Face-Recognition/train.py at main · shivakantkurmi/Face-Recognition · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
from tkinter import *
from tkinter import ttk
from PIL import Image, ImageTk
from tkinter import messagebox
import mysql.connector
import cv2

import os
import numpy as np

class Train:
    def __init__(self, root):
        self.root=root
        self.root.geometry("1530x790+0+0")
        self.root.title("Face Recognition System")

        title_lbl = Label(self.root, text="TRAIN DATASET", font=("times new roman",35,"bold"),bg="white",fg="green")
        title_lbl.place(x=0,y=0,width=1530,height=45)

        img_top = Image.open(r"img\facialrecognition.png")
        img_top = img_top.resize((1530,325),Image.LANCZOS)
        self.photoimg_top = ImageTk.PhotoImage(img_top)

        f_lbl = Label( self.root,image = self.photoimg_top)
        f_lbl.place(x=0,y=55,width=1530,height=325)

        #button
        b1_1 = Button(self.root, text="Train Data",command=self.train_classifier, cursor="hand2",font=("times new roman",30,"bold"),bg="red",fg="white")
        b1_1.place(x=0,y=380,width=1530,height=60)


        img_bottom = Image.open(r"img\di.jpg")
        img_bottom = img_bottom.resize((1530,325),Image.LANCZOS)
        self.photoimg_bottom = ImageTk.PhotoImage(img_bottom)

        f_lbl = Label( self.root,image = self.photoimg_bottom)
        f_lbl.place(x=0,y=440,width=1530,height=325)


    def train_classifier(self):
        data_dir = "data"
        if not os.path.exists(data_dir):
            os.makedirs(data_dir)
            print("Directory 'data' created successfully.")

        # Proceed with reading files from the data directory
        path = [os.path.join(data_dir, file) for file in os.listdir(data_dir)]
        # Continue with the rest of your code

        faces = []
        ids =[]

        for image in path:
            img = Image.open(image).convert('L')  #gray scale image
            imageNp = np.array(img,'uint8')
            id = int(os.path.split(image)[1].split('.')[1])

            faces.append(imageNp)
            ids.append(id)

            cv2.imshow("Training",imageNp)
            cv2.waitKey(1)==13
        ids=np.array(ids)

        #========train the classifier and save============
        clf = cv2.face.LBPHFaceRecognizer_create()
        clf.train(faces,ids)
        clf.write("classifier.xml")
        cv2.destroyAllWindows()
        messagebox.showinfo("Result","Training datasets completed!!!",parent=self.root)


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