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from sklearn.neighbors import KNeighborsClassifier
import cv2
import pickle
import numpy as np
import os
import csv
import time
from datetime import datetime
from flask import Flask, render_template, request
from win32com.client import Dispatch
def speak(str1):
speak=Dispatch(("SAPI.SpVoice"))
speak.Speak(str1)
facedetect=cv2.CascadeClassifier('data/haarcascade_frontalface_default.xml')
with open('data/names.pkl', 'rb') as w:
LABELS=pickle.load(w)
with open('data/faces_data.pkl', 'rb') as f:
FACES=pickle.load(f)
# print('Shape of Faces matrix --> ', FACES.shape)
knn=KNeighborsClassifier(n_neighbors=5)
knn.fit(FACES, LABELS)
COL_NAMES = ['NAME', 'TIME']
# def take_attendence():
# ret,frame=video.read()
# gray=cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# faces=facedetect.detectMultiScale(gray, 1.3 ,5)
# for (x,y,w,h) in faces:
# crop_img=frame[y:y+h, x:x+w, :]
# resized_img=cv2.resize(crop_img, (50,50)).flatten().reshape(1,-1)
# output=knn.predict(resized_img)
# ts=time.time()
# date=datetime.fromtimestamp(ts).strftime("%d-%m-%Y")
# timestamp=datetime.fromtimestamp(ts).strftime("%H:%M-%S")
# exist=os.path.isfile("Attendance/Attendance_" + date + ".csv")
# cv2.rectangle(frame, (x,y), (x+w, y+h), (0,0,255), 1)
# cv2.rectangle(frame,(x,y),(x+w,y+h),(50,50,255),2)
# cv2.rectangle(frame,(x,y-40),(x+w,y),(50,50,255),-1)
# cv2.putText(frame, str(output[0]), (x,y-15), cv2.FONT_HERSHEY_COMPLEX, 1, (255,255,255), 1)
# cv2.rectangle(frame, (x,y), (x+w, y+h), (50,50,255), 1)
# attendance=[str(output[0]), str(timestamp)]
# speak("Attendance Taken..")
# if exist:
# with open("Attendance/Attendance_" + date + ".csv", "+a") as csvfile:
# writer=csv.writer(csvfile)
# writer.writerow(attendance)
# csvfile.close()
# else:
# with open("Attendance/Attendance_" + date + ".csv", "+a") as csvfile:
# writer=csv.writer(csvfile)
# writer.writerow(COL_NAMES)
# writer.writerow(attendance)
# csvfile.close()
# # if k==ord('q'):
# # break
# # video.release()
# # cv2.destroyAllWindows()
app = Flask(__name__)
@app.route('/')
def index():
return render_template('index.html')
@app.route('/atten')
def atten():
return render_template('atten.html')
@app.route('/take_attendance', methods=['POST'])
def take_attendance():
video=cv2.VideoCapture(0)
ret, frame = video.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = facedetect.detectMultiScale(gray, 1.3, 5)
for (x,y,w,h) in faces:
crop_img=frame[y:y+h, x:x+w, :]
resized_img=cv2.resize(crop_img, (50,50)).flatten().reshape(1,-1)
output=knn.predict(resized_img)
ts=time.time()
date=datetime.fromtimestamp(ts).strftime("%d-%m-%Y")
timestamp=datetime.fromtimestamp(ts).strftime("%H:%M-%S")
exist=os.path.isfile("Attendance/Attendance_" + date + ".csv")
cv2.rectangle(frame, (x,y), (x+w, y+h), (0,0,255), 1)
cv2.rectangle(frame,(x,y),(x+w,y+h),(50,50,255),2)
cv2.rectangle(frame,(x,y-40),(x+w,y),(50,50,255),-1)
cv2.putText(frame, str(output[0]), (x,y-15), cv2.FONT_HERSHEY_COMPLEX, 1, (255,255,255), 1)
cv2.rectangle(frame, (x,y), (x+w, y+h), (50,50,255), 1)
attendance=[str(output[0]), str(timestamp)]
speak("Attendance Taken..")
if exist:
with open("Attendance/Attendance_" + date + ".csv", "+a") as csvfile:
writer=csv.writer(csvfile)
writer.writerow(attendance)
csvfile.close()
else:
with open("Attendance/Attendance_" + date + ".csv", "+a") as csvfile:
writer=csv.writer(csvfile)
writer.writerow(COL_NAMES)
writer.writerow(attendance)
csvfile.close()
video.release()
return "Attendance taken successfully!"
if __name__ == '__main__':
app.run(debug=True) |