face_recognition.py

from tkinter import*
from tkinter import ttk
from PIL import Image,ImageTk #pip install pillow
from tkinter import messagebox
import mysql.connector
from time import strftime
from datetime import datetime
import cv2
import os
import numpy as np

class Face_Recognition:
    def __init__(self,root):
        self.root=root
        self.root.geometry("1350x700+0+0")
        self.root.title("Face Attendance System")
        
        
        title_lbl=Label(self.root,text="FACE RECOGNITION", font=("times new roman",35,"bold"),bg="white",fg="Blue") #putting img above bg img
        title_lbl.place(x=0,y=0,width=1350,height=40)
        
        
        img3=Image.open(r"college_images\facial_recognition_system_identification_digital_id_security_scanning_thinkstock_858236252_3x3-100740902-large.jpg")
        img3=img3.resize((950,700),Image.ANTIALIAS)
        self.photoimg3=ImageTk.PhotoImage(img3)

        bg_img=Label(self.root,image=self.photoimg3)
        bg_img.place(x=650,y=40,width=950,height=650)
        
        #button
        b1_1=Button(bg_img,text="FACE RECOGNITION",cursor="hand2",command=self.face_recog,font=("times new roman",15,"bold"),bg="red",fg="white")
        b1_1.place(x=360,y=590,width=250,height=40)
        
    # =========================== Attendance ==========================
    def mark_attendance(self,i,r,n,d):
        with open("Prashant.csv","r+",newline="\n") as f:
            myDataList=f.readlines()
            name_list=[]
            for line in myDataList:
                entry=line.split((","))
                name_list.append(entry[0])
            if((i not in name_list) and (r not in name_list) and (n not in name_list) and (d not in name_list)):
                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")
        
    #=====face recognition=====
    def face_recog(self):
        def draw_boundary(img,classifier,scaleFactor,minNeighbors,color,text,clf):
            gray_image=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
            features=classifier.detectMultiScale(gray_image,scaleFactor,minNeighbors)
            
            
            coord=[]

            for (x,y,w,h) in features:
                cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),3)
                id,predict=clf.predict(gray_image[y:y+h,x:x+w])
                confidence=int((100*(1-predict/300)))
                
                conn=mysql.connector.connect(host="localhost",username="root",password="root",database="student_attendance_system")
                my_cursor=conn.cursor()
                
                my_cursor.execute("Select Name from student where Student_id="+str(id))
                n=my_cursor.fetchone()
                n="+".join(n)
                
                my_cursor.execute("Select Roll from student where Student_id="+str(id))
                r=my_cursor.fetchone()
                r="+".join(r)

                my_cursor.execute("Select Dep from student where Student_id="+str(id))
                d=my_cursor.fetchone()
                d="+".join(d)
                
                my_cursor.execute("Select Student_id from student where Student_id="+str(id))
                i=my_cursor.fetchone()
                i="+".join(i)
         
                if confidence>77:
                    cv2.putText(img,f"ID:{i}",(x,y-75),cv2.FONT_HERSHEY_COMPLEX,0.8,(255,255,255),3)
                    cv2.putText(img,f"Roll:{r}",(x,y-55),cv2.FONT_HERSHEY_COMPLEX,0.8,(255,255,255),3)
                    cv2.putText(img,f"Name:{n}",(x,y-30),cv2.FONT_HERSHEY_COMPLEX,0.8,(255,255,255),3)
                    cv2.putText(img,f"Department:{d}",(x,y-5),cv2.FONT_HERSHEY_COMPLEX,0.8,(255,255,255),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-55),cv2.FONT_HERSHEY_COMPLEX,0.8,(255,255,255),3)

                coord=[x,y,w,h]

            return coord
    
        def recognize(img,clf,faceCascade):
            coord=draw_boundary(img,faceCascade,1.1,10,(255,25,255),"Face",clf)
            return img

        faceCascade=cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
        clf=cv2.face.LBPHFaceRecognizer_create()
        clf.read("classifier.xml")
        
        video_cap=cv2.VideoCapture(0)

        while True:
            ret,img=video_cap.read()
            img=recognize(img,clf,faceCascade)
            cv2.imshow("Welcome to Face Recognition",img)

            if cv2.waitKey(1)==13:
                break
        video_cap.release()
        cv2.destroyAllWindows()
            


if __name__=="__main__":
    root=Tk()
    obj=Face_Recognition(root)
    root.mainloop()