├── StudentDetails └── StudentDetails.csv ├── Face_Recogniser 13-06-2020 9.14.42 PM.png ├── required.txt ├── README.md └── train.py /StudentDetails/StudentDetails.csv: -------------------------------------------------------------------------------- 1 | Id,Name 2 | -------------------------------------------------------------------------------- /Face_Recogniser 13-06-2020 9.14.42 PM.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/imbansalaniket/Facial-Recognition-Attandance-System-Using-Python/HEAD/Face_Recogniser 13-06-2020 9.14.42 PM.png -------------------------------------------------------------------------------- /required.txt: -------------------------------------------------------------------------------- 1 | cx-Freeze==6.0 2 | DateTime==4.3 3 | idna==2.8 4 | numpy==1.17.3 5 | opencv-contrib-python==4.2.0.34 6 | opencv-python==4.1.1.26 7 | pandas==1.0.4 8 | Pillow==7.1.2 9 | python-dateutil==2.8.0 10 | pytz==2019.3 11 | six==1.12.0 12 | zope.interface==4.6.0 13 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | To run this project on your machine, after unzipping the project follow these commands: 2 |
    3 |
  1. 4 | Create Several Empty directories with these exact names: 5 |
      6 |
    1. Attendance
      2. 7 |
    2. ImagesUnknown
      3. 8 |
    3. TrainingImage
      4. 9 |
    4. TrainingImageLabel
      5. 10 |
    11 |
    2. 12 |
  2. Then open Command Prompt in same Project directory and run these Commands: 13 |
    14 | (Assuming you have Python3 and pip installed) 15 |
      16 |
    1. pip install -r required.txt --user
      2. 17 |
    2. pip install -r opencv-contrib-python --upgrade --user
      3. 18 | Now you are all set to start this project, just start by this command: 19 |
    3. python train.py
      4. 20 |
    21 |
    3. 22 |
  3. You will be shown a window like this:
    23 | 24 |
    4. 25 |
  4. Enter Numeric value for Id.
    5. 26 |
  5. Enter your Name in the field provided.
    6. 27 |
  6. Click on Take Images. 28 |
    29 | (Another window will open and your webcam will be activated you can see it is taking your picture to train its model. 30 |
    31 | The window will close automatically,if it doesn't press q to close it.) 32 |
    7. 33 |
  7. Click on Train Images.
    8. 34 |
  8. Now Click on Track Images. 35 |
    36 | (Another window will open and your webcam will be activated you can see it is showing your name below your face.) 37 |
    9. 38 |
  9. Press q to close the window.
    10. 39 |
  10. Now go to your project diectory and open Attendance folder(remember you created blank folders). 40 |
    41 | Here you can see a .csv file is created open it with excel you can see it contains your name id and a datestamp of you when you tracked the image. 42 |
    11. 43 |
44 | Similarly You can train it for multiple peoples.(Place one person in the frame while taking the image.) 45 |
46 | Although try with multiple people in the frame when you are marking the attandance i.e. Tracking Images. 47 |
48 |
49 | For further assistance raise a Issue. 50 | -------------------------------------------------------------------------------- /train.py: -------------------------------------------------------------------------------- 1 | import tkinter as tk 2 | from tkinter import Message ,Text 3 | import cv2,os 4 | import shutil 5 | import csv 6 | import numpy as np 7 | from PIL import Image, ImageTk 8 | import pandas as pd 9 | import datetime 10 | import time 11 | import tkinter.ttk as ttk 12 | import tkinter.font as font 13 | 14 | window = tk.Tk() 15 | #helv36 = tk.Font(family='Helvetica', size=36, weight='bold') 16 | window.title("Face_Recogniser") 17 | 18 | dialog_title = 'QUIT' 19 | dialog_text = 'Are you sure?' 20 | #answer = messagebox.askquestion(dialog_title, dialog_text) 21 | 22 | window.geometry('1280x720') 23 | window.configure(background='grey') 24 | 25 | #window.attributes('-fullscreen', True) 26 | 27 | window.grid_rowconfigure(0, weight=1) 28 | window.grid_columnconfigure(0, weight=1) 29 | 30 | #path = "profile.jpg" 31 | 32 | #Creates a Tkinter-compatible photo image, which can be used everywhere Tkinter expects an image object. 33 | #img = ImageTk.PhotoImage(Image.open(path)) 34 | 35 | #The Label widget is a standard Tkinter widget used to display a text or image on the screen. 36 | #panel = tk.Label(window, image = img) 37 | 38 | 39 | #panel.pack(side = "left", fill = "y", expand = "no") 40 | 41 | #cv_img = cv2.imread("img541.jpg") 42 | #x, y, no_channels = cv_img.shape 43 | #canvas = tk.Canvas(window, width = x, height =y) 44 | #canvas.pack(side="left") 45 | #photo = PIL.ImageTk.PhotoImage(image = PIL.Image.fromarray(cv_img)) 46 | # Add a PhotoImage to the Canvas 47 | #canvas.create_image(0, 0, image=photo, anchor=tk.NW) 48 | 49 | #msg = Message(window, text='Hello, world!') 50 | 51 | # Font is a tuple of (font_family, size_in_points, style_modifier_string) 52 | 53 | 54 | 55 | message = tk.Label(window, text="Face-Recognition-Based-Attendance-Management-System" ,fg="black", bg="grey" ,font=('times', 30, 'italic bold underline')) 56 | 57 | message.place(x=200, y=20) 58 | 59 | lbl = tk.Label(window, text="Enter ID",width=20 ,height=2, bg="grey" ,font=('times', 15, ' bold ') ) 60 | lbl.place(x=400, y=200) 61 | 62 | txt = tk.Entry(window,width=20 ,bg="white" ,font=('times', 15, ' bold ')) 63 | txt.place(x=700, y=215) 64 | 65 | lbl2 = tk.Label(window, text="Enter Name",width=20 ,bg="grey" ,height=2 ,font=('times', 15, ' bold ')) 66 | lbl2.place(x=400, y=300) 67 | 68 | txt2 = tk.Entry(window,width=20 ,bg="white" ,font=('times', 15, ' bold ') ) 69 | txt2.place(x=700, y=315) 70 | 71 | lbl3 = tk.Label(window, text="Notification : ",width=20 ,bg="grey" ,height=2 ,font=('times', 15, ' bold ')) 72 | lbl3.place(x=400, y=400) 73 | 74 | message = tk.Label(window, text="" ,bg="grey" ,width=30 ,height=2, activebackground = "yellow" ,font=('times', 15, ' bold ')) 75 | message.place(x=700, y=400) 76 | 77 | lbl3 = tk.Label(window, text="Attendance : ",width=20 ,bg="grey" ,height=2 ,font=('times', 15, ' bold underline')) 78 | lbl3.place(x=400, y=600) 79 | 80 | 81 | message2 = tk.Label(window, text="" ,bg="grey",activeforeground = "green",width=30 ,height=2 ,font=('times', 15, ' bold ')) 82 | message2.place(x=700, y=600) 83 | 84 | def clear(): 85 | txt.delete(0, 'end') 86 | res = "" 87 | message.configure(text= res) 88 | 89 | def clear2(): 90 | txt2.delete(0, 'end') 91 | res = "" 92 | message.configure(text= res) 93 | 94 | def is_number(s): 95 | try: 96 | float(s) 97 | return True 98 | except ValueError: 99 | pass 100 | 101 | try: 102 | import unicodedata 103 | unicodedata.numeric(s) 104 | return True 105 | except (TypeError, ValueError): 106 | pass 107 | 108 | return False 109 | 110 | def TakeImages(): 111 | Id=(txt.get()) 112 | name=(txt2.get()) 113 | if(is_number(Id) and name != ""): 114 | cam = cv2.VideoCapture(0) 115 | harcascadePath = "haarcascade_frontalface_default.xml" 116 | detector=cv2.CascadeClassifier(harcascadePath) 117 | sampleNum=0 118 | while(True): 119 | ret, img = cam.read() 120 | gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) 121 | faces = detector.detectMultiScale(gray, 1.3, 5) 122 | for (x,y,w,h) in faces: 123 | cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2) 124 | #incrementing sample number 125 | sampleNum=sampleNum+1 126 | #saving the captured face in the dataset folder TrainingImage 127 | cv2.imwrite("TrainingImage\ "+name +"."+Id +'.'+ str(sampleNum) + ".jpg", gray[y:y+h,x:x+w]) 128 | #display the frame 129 | cv2.imshow('frame',img) 130 | #wait for 100 miliseconds 131 | if cv2.waitKey(100) & 0xFF == ord('q'): 132 | break 133 | # break if the sample number is morethan 100 134 | elif sampleNum>60: 135 | break 136 | cam.release() 137 | cv2.destroyAllWindows() 138 | res = "Images Saved for ID : " + Id +" Name : "+ name 139 | row = [Id , name] 140 | with open('StudentDetails\StudentDetails.csv','a+') as csvFile: 141 | writer = csv.writer(csvFile) 142 | writer.writerow(row) 143 | csvFile.close() 144 | message.configure(text= res) 145 | else: 146 | if(is_number(Id)): 147 | res = "Enter Alphabetical Name" 148 | message.configure(text= res) 149 | if(name.isalpha()): 150 | res = "Enter Numeric Id" 151 | message.configure(text= res) 152 | 153 | def TrainImages(): 154 | recognizer = cv2.face_LBPHFaceRecognizer.create()#recognizer = cv2.face.LBPHFaceRecognizer_create()#$cv2.createLBPHFaceRecognizer() 155 | harcascadePath = "haarcascade_frontalface_default.xml" 156 | detector =cv2.CascadeClassifier(harcascadePath) 157 | faces,Id = getImagesAndLabels("TrainingImage") 158 | recognizer.train(faces, np.array(Id)) 159 | recognizer.save("TrainingImageLabel\Trainner.yml") 160 | res = "Image Trained"#+",".join(str(f) for f in Id) 161 | message.configure(text= res) 162 | 163 | def getImagesAndLabels(path): 164 | #get the path of all the files in the folder 165 | imagePaths=[os.path.join(path,f) for f in os.listdir(path)] 166 | #print(imagePaths) 167 | 168 | #create empth face list 169 | faces=[] 170 | #create empty ID list 171 | Ids=[] 172 | #now looping through all the image paths and loading the Ids and the images 173 | for imagePath in imagePaths: 174 | #loading the image and converting it to gray scale 175 | pilImage=Image.open(imagePath).convert('L') 176 | #Now we are converting the PIL image into numpy array 177 | imageNp=np.array(pilImage,'uint8') 178 | #getting the Id from the image 179 | Id=int(os.path.split(imagePath)[-1].split(".")[1]) 180 | # extract the face from the training image sample 181 | faces.append(imageNp) 182 | Ids.append(Id) 183 | return faces,Ids 184 | 185 | def TrackImages(): 186 | recognizer = cv2.face.LBPHFaceRecognizer_create()#cv2.createLBPHFaceRecognizer() 187 | recognizer.read("TrainingImageLabel\Trainner.yml") 188 | harcascadePath = "haarcascade_frontalface_default.xml" 189 | faceCascade = cv2.CascadeClassifier(harcascadePath); 190 | df=pd.read_csv("StudentDetails\StudentDetails.csv") 191 | cam = cv2.VideoCapture(0) 192 | font = cv2.FONT_HERSHEY_SIMPLEX 193 | col_names = ['Id','Name','Date','Time'] 194 | attendance = pd.DataFrame(columns = col_names) 195 | while True: 196 | ret, im =cam.read() 197 | gray=cv2.cvtColor(im,cv2.COLOR_BGR2GRAY) 198 | faces=faceCascade.detectMultiScale(gray, 1.2,5) 199 | for(x,y,w,h) in faces: 200 | cv2.rectangle(im,(x,y),(x+w,y+h),(225,0,0),2) 201 | Id, conf = recognizer.predict(gray[y:y+h,x:x+w]) 202 | if(conf < 60): 203 | ts = time.time() 204 | date = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d') 205 | timeStamp = datetime.datetime.fromtimestamp(ts).strftime('%H:%M:%S') 206 | aa=df.loc[df['Id'] == Id]['Name'].values 207 | tt=str(Id)+"-"+aa 208 | attendance.loc[len(attendance)] = [Id,aa,date,timeStamp] 209 | 210 | else: 211 | Id='Unknown' 212 | tt=str(Id) 213 | # if(conf > 50): 214 | # noOfFile=len(os.listdir("ImagesUnknown"))+1 215 | # cv2.imwrite("ImagesUnknown\Image"+str(noOfFile) + ".jpg", im[y:y+h,x:x+w]) 216 | cv2.putText(im,str(tt),(x,y+h), font, 1,(255,255,255),2) 217 | attendance=attendance.drop_duplicates(subset=['Id'],keep='first') 218 | cv2.imshow('im',im) 219 | if (cv2.waitKey(1)==ord('q')): 220 | break 221 | ts = time.time() 222 | date = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d') 223 | timeStamp = datetime.datetime.fromtimestamp(ts).strftime('%H:%M:%S') 224 | Hour,Minute,Second=timeStamp.split(":") 225 | fileName="Attendance\Attendance_"+date+"_"+Hour+"-"+Minute+"-"+Second+".csv" 226 | attendance.to_csv(fileName,index=False) 227 | cam.release() 228 | cv2.destroyAllWindows() 229 | # print(attendance) 230 | res=attendance 231 | message2.configure(text= res) 232 | 233 | 234 | clearButton = tk.Button(window, text="Clear", command=clear ,width=5 ,height=1 ,activebackground = "Red" ,font=('times', 15, ' bold ')) 235 | clearButton.place(x=950, y=210) 236 | clearButton2 = tk.Button(window, text="Clear", command=clear2 ,width=5 ,height=1, activebackground = "Red" ,font=('times', 15, ' bold ')) 237 | clearButton2.place(x=950, y=310) 238 | takeImg = tk.Button(window, text="Take Images", command=TakeImages ,width=10 ,height=1, activebackground = "Red" ,font=('times', 15, ' bold ')) 239 | takeImg.place(x=200, y=500) 240 | trainImg = tk.Button(window, text="Train Images", command=TrainImages ,width=10 ,height=1, activebackground = "Red" ,font=('times', 15, ' bold ')) 241 | trainImg.place(x=500, y=500) 242 | trackImg = tk.Button(window, text="Track Images", command=TrackImages ,width=10 ,height=1, activebackground = "Red" ,font=('times', 15, ' bold ')) 243 | trackImg.place(x=800, y=500) 244 | quitWindow = tk.Button(window, text="Quit", command=window.destroy ,width=10 ,height=1, activebackground = "Red" ,font=('times', 15, ' bold ')) 245 | quitWindow.place(x=1100, y=500) 246 | 247 | 248 | window.mainloop() --------------------------------------------------------------------------------