Initial Commit

.gitignore

@@ -0,0 +1,3 @@
+.idea
+__pycache__
+venv

.ipynb_checkpoints/Capture_Image-checkpoint.py

@@ -0,0 +1,76 @@
+import csv
+
+import cv2
+import os
+
+
+# counting the numbers
+
+
+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
+
+
+
+# Take image function
+
+def takeImages():
+
+
+    Id = input("Enter Your Id: ")
+    name = input("Enter Your Name: ")
+    email = input("Enter Your emailid: ")
+
+    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, minSize=(30,30),flags = cv2.CASCADE_SCALE_IMAGE)
+            for(x,y,w,h) in faces:
+                cv2.rectangle(img, (x, y), (x+w, y+h), (10, 159, 255), 2)
+                #incrementing sample number
+                sampleNum = sampleNum+1
+                #saving the captured face in the dataset folder TrainingImage
+                cv2.imwrite("TrainingImage" + os.sep +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 more than 100
+            elif sampleNum > 100:
+                break
+        cam.release()
+        cv2.destroyAllWindows()
+        res = "Images Saved for ID : " + Id + " Name : " + name + "Email :" + email 
+        row = [Id, name,email]
+        with open("StudentDetails"+os.sep+"StudentDetails.csv", 'a+') as csvFile:
+            writer = csv.writer(csvFile)
+            writer.writerow(row)
+        csvFile.close()
+    else:
+        if(is_number(Id)):
+            print("Enter Alphabetical Name")
+        if(name.isalpha()):
+            print("Enter Numeric ID")
+
+

.ipynb_checkpoints/Info-checkpoint.py

@@ -0,0 +1,2 @@
+EMAIL_ID = ''
+PASSWORD = ''

.ipynb_checkpoints/Recognize-checkpoint.py

@@ -0,0 +1,94 @@
+import datetime
+import os
+import time
+
+import cv2
+import pandas as pd
+from csv import writer 
+
+#-------------------------
+def recognize_attendence():
+    recognizer = cv2.face.LBPHFaceRecognizer_create()  # cv2.createLBPHFaceRecognizer()
+    recognizer.read("TrainingImageLabel"+os.sep+"Trainner.yml")
+    harcascadePath = "haarcascade_frontalface_default.xml"
+    faceCascade = cv2.CascadeClassifier(harcascadePath)
+    df = pd.read_csv("StudentDetails"+os.sep+"StudentDetails.csv")
+    font = cv2.FONT_HERSHEY_SIMPLEX
+    col_names = ['Id', 'Name', 'Time']
+    attendance = pd.DataFrame(columns=col_names)
+
+    # Initialize and start realtime video capture
+    cam = cv2.VideoCapture(0, cv2.CAP_DSHOW)
+    cam.set(3, 640)  # set video width
+    cam.set(4, 480)  # set video height
+    # Define min window size to be recognized as a face
+    minW = 0.1 * cam.get(3)
+    minH = 0.1 * cam.get(4)
+
+    while True:
+        minThreshold = 55 # Accurate minThresold = 67
+
+        ret, im = cam.read()
+        gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
+        faces = faceCascade.detectMultiScale(gray, 1.2, 5,minSize = (int(minW), int(minH)),flags = cv2.CASCADE_SCALE_IMAGE)
+        for(x, y, w, h) in faces:
+            cv2.rectangle(im, (x, y), (x+w, y+h), (10, 159, 255), 2)
+            Id, conf = recognizer.predict(gray[y:y+h, x:x+w])
+
+            if conf < 100:
+
+                aa = df.loc[df['Id'] == Id]['Name'].values
+                confstr = "  {0}%".format(round(100 - conf))
+                tt = str(Id)+"-"+aa
+
+            else:
+                Id = '  Unknown  '
+                tt = str(Id)
+                confstr = "  {0}%".format(round(100 - conf))
+
+            # if (100-conf) > 67:
+            if (100-conf) > minThreshold:
+                ts = time.time()
+                timeStamp = datetime.datetime.fromtimestamp(ts).strftime('%H:%M:%S')
+                aa = str(aa)[2:-2]
+
+                attendance.loc[len(attendance)] = [Id, aa, timeStamp]
+            tt = str(tt)[2:-2]
+            if(100-conf) > minThreshold:
+                tt = tt + " [Pass]"
+                cv2.putText(im, str(tt), (x+5,y-5), font, 1, (255, 255, 255), 2)
+            else:
+                cv2.putText(im, str(tt), (x + 5, y - 5), font, 1, (255, 255, 255), 2)
+
+            if (100-conf) > minThreshold:
+                cv2.putText(im, str(confstr), (x + 5, y + h - 5), font,1, (0, 255, 0),1 )
+            elif (100-conf) > 50:
+                cv2.putText(im, str(confstr), (x + 5, y + h - 5), font, 1, (0, 255, 255), 1)
+            else:
+                cv2.putText(im, str(confstr), (x + 5, y + h - 5), font, 1, (0, 0, 255), 1)
+
+
+
+        attendance = attendance.drop_duplicates(subset=['Id'], keep='first')
+        cv2.imshow('Attendance', 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"+os.sep+"Attendance_"+date+"_"+Hour+"-"+Minute+"-"+Second+".csv"
+    fileName ="Attendance"+os.sep+"Attendance_"+date+".csv"
+    temp = os.getcwd()+os.sep+fileName
+    if os.path.exists(temp):
+        old_file = pd.read_csv(temp)
+        new_file = pd.concat([old_file,attendance])
+        new_file.drop_duplicates(subset=['Id'], keep='first',inplace=True)
+        new_file.to_csv(fileName, index=False)
+    else:
+        attendance.to_csv(fileName, index=False)
+    print("Attendance Successful")
+    cam.release()
+    cv2.destroyAllWindows()
+
+

.ipynb_checkpoints/automail-checkpoint.py

@@ -0,0 +1,37 @@
+import yagmail
+import os
+import datetime
+import Info
+import pandas as pd
+import numpy as np
+
+date = datetime.date.today().strftime("%B %d, %Y")
+path = 'Attendance'
+os.chdir(path)
+files = sorted(os.listdir(os.getcwd()), key=os.path.getmtime)
+# receiver = '[email protected]'
+# receiver = '[email protected]'
+df = pd.read_csv(r'C:\Users\neel\Desktop\FRAS (1)\FRAS\StudentDetails\StudentDetails.csv')   #ama check kari lejo ke path set che ne
+
+receivers = df["email"]
+newest = files[-1]
+filename = newest
+sub = "Attendance Report for " + str(date)
+body = " Attendance Submitted."
+
+for receiver in receivers:
+    # receiver = '[email protected]'
+    # mail information
+    if pd.isnull(reciver):
+        continue
+    else:
+        yag = yagmail.SMTP(Info.EMAIL_ID, Info.PASSWORD)
+
+        # sent the mail
+        yag.send(
+            to=receiver,
+            subject=sub, # email subject
+            contents=body,  # email body
+            attachments= filename  # file attached
+        )
+        print("Email Sent to "+reciver)

.ipynb_checkpoints/main-checkpoint.py

@@ -0,0 +1,101 @@
+import os  # accessing the os functions
+import check_camera
+import Capture_Image
+import Train_Image
+import Recognize
+
+
+# creating the title bar function
+
+def title_bar():
+    os.system('cls')  # for windows
+
+    # title of the program
+
+    print("\t**********************************************")
+    print("\t***** Face Recognition Attendance System *****")
+    print("\t**********************************************")
+
+
+# creating the user main menu function
+
+def mainMenu():
+    title_bar()
+    print()
+    print(10 * "*", "WELCOME MENU", 10 * "*")
+    print("[1] Check Camera")
+    print("[2] Capture Faces")
+    print("[3] Train Images")
+    print("[4] Recognize & Attendance")
+    print("[5] Auto Mail")
+    print("[6] Quit")
+
+    while True:
+        try:
+            choice = int(input("Enter Choice: "))
+
+            if choice == 1:
+                checkCamera()
+                break
+            elif choice == 2:
+                CaptureFaces()
+                break
+            elif choice == 3:
+                Trainimages()
+                break
+            elif choice == 4:
+                RecognizeFaces()
+                break
+            elif choice == 5:
+                os.system("py automail.py")
+                break
+                mainMenu()
+            elif choice == 6:
+                print("Thank You")
+                break
+            else:
+                print("Invalid Choice. Enter 1-4")
+                mainMenu()
+        except ValueError:
+            print("Invalid Choice. Enter 1-4\n Try Again")
+    exit
+
+
+# ---------------------------------------------------------
+# calling the camera test function from check camera.py file
+
+def checkCamera():
+    check_camera.camer()
+    key = input("Enter any key to return main menu")
+    mainMenu()
+
+
+# --------------------------------------------------------------
+# calling the take image function form capture image.py file
+
+def CaptureFaces():
+    Capture_Image.takeImages()
+    key = input("Enter any key to return main menu")
+    mainMenu()
+
+
+# -----------------------------------------------------------------
+# calling the train images from train_images.py file
+
+def Trainimages():
+    Train_Image.TrainImages()
+    key = input("Enter any key to return main menu")
+    mainMenu()
+
+
+# --------------------------------------------------------------------
+# calling the recognize_attendance from recognize.py file
+
+def RecognizeFaces():
+    Recognize.recognize_attendence()
+    key = input("Enter any key to return main menu")
+    mainMenu()
+
+
+# ---------------main driver ------------------
+mainMenu()

.travis.yml

@@ -0,0 +1,9 @@
+language: python
+python:
+  - "3.7"
+# command to install dependencies
+cache: pip
+install:
+  - pip install -r requirements.txt
+# command to run tests
+script: python main.py

Attendance/.ipynb_checkpoints/Attendance_2021-02-27-checkpoint.csv

@@ -0,0 +1,7 @@
+Id,Name,Time
+1234,Urvesh,17.19.16
+29,neel,17.19.28
+69,dp,17.20.46
+98,nirja,17.20.50
+123,neel,17:53:32
+234,parul,17:53:39

Attendance/Attendance_2019-08-22_00-38-17.csv

@@ -0,0 +1,8 @@
+Id,Name,Date,Time
+1,['Mubin'],8/22/2019,0:36:55
+7,['Jonny'],8/22/2019,0:37:06
+6,['Ajay'],8/22/2019,0:37:33
+5,['Aksay'],8/22/2019,0:37:48
+4,['Salman'],8/22/2019,0:37:56
+3,['Tom'],8/22/2019,0:38:03
+2,['Aamir'],8/22/2019,0:38:10

Attendance/Attendance_2019-08-24_13-34-43.csv

@@ -0,0 +1,9 @@
+Id,Name,Date,Time
+2,['Jacky'],8/24/2019,13:31:55
+3,['Aamir'],8/24/2019,13:32:11
+4,['Tom'],8/24/2019,13:32:19
+1,['Mubin'],8/24/2019,13:32:38
+6,['Aksay'],8/24/2019,13:33:05
+12,['Bruce'],8/24/2019,13:34:09
+13,['Jonny'],8/24/2019,13:34:17
+11,['Kasfia'],8/24/2019,13:34:23

Attendance/Attendance_2019-08-24_14-11-44.csv

@@ -0,0 +1,3 @@
+Id,Name,Date,Time
+14,['Fuad'],2019-08-24,14:11:34
+1,['Mubin'],2019-08-24,14:11:42

Attendance/Attendance_2019-08-24_14-44-53.csv

@@ -0,0 +1,2 @@
+Id,Name,Date,Time
+15,['jawad'],2019-08-24,14:44:39

Attendance/Attendance_2021-02-27.csv

@@ -0,0 +1,8 @@
+Id,Name,Time
+1234,Urvesh,17.19.16
+29,neel,17.19.28
+69,dp,17.20.46
+98,nirja,17.20.50
+123,neel,17:53:32
+234,parul,17:53:39
+456,neelshah,20:14:44