import gradio as gr
import cv2
import numpy as np
import face_recognition
import os
import sys
from pathlib import Path
from datetime import datetime


def greet(video):
    path = "ImagesAttendance"
    images = []
    classNames = []
    myList = os.listdir(path)
    print(myList)
    for cl in myList:
        curImg = cv2.imread(f'{path}/{cl}')
        images.append(curImg)
        classNames.append(os.path.splitext(cl)[0])
    print(classNames)

    def findEncodings(images):
        encodeList = []
        for img in images:
            img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
            encode = face_recognition.face_encodings(img)[0]
            encodeList.append(encode)
        return encodeList

    def markAttendance(name):
        with open('Attendance.csv', 'r+') as f:
            myDataList = f.readlines()
            nameList = []
            for line in myDataList:
                entry = line.split(',')
                nameList.append(entry[0])
            if name not in nameList:
                now = datetime.now()
                dtString = now.strftime('%H:%M:%S')
                f.writelinbes(f'\n{name},{dtString}')
    encodeListKnown = findEncodings(images)
    print('Encoding Complete')

    cap = cv2.VideoCapture(video)

    while True:
        succes, img = cap.read()
        imgS = cv2.resize(img, (0, 0), None, 0.25, 0.25)
        imgS = cv2.cvtColor(imgS, cv2.COLOR_BGR2GRAY)

        facesCurFrame = face_recognition.face_locations(imgS)
        encodesCurFrame = face_recognition.face_encodings(imgS, facesCurFrame)

        for encodeFace, faceLoc in zip(encodesCurFrame, facesCurFrame):
            matches = face_recognition.compare_faces(
                encodeListKnown, encodeFace)
            faceDis = face_recognition.face_distance(
                encodeListKnown, encodeFace)
            matchIndex = np.argmin(faceDis)

        if matches[matchIndex]:
            name = classNames[matchIndex].upper()
            y1, x2, y2, x1 = faceLoc
            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.FILED)
            cv2.putText(img, name, (x1+6, y2-6),
                        cv2.FONT_HERSHEY_COMPLEX, 1, (255, 255, 255), 2)
            markAttendance(name)
        cv2.imshow('Webcam', img)
        cv2.waitKey(1)


iface = gr.Interface(
    fn=greet,
    inputs=gr.Video(source="webcam", format="mp4", streaming="True"),
    outputs="image"
)

iface.launch()