import cv2

import face_recognition

import os

import numpy as np

from datetime import datetime

import pickle

import pandas as pd

path = 'images'

images = []

classNames = []

mylist = os.listdir(path)

for cl in mylist:

    curImg = cv2.imread(f'{path}/{cl}')

    images.append(curImg)

    classNames.append(os.path.splitext(cl)[0])

def findEncodings(images):

    encodeList = []

    for img in images:

        img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)

        encoded_face = face_recognition.face_encodings(img)[0]

        encodeList.append(encoded_face)

    return encodeList

encoded_face_train = findEncodings(images)

def markAttendance(name):

    with open('Attendance.csv','r+') as f:

        next(f)

        myDataList = f.readlines()

        entryExisted = []

        now = datetime.now()

        todayDate = now.strftime('%d-%B-%Y')

        #print(myDataList);

#['deepak, 09:19:42:PM, 08-March-2025\n', 'nl1, 09:25:18:PM, 08-March-2025\n']

        for row in myDataList:

            col = row.split(',')

            entryExisted.append(col[0].strip()+"~"+col[2].strip())

            #print(entryExisted)

            newEntry=name+"~"+todayDate

            #print(newEntry,entryExisted)

        if  newEntry not in entryExisted:

            time = now.strftime('%I:%M:%S:%p')

            f.writelines(f'{name}, {time}, {todayDate}')

            f.writelines("\n")

        #['name,attendance,\n', 'ndeepak, 08:38:06:PM, 08-March-2025ndeepak\n']

# take pictures from webcam 

cap  = cv2.VideoCapture(0)

while True:

    success, img = cap.read()

    imgS = cv2.resize(img, (0,0), None, 0.25,0.25)

    imgS = cv2.cvtColor(imgS, cv2.COLOR_BGR2RGB)

    faces_in_frame = face_recognition.face_locations(imgS)

    encoded_faces = face_recognition.face_encodings(imgS, faces_in_frame)

    for encode_face, faceloc in zip(encoded_faces,faces_in_frame):

        matches = face_recognition.compare_faces(encoded_face_train, encode_face)

        faceDist = face_recognition.face_distance(encoded_face_train, encode_face)

        matchIndex = np.argmin(faceDist)

        print(matchIndex)

        if matches[matchIndex]:

            name = classNames[matchIndex].upper().lower()

            y1,x2,y2,x1 = faceloc

            # since we scaled down by 4 times

            y1, x2,y2,x1 = y1*4,x2*4,y2*4,x1*4

            cv2.rectangle(img,(x1,y1),(x2,y2),(0,255,0),2)

            cv2.rectangle(img, (x1,y2-35),(x2,y2), (0,255,0), cv2.FILLED)

            cv2.putText(img,name, (x1+6,y2-5), cv2.FONT_HERSHEY_COMPLEX,1,(255,255,255),2)

            markAttendance(name)

    cv2.imshow('webcam', img)

    if cv2.waitKey(1) & 0xFF == ord('q'):

        break