import os
import cv2
import numpy as np
from PIL import Image
import face_recognition
import streamlit as st
import requests

# Set up Streamlit
st.title("Face Recognition App")

# Load images from the current directory
Images = []
classnames = []
myList = os.listdir()
for cls in myList:
    if os.path.splitext(cls)[1] == ".jpg":
        curImg = cv2.imread(f'{cls}')
        Images.append(curImg)
        classnames.append(os.path.splitext(cls)[0])

# Function to find face encodings
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

encodeListknown = findEncodings(Images)
st.write('Encoding Complete')

# Take a picture using Streamlit camera input
img_file_buffer = st.camera_input("Take a picture")

# Check if an image was taken
if img_file_buffer is not None:
    test_image = Image.open(img_file_buffer)
    st.image(test_image, use_column_width=True)

    # Convert the image to numpy array
    image = np.asarray(test_image)

    # Resize image
    imgS = cv2.resize(image, (0, 0), None, 0.25, 0.25)
    imgS = cv2.cvtColor(imgS, cv2.COLOR_BGR2RGB)

    # Find face locations and encodings
    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()
            st.write(name)
            y1, x2, y2, x1 = faceLoc
            y1, x2, y2, x1 = y1 * 4, x2 * 4, y2 * 4, x1 * 4
            cv2.rectangle(image, (x1, y1), (x2, y2), (0, 255, 0), 2)
            cv2.rectangle(image, (x1, y2 - 35), (x2, y2), (0, 255, 0), cv2.FILLED)
            cv2.putText(image, name, (x1 + 6, y2 - 6), cv2.FONT_HERSHEY_COMPLEX, 1, (255, 255, 255), 2)

            # Update data using requests
            url = "https://rgiattendance.000webhostapp.com/update.php"
            data1 = {'name': name}
            response = requests.post(url, data=data1)

            if response.status_code == 200:
                st.write("Data updated on: " + url)
            else:
                st.write("Data NOT updated " + url)

    st.image(image)