face_recognition.py

from tkinter import*
from PIL import Image,ImageTk
import mysql.connector
import cv2
from datetime import datetime, timedelta
from time import strftime
class Face_Recognition:

    def __init__(self,root):
        self.root=root
        self.root.geometry("1366x768+0+0")
        self.root.title("Face Recognition Pannel")
        
        self.last_attendance_time = None

        # This part is image labels setting start 
        # first header image  
        img=Image.open("Images_GUI/banner.jpg")
        img=img.resize((1366,130),Image.Resampling.LANCZOS)
        self.photoimg=ImageTk.PhotoImage(img)

        # set image as lable
        f_lb1 = Label(self.root,image=self.photoimg)
        f_lb1.place(x=0,y=0,width=1366,height=130)

        # backgorund image 
        bg1=Image.open(r"Images_GUI\bg2.jpg")
        bg1=bg1.resize((1366,768),Image.Resampling.LANCZOS)
        self.photobg1=ImageTk.PhotoImage(bg1)

        # set image as lable
        bg_img = Label(self.root,image=self.photobg1)
        bg_img.place(x=0,y=130,width=1366,height=768)


        #title section
        title_lb1 = Label(bg_img,text="Welcome to Face Recognition Pannel",font=("verdana",30,"bold"),bg="white",fg="navyblue")
        title_lb1.place(x=0,y=0,width=1366,height=45)

        # Create buttons below the section 
        # ------------------------------------------------------------------------------------------------------------------- 
        std_img_btn=Image.open(r"Images_GUI\f_det.jpg")
        std_img_btn=std_img_btn.resize((180,180),Image.Resampling.LANCZOS)
        self.std_img1=ImageTk.PhotoImage(std_img_btn)

        std_b1 = Button(bg_img,command=self.face_recog,image=self.std_img1,cursor="hand2")
        std_b1.place(x=600,y=170,width=180,height=180)

        std_b1_1 = Button(bg_img,command=self.face_recog,text="Face Detector",cursor="hand2",font=("tahoma",15,"bold"),bg="white",fg="navyblue")
        std_b1_1.place(x=600,y=350,width=180,height=45)
    #=====================Attendance===================

    def mark_attendance(self,s,i,d):
        with open("test1.csv","r+",newline="\n") as f:
            myDatalist=f.readlines()
            name_list=[]
            for line in myDatalist:
                entry=line.split((","))
                name_list.append(entry[0])

            if((s not in name_list)) and ((i 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")
                if self.last_attendance_time is None or now - self.last_attendance_time >= timedelta(minutes=5):
                    f.writelines(f"\n{s}, {i}, {d}, {dtString}, {d1}, Present")
                    self.last_attendance_time = now


    #================face recognition==================
    def face_recog(self):
        def draw_boundray(img,classifier,scaleFactor,minNeighbors,color,text,clf):
            gray_image=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
            featuers=classifier.detectMultiScale(gray_image,scaleFactor,minNeighbors)

            coord=[]
            
            for (x,y,w,h) in featuers:
                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(user="root",password=" ",host="localhost",database="face_recognizer",port=3306)
                cursor = conn.cursor()

                cursor.execute("select Student_ID from student where Student_ID=" + str(id))
                s = cursor.fetchone()
                s = str(s[0])

                cursor.execute("select Name from student where Student_ID=" + str(id))
                i = cursor.fetchone()
                i = str(i[0])

                cursor.execute("select Department from student where Student_ID=" + str(id))
                d = cursor.fetchone()
                d = str(d[0])


                if confidence > 77:
                    cv2.putText(img,f"Student_ID:{s}",(x,y-80),cv2.FONT_HERSHEY_COMPLEX,0.8,(64,15,223),2)
                    cv2.putText(img,f"Name:{i}",(x,y-55),cv2.FONT_HERSHEY_COMPLEX,0.8,(64,15,223),2)
                    cv2.putText(img,f"Department:{d}",(x,y-30),cv2.FONT_HERSHEY_COMPLEX,0.8,(64,15,223),2)
                    self.mark_attendance(s,i,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,(255,255,0),3)    

                coord=[x,y,w,y]
            
            return coord    


        #==========
        def recognize(img,clf,faceCascade):
            coord=draw_boundray(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")

        videoCap=cv2.VideoCapture(0)

        while True:
            ret,img=videoCap.read()
            img=recognize(img,clf,faceCascade)
            cv2.imshow("Face Detector",img)

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




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