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face_recognition.py
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face_recognition.py
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# Import OpenCV2 for image processing
import cv2
#import employee
import pickle
#Import numpy for matrices calculations
import numpy as np
import datetime
import time
from pygame import mixer
import os
import sys
import pyttsx3
now = datetime.datetime.now()
Date=now.strftime("%d-%m-%Y")
Time=now.strftime("%H:%M:%S")
dn=now.strftime('%H')
dn1=int(dn)
# Create Local Binary Patterns Histograms for face recognization
recognizer = cv2.face.LBPHFaceRecognizer_create()
# Load the trained mode
recognizer.read('trainer/trainer.yml')
# Load prebuilt model for Frontal Face
cascadePath = ("haarcascade_frontalface_default.xml")
cascadePath2 = ("haarcascade_eye.xml")
# Create classifier from prebuilt model
faceCascade = cv2.CascadeClassifier(cascadePath);
eyeCascade = cv2.CascadeClassifier(cascadePath2)
# Set the font style
font = cv2.FONT_HERSHEY_SIMPLEX
def welcome(dn1):
engine = pyttsx3.init()
if dn1<13:
engine.say('Good morning ! Welcome to apna Infotech')
engine.runAndWait()
else:
engine.say('Good evening ! Welcome to apna Infotech')
engine.runAndWait()
def greet(i,dn1):
engine = pyttsx3.init()
s=''
if dn1<12:
engine.say('Good morning %s'%i)
engine.runAndWait()
elif dn1<17:
engine.say('Good afternoon %s'%i)
engine.runAndWait()
else:
engine.say('Good evening %s'%i)
engine.runAndWait()
# alert sound when recoganized and saved to file
def alert():
mixer.init()
alert = mixer.Sound('beep-07.wav')
alert.play()
time.sleep(0.1)
alert.play()
#SAVE to file
def attendance(Id, lt):
file = open("Employee Attendance.csv", "a")
#file.write("\n" + Date)
id1 = str(Id)
ir = id1[2]
ir2 = id1[3]
if (ir == ','):
id2 = id1[1]
print("EMPLOYEE ID:", id2)
print("Local current time :", lt)
file.write("\n" + id2 + ' ' + lt)
alert()
greet(id2,dn1)
print("ALERT!! ATTENDANCE MARKED")
elif (ir2 == ','):
id2 = id1[1]+id1[2]
print("EMPLOYEE ID:", id2)
print("Local current time :", lt)
file.write("\n" + id2 + ' ' + lt)
alert()
greet(id2,dn1)
print("ALERT!! ATTENDANCE MARKED")
else:
id2 = id1[1] + id1[2] + id1[3]
file.write("\n" + id2 + ' ' + lt)
print("EMPLOYEE ID:", id2)
print("Local current time :", lt)
alert()
greet(id2,dn1)
print("ALERT!! ATTENDANCE MARKED")
file.close()
# Initialize and start the video frame capture
cam = cv2.VideoCapture(0)
eyeDetected = False
oneEyeDetected = False
x = 0
y = 0
w = 0
Id = ()
k=False
# Loop
while True:
# Read the video frame
ret, im = cam.read()
# Convert the captured frame into grayscale
gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
# Get all face from the video frame
faces = faceCascade.detectMultiScale(gray, 1.2, 5)
# For each face in faces
for (x, y, w, h) in faces:
# Create rectangle around the face
cv2.rectangle(im, (x - 20, y - 20), (x + w + 20, y + h + 20), (255, 0, 0), 4)
roi_gray = gray[y:y + h, x:x + w]
roi_color = im[y:y + h, x:x + w]
# Recognize the face belongs to which ID
Id = recognizer.predict(gray[y:y + h, x:x + w])
cv2.putText(im, 'Face Detected', (10, 30), font, 1, (255, 0, 0), 2)
if k==False:
welcome(dn1)
k=True
ip=Id[0]
# to detect eye in face
eyes = eyeCascade.detectMultiScale(roi_gray,
scaleFactor = 1.2,
minNeighbors = 5,
minSize = (15, 15),
maxSize = (80, 80))
try:
eyes
except NameError:
print("No eyes detected!")
else:
ii = 0
# for each eye in face
for (ex, ey, ew, eh) in eyes:
if ip >= 1:
cv2.putText(im, 'Eye Detected!', (10, 100), font, 1, (255, 0, 0), 2)
cv2.rectangle(roi_color, (ex, ey), (ex + ew, ey + eh), (0, 0, 255), 2)
if ((ip >= 1 and ii < 1 and ey < (h * .33) and oneEyeDetected == False and eyeDetected == False)):
# local time on pc
#lt = time.asctime(time.localtime(time.time()))
lt2=Time
attendance(Id,lt2)
cv2.putText(im, 'ATTENDANCE MARKED!', (10, 300), font, 1, (255, 255, 255), 2)
id5=Id
#time.sleep(200)
if id5==Id:
#attendance marked
eyeDetected = True
else:
#attendance not marked
eyeDetected = False
# Put text describe who is in the picture
cv2.rectangle(im, (x - 22, y - 90), (x + w + 22, y - 22), (0, 255, 0), -1)
cv2.putText(im, str(Id), (x, y - 40), font, 2, (255, 255, 255), 3)
cv2.putText(im, 'Press q to end AMS!', (10, 460), font, 1, (255, 255, 255), 2)
# Display the video frame with the bounded rectangle
cv2.imshow('AAPNA Attendance Monitoring System',im)
# If 'q' is pressed, close program
#if cv2.waitKey(10) & 0xFF==ord('esc'):
if cv2.waitKey(10) & 0xFF == ord('q'):
break
# Stop the camera
cam.release()
# Close all windows
cv2.destroyAllWindows()