import gradio as gr
import cv2
import numpy as np
import face_recognition
import os
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 findEncoding(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)
        
        
    return gray
    
iface = gr.Interface(
fn=greet, 
inputs=gr.Video(source = "webcam", format = "mp4", streaming = "True"),  
outputs="image"
)

iface.launch()