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)