asankad7/face-recognition-train-yml-python

face recognition and train .yml file detect specific face using python and opencv

Face-Recognition-Train-YML-Python

In this project you can have face detection using 'haarcascade_frontalface_default.xml' file python code. you can run 'face.py' access faces thurough USB camera.

To do face Recognition part first you have to create 'train.yml' file it's like a 'haarcascade_frontalface_default.xml' file.In that file have specific faces data.After generate 'train.yml' file you can run 'recognizer.py' file, in this file can do recognition part.

face-recognition-train-yml-python's Issues

cv2.error: OpenCV(4.9.0) D:\a\opencv-python\opencv-python\opencv_contrib\modules\face\src\lbph_faces.cpp:406: error: (-5:Bad argument) This LBPH model is not computed yet. Did you call the train method? in function 'cv::face::LBPH::predict

import re

from sys import path
from tkinter import*
from tkinter import ttk
from PIL import Image,ImageTk
import os
import mysql.connector
import cv2
import numpy as np
from tkinter import messagebox
from time import strftime
from datetime import datetime
class Face_Recognition:

def __init__(self,root):
    self.root=root
    self.root.geometry("1366x768+0+0")
    self.root.title("Face Recognition Pannel")

    # This part is image labels setting start 
    # first header image  
    img=Image.open(r"C:\Users\mc882\Videos\Captures\OneDrive\Desktop\Python-FYP-Face-Recognition-Attendence-System-master\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"C:\Users\mc882\Videos\Captures\OneDrive\Desktop\Python-FYP-Face-Recognition-Attendence-System-master\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 
    # ------------------------------------------------------------------------------------------------------------------- 
    # Training button 1
    std_img_btn=Image.open(r"C:\Users\mc882\Videos\Captures\OneDrive\Desktop\Python-FYP-Face-Recognition-Attendence-System-master\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,i,r,n):
    with open("attendance.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)):
            now=datetime.now()
            d1=now.strftime("%d/%m/%Y")
            dtString=now.strftime("%H:%M:%S")
            f.writelines(f"\n{i}, {r}, {n}, {dtString}, {d1}, Present")


#================face recognition==================
def face_recog(self):
    def draw_boundray(img,classifier,scaleFactor,minNeighbors,color,text,clf):
       

        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='Azsxdc!#312',host='127.0.0.1',database='face_recognition',port=3306)
            cursor = conn.cursor()

            cursor.execute("select Name from student where Student_ID="+str(id))
            n=cursor.fetchone()
            n="+".join(n)

            cursor.execute("select Roll_No from student where Student_ID="+str(id))
            r=cursor.fetchone()
            r="+".join(r)

            cursor.execute("select Student_ID from student where Student_ID="+str(id))
            i=cursor.fetchone()
            i="+".join(i)


            if confidence > 77:
                cv2.putText(img,f"Student_ID:{i}",(x,y-80),cv2.FONT_HERSHEY_COMPLEX,0.8,(64,15,223),2)
                cv2.putText(img,f"Name:{n}",(x,y-55),cv2.FONT_HERSHEY_COMPLEX,0.8,(64,15,223),2)
                cv2.putText(img,f"Roll-No:{r}",(x,y-30),cv2.FONT_HERSHEY_COMPLEX,0.8,(64,15,223),2)
                self.mark_attendance(i,r,n)
            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(cv2.data.haarcascades + "haarcascade_frontalface_default.xml")
    clf=cv2.face.LBPHFaceRecognizer_create()
    clf.read(r"C:\Users\mc882\Videos\Captures\OneDrive\Desktop\Python-FYP-Face-Recognition-Attendence-System-master\clf.xml")
    def recognize(img,clf,faceCascade):
        coord=draw_boundray(img,faceCascade,1.1,10,(255,25,255),"Face",clf)
        return img
    videoCap=cv2.VideoCapture(0)

    while True:
        ret,img=videoCap.read()
        gray_image=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
        featuers=faceCascade.detectMultiScale(gray_image,1.3,5)
        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()

C:\ci\opencv_1512688052760\work\opencv_contrib-3.3.1\modules\face\src\lbph_faces.cpp:400: error: (-5) This LBPH model is not computed yet. Did you call the train method? in function cv::face::LBPH::predict

i get an error
Here is my code

import cv2
import numpy as np
faceDetect=cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
cam=cv2.VideoCapture(0);
rec=cv2.face.LBPHFaceRecognizer_create();
rec.read("recognizer/trainningData.yml")
id=0
font = cv2.FONT_HERSHEY_SIMPLEX
while(True):
    ret,img=cam.read();
    gray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    faces=faceDetect.detectMultiScale(gray,1.3,5);
    for(x,y,w,h) in faces:
        cv2.rectangle(img,(x,y),(x+w,y+h),(0,0,255),2)
        id,conf=rec.predict(gray[y:y+h,x:x+w])
        cv2.putText(img,str(id),(x,y+h),font,1,255)
        
    cv2.imshow("Face",img);
    if(cv2.waitKey(1)==ord('q')):
        break;
cam.release()
cv2.destroyAllWindows()

can you help me ?