-
Notifications
You must be signed in to change notification settings - Fork 0
/
train.py
400 lines (345 loc) · 16.6 KB
/
train.py
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
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
import tkinter as tk
from tkinter import Message ,Text
import cv2,os
import shutil
import csv
import numpy as np
from PIL import Image, ImageTk
import pandas as pd
import datetime
import time
import tkinter.ttk as ttk
import tkinter.font as font
# window = tk.Tk()
# #helv36 = tk.Font(family='Helvetica', size=36, weight='bold')
# window.title("Face_Recognition_for_Attendance")
# dialog_title = 'QUIT'
# dialog_text = 'Are you sure?'
# #answer = messagebox.askquestion(dialog_title, dialog_text)
# #window.geometry('1280x720')
# window.configure(background='black')
# window.attributes('-fullscreen', True)
# canvas = tk.Canvas(window, width=1500, height=900)
# canvas.pack()
# img = ImageTk.PhotoImage(Image.open("P1.jpg"))
# canvas.create_image(0, 0, anchor='nw', image=img)
# window.grid_rowconfigure(0, weight=1)
# window.grid_columnconfigure(0, weight=1)
#path = "profile.jpg"
#Creates a Tkinter-compatible photo image, which can be used everywhere Tkinter expects an image object.
#img = ImageTk.PhotoImage(Image.open(path))
#The Label widget is a standard Tkinter widget used to display a text or image on the screen.
#panel = tk.Label(window, image = img)
#panel.pack(side = "left", fill = "y", expand = "no")
#cv_img = cv2.imread("img541.jpg")
#x, y, no_channels = cv_img.shape
#canvas = tk.Canvas(window, width = x, height =y)
#canvas.pack(side="left")
#photo = PIL.ImageTk.PhotoImage(image = PIL.Image.fromarray(cv_img))
# Add a PhotoImage to the Canvas
#canvas.create_image(0, 0, image=photo, anchor=tk.NW)
#msg = Message(window, text='Hello, world!')
# Font is a tuple of (font_family, size_in_points, style_modifier_string)
# border = tk.Label(window, text="WELCOME TO SMART ATTENDANCE SYSTEM :: ENTER YOUR DETAILS AND CAPTURE PICTURES AND PRESS 'TRAIN IMAGE' :: EXISTING USER: Click on 'TRACK IMAGE' after tracking Press 'Q'",
# width=200, height=1, bg='Red', fg="yellow", font=('Helvetica', 7, ' bold '), relief="raised")
# border.place(x=0, y=0)
# message = tk.Label(window, text="STUDENT ATTENDENCE MANAGMENT SYSTEM" ,bg="white" ,fg="black" ,width=40 ,height=3,font=('times', 35, ' bold'))
# message.place(x=50, y=18 )
# lbl = tk.Label(window, text="Enter ID",width=20 ,height=2 ,fg="black" ,bg="white" ,font=('times', 15, ' bold ') )
# lbl.place(x=300, y=200)
# txt = tk.Entry(window,width=20 ,bg="white" ,fg="black",font=('times', 15, ' bold '))
# txt.place(x=700, y=215)
# lbl2 = tk.Label(window, text="Enter Name",width=20 ,fg="black" ,bg="white" ,height=2 ,font=('times', 15, ' bold '))
# lbl2.place(x=400, y=300)
# txt2 = tk.Entry(window,width=20 ,bg="white" ,fg="black",font=('times', 15, ' bold ') )
# txt2.place(x=700, y=315)
# lblClass = tk.Label(window, text="Enter Class",width=20 ,fg="black" ,bg="white" ,height=2 ,font=('times', 15, ' bold '))
# lblClass.place(x=400, y=350)
# txtClass = tk.Entry(window,width=20 ,bg="white" ,fg="black",font=('times', 15, ' bold ') )
# txtClass.place(x=700, y=365)
# lbl3 = tk.Label(window, text="Notification : ",width=20 ,fg="black" ,bg="white" ,height=2 ,font=('times', 15, ' bold underline '))
# lbl3.place(x=400, y=400)
# message = tk.Label(window, text="" ,bg="white" ,fg="black" ,width=30 ,height=2, activebackground = "yellow" ,font=('times', 15, ' bold '))
# message.place(x=700, y=400)
# lbl3 = tk.Label(window, text="Attendance : ",width=20 ,fg="white" ,bg="Blue" ,height=2 ,font=('times', 15, ' bold underline'))
# lbl3.place(x=400, y=720)
# message2 = tk.Label(window, text="" ,fg="white" ,bg="Blue",activeforeground = "green",width=30 ,height=2 ,font=('times', 15, ' bold '))
# message2.place(x=700, y=720)
# def clear():
# txt.delete(0, 'end')
# res = ""
# message.configure(text= res)
# def clear2():
# txt2.delete(0, 'end')
# res = ""
# message.configure(text= res)
def is_number(s):
try:
float(s)
return True
except ValueError:
pass
try:
import unicodedata
unicodedata.numeric(s)
return True
except (TypeError, ValueError):
pass
return False
# def TakeImages():
# Id=(txt.get())
# name=(txt2.get())
# className=(txtClass.get())
# if(is_number(Id) and name.isalpha()):
# cam = cv2.VideoCapture(0)
# harcascadePath = "haarcascade_frontalface_default.xml"
# detector=cv2.CascadeClassifier(harcascadePath)
# sampleNum=0
# while(True):
# ret, img = cam.read()
# gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# faces = detector.detectMultiScale(gray, 1.3, 5)
# for (x,y,w,h) in faces:
# cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
# #incrementing sample number
# sampleNum=sampleNum+1
# #saving the captured face in the dataset folder TrainingImage
# cv2.imwrite("TrainingImage\ "+name +"."+Id +'.'+ str(sampleNum) + ".jpg", gray[y:y+h,x:x+w])
# #display the frame
# cv2.imshow('frame',img)
# #wait for 100 miliseconds
# if cv2.waitKey(100) & 0xFF == ord('q'):
# break
# # break if the sample number is morethan 100
# elif sampleNum>60:
# break
# cam.release()
# cv2.destroyAllWindows()
# res = "Images Saved for ID : " + Id +" Name : "+ name
# row = [Id , name, className]
# with open('StudentDetails\StudentDetails.csv','a+') as csvFile:
# writer = csv.writer(csvFile)
# writer.writerow(row)
# csvFile.close()
# message.configure(text= res)
# else:
# if(is_number(Id)):
# res = "Enter Alphabetical Name"
# message.configure(text= res)
# if(name.isalpha()):
# res = "Enter Numeric Id"
# message.configure(text= res)
# def TrainImages():
# recognizer = cv2.face.LBPHFaceRecognizer.create()#recognizer = cv2.face.LBPHFaceRecognizer_create()#$cv2.createLBPHFaceRecognizer()
# harcascadePath = "haarcascade_frontalface_default.xml"
# detector =cv2.CascadeClassifier(harcascadePath)
# faces,Id = getImagesAndLabels("TrainingImage")
# recognizer.train(faces, np.array(Id))
# recognizer.save("face-trainner.yml")
# res = "Image Trained"#+",".join(str(f) for f in Id)
# message.configure(text= res)
# def StudentData():
# hyperlink_format.format(link='C:\Users\hp\Downloads\final\F!\StudentDetails\StudentDetails.csv', text='Student Data')
# '<a href="C:\Users\hp\Downloads\final\F!\StudentDetails\StudentDetails.csv">Student Data</a>'
def getImagesAndLabels(path):
#get the path of all the files in the folder
imagePaths=[os.path.join(path,f) for f in os.listdir(path)]
#print(imagePaths)
#create empth face list
faces=[]
#create empty ID list
Ids=[]
#now looping through all the image paths and loading the Ids and the images
for imagePath in imagePaths:
#loading the image and converting it to gray scale
pilImage=Image.open(imagePath).convert('L')
#Now we are converting the PIL image into numpy array
imageNp=np.array(pilImage,'uint8')
#getting the Id from the image
Id=int(os.path.split(imagePath)[-1].split(".")[1])
# extract the face from the training image sample
faces.append(imageNp)
Ids.append(Id)
return faces,Ids
# def display_csv():
attendance_dir = "Attendance" # Replace with the actual directory path
# latest_file = max(os.listdir(attendance_dir), key=lambda x: os.path.getctime(attendance_dir+'/'+x))
latest_file = os.listdir(attendance_dir)[0]
file_path = os.path.join(attendance_dir, latest_file)
with open(file_path) as csvfile:
reader = csv.DictReader(csvfile)
tree = ttk.Treeview(window, columns=reader.fieldnames)
tree.pack(fill=tk.BOTH, expand=True)
for row in reader:
tree.insert("", tk.END, values=list(row.values()))
for col in reader.fieldnames:
tree.heading(col, text=col)
# def TrackImages():
recognizer = cv2.face.LBPHFaceRecognizer_create()#cv2.createLBPHFaceRecognizer()
recognizer.read("face-trainner.yml")
harcascadePath = "haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(harcascadePath);
df=pd.read_csv("StudentDetails\StudentDetails.csv")
cam = cv2.VideoCapture(0)
font = cv2.FONT_HERSHEY_SIMPLEX
col_names = ['Id','Name','Date','Time']
attendance = pd.DataFrame(columns = col_names)
while True:
ret, im =cam.read()
gray=cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
faces=faceCascade.detectMultiScale(gray, 1.2,5)
for(x,y,w,h) in faces:
cv2.rectangle(im,(x,y),(x+w,y+h),(225,0,0),2)
Id, conf = recognizer.predict(gray[y:y+h,x:x+w])
if(conf < 50):
ts = time.time()
date = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d')
timeStamp = datetime.datetime.fromtimestamp(ts).strftime('%H:%M:%S')
aa=df.loc[df['Id'] == Id]['Name'].values
tt=str(Id)+"-"+aa
attendance.loc[len(attendance)] = [Id,aa,date,timeStamp]
else:
Id='Unknown'
tt=str(Id)
if(conf > 75):
noOfFile=len(os.listdir("ImagesUnknown"))+1
cv2.imwrite("ImagesUnknown\Image"+str(noOfFile) + ".jpg", im[y:y+h,x:x+w])
cv2.putText(im,str(tt),(x,y+h), font, 1,(255,255,255),2)
attendance=attendance.drop_duplicates(subset=['Id'],keep='first')
cv2.imshow('im',im)
if (cv2.waitKey(1)==ord('q')):
break
ts = time.time()
date = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d')
timeStamp = datetime.datetime.fromtimestamp(ts).strftime('%H:%M:%S')
Hour,Minute,Second=timeStamp.split(":")
fileName="Attendance\Attendance_"+date+"_"+Hour+"-"+Minute+"-"+Second+".csv"
attendance.to_csv(fileName,index=False)
cam.release()
cv2.destroyAllWindows()
#print(attendance)
res=attendance
message2.configure(text= res)
# clearButton = tk.Button(window, text="Clear", command=clear ,fg="black" ,bg="white" ,width=20 ,height=2 ,activebackground = "Red" ,font=('times', 15, ' bold '))
# clearButton.place(x=950, y=200)
# clearButton2 = tk.Button(window, text="Clear", command=clear2 ,fg="black" ,bg="white" ,width=20 ,height=2, activebackground = "Red" ,font=('times', 15, ' bold '))
# clearButton2.place(x=950, y=300)
# takeImg = tk.Button(window, text="Take Images", command=TakeImages ,fg="black" ,bg="white" ,width=20 ,height=3, activebackground = "Red" ,font=('times', 15, ' bold '))
# takeImg.place(x=200, y=500)
# takeImg = tk.Button(window, text="Student Data", command=TakeImages ,fg="black" ,bg="white" ,width=20 ,height=3, activebackground = "Red" ,font=('times', 15, ' bold '))
# takeImg.place(x=200, y=600)
# trainImg = tk.Button(window, text="Train Images", command=TrainImages ,fg="black" ,bg="white" ,width=20 ,height=3, activebackground = "Red" ,font=('times', 15, ' bold '))
# trainImg.place(x=500, y=500)
# # trainImg = tk.Button(window, text="Attendance Files", command=display_csv ,fg="black" ,bg="white" ,width=20 ,height=3, activebackground = "Red" ,font=('times', 15, ' bold '))
# # trainImg.place(x=500, y=600)
# trackImg = tk.Button(window, text="Track Images", command=TrackImages ,fg="black" ,bg="white" ,width=20 ,height=3, activebackground = "Red" ,font=('times', 15, ' bold '))
# trackImg.place(x=800, y=500)
# trackImg = tk.Button(window, text="Analytics", command=TrackImages ,fg="black" ,bg="white" ,width=20 ,height=3, activebackground = "Red" ,font=('times', 15, ' bold '))
# trackImg.place(x=800, y=600)
# copyWrite = tk.Label(window, text="Created By Pu-Tech \n (Yash, Diya, Jugal, Kinjal, Yogesh)",
# bg="Red", fg="black", width=100, height=2, activebackground="Blue", font=('times', 12, ' bold '))
# copyWrite.place(x=300, y=800)
# quitWindow = tk.Button(window, text="Quit", command=window.destroy ,fg="black" ,bg="white" ,width=20 ,height=3, activebackground = "Red" ,font=('times', 15, ' bold '))
# quitWindow.place(x=1100, y=500)
# window.mainloop()
def TakeImagesRequest(Id, name, className):
if(is_number(Id)):
cam = cv2.VideoCapture(0)
cam.set(cv2.CAP_PROP_FPS, 5)
harcascadePath = "haarcascade_frontalface_default.xml"
detector=cv2.CascadeClassifier(harcascadePath)
sampleNum=0
while(True):
ret, img = cam.read()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = detector.detectMultiScale(gray, 1.3, 5)
for (x,y,w,h) in faces:
cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
#incrementing sample number
sampleNum=sampleNum+1
#saving the captured face in the dataset folder TrainingImage
cv2.imwrite("TrainingImage\ "+name +"."+str(Id) +'.'+ str(sampleNum) + ".jpg", gray[y:y+h,x:x+w])
#display the frame
cv2.imshow('frame',img)
#wait for 100 miliseconds
if cv2.waitKey(100) & 0xFF == ord('q'):
break
# break if the sample number is morethan 100
elif sampleNum>60:
break
cam.release()
cv2.destroyAllWindows()
row = [Id , name, className]
with open('StudentDetails\StudentDetails.csv','a+') as csvFile:
writer = csv.writer(csvFile)
writer.writerow(row)
csvFile.close()
return "Images Saved for ID: "+str(Id)+", Name: "+name+" and Class: "+ className
else:
return ""
# TakeImagesRequest(5, 'Tushar', 'CSA')
def TrainImagesRequest():
recognizer = cv2.face.LBPHFaceRecognizer.create()#recognizer = cv2.face.LBPHFaceRecognizer_create()#$cv2.createLBPHFaceRecognizer()
harcascadePath = "haarcascade_frontalface_default.xml"
detector =cv2.CascadeClassifier(harcascadePath)
faces,Id = getImagesAndLabels("TrainingImage")
recognizer.train(faces, np.array(Id))
recognizer.save("face-trainner.yml")
return True
def TrackImagesRequest(teacher):
recognizer = cv2.face.LBPHFaceRecognizer_create()#cv2.createLBPHFaceRecognizer()
recognizer.read("face-trainner.yml")
harcascadePath = "haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(harcascadePath);
df=pd.read_csv("StudentDetails\StudentDetails.csv")
cam = cv2.VideoCapture(0)
cam.set(cv2.CAP_PROP_FPS, 5)
font = cv2.FONT_HERSHEY_SIMPLEX
col_names = ['Id','Name', 'Class', 'Date','Time']
attendance = pd.DataFrame(columns = col_names)
while True:
ret, im =cam.read()
gray=cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
faces=faceCascade.detectMultiScale(gray, 1.2,5)
for(x,y,w,h) in faces:
cv2.rectangle(im,(x,y),(x+w,y+h),(225,0,0),2)
Id, conf = recognizer.predict(gray[y:y+h,x:x+w])
if(conf < 50):
ts = time.time()
date = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d')
timeStamp = datetime.datetime.fromtimestamp(ts).strftime('%H:%M:%S')
aa=df.loc[df['Id'] == Id]['Name'].values[0]
ac=df.loc[df['Id'] == Id]['ClassName'].values[0]
tt=str(Id)+"-"+aa
attendance.loc[len(attendance)] = [Id,aa,ac,date,timeStamp]
else:
Id='Unknown'
tt=str(Id)
cv2.putText(im,str(tt),(x,y+h), font, 1,(255,255,255),2)
attendance=attendance.drop_duplicates(subset=['Id'],keep='first')
cv2.imshow('im',im)
if (cv2.waitKey(1)==ord('q')):
break
ts = time.time()
date = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d')
fileName="Attendance\Attendance_"+date+"_"+teacher +".csv"
attendance.to_csv(fileName,index=False)
cam.release()
cv2.destroyAllWindows()
#print(attendance)
res=attendance
return res
def ViewAttendanceRequest(date, teacher):
fileName="Attendance\Attendance_"+date+"_"+teacher +".csv"
df = pd.read_csv(fileName)
new_column_names = {
'Id': 'id',
'Name': 'name',
'Class': 'batch',
'Date': 'date',
'Time': 'time'
# Add more key-value pairs for the columns you want to rename
}
df = df.rename(columns=new_column_names)
data = df.to_dict(orient='records')
return data