faceCascade)
cv2.imshow("Welcome to face recognition", img1)
if cv2.waitKey(1) == 13:
break
video_cap.release()
cv2.destroyAllWindows()
# def mark_attendance(self,i,r,n,d):
# already_in_file = set()
# with open('atten.csv','r+',newline="\n") as f:
# for line in f:
# already_in_file.add(line.split(",")[0])
# if((i not in already_in_file) and (r not in already_in_file) and (n not in already_in_file) and (d not in already_in_file)):
# with open('atten.csv','r+',newline="\n") as f:
# now=datetime.now()
# d1=now.strftime("%d/%m/%Y")
# dtString=now.strftime("%H:%M:%S")
# f.writelines(f"\n{i},{r},{n},{d},{dtString},{d1},present")
def mark_attendance(self,i,r,n,d):
already_in_file = set()
with open('atten.csv','r+',newline="\n") as f:
for line in f:
already_in_file.add(line.split(",")[0])
if((i not in already_in_file) and (r not in already_in_file) and (n not in already_in_file) and (d not in already_in_file)):
now=datetime.now()
d1=now.strftime("%d/%m/%Y")
dtString=now.strftime("%H:%M:%S")
f.writelines(f"\n{i},{r},{n},{d},{dtString},{d1},present")
if __name__ == "__main__":
root = Tk()
obj = Face_Recognition(root)
root.mainloop()