####### Section 1 ###################
from PIL import Image
import numpy as np
import cv2
import requests
import face_recognition
import os
import streamlit as st
import urllib.request

####### Section 2 ###################
p1 = "sarwan.jpg"
p2 = "rattantata.png"
p3 = "Ravinder.jpg"

st.title("Face Recognition ")
Images     = []
classnames = []

#read images and train the face_recognition package
img1 = cv2.imread(p1)
Images.append(img1)
classnames.append("Sarwan")

img2 = cv2.imread(p2)
Images.append(img2)
classnames.append("RattanTata")

img3 = cv2.imread(p3)
Images.append(img3)
classnames.append("RavinderKaur")

directory = "facerecognition"
myList = os.listdir(directory)


for cls in myList:
    if os.path.splitext(cls)[1] in [".jpg", ".jpeg",".png"]:
        img_path = os.path.join(directory, cls)
        curImg = cv2.imread(img_path)
        Images.append(curImg)
        classnames.append(os.path.splitext(cls)[0])


# Load images for face recognition
encodeListknown = [face_recognition.face_encodings(img)[0] for img in Images]


####### Section 3 ################### 
# Take picture using the camera 
img_file_buffer = st.camera_input("Take Your picture")

# recognise the face in the uploaded image 
if img_file_buffer is not None:
    test_image = Image.open(img_file_buffer)
    image  = np.asarray(test_image)
    image = image.copy()
    
    imgS = cv2.resize(image, (0, 0), None, 0.25, 0.25)
    imgS = cv2.cvtColor(imgS, cv2.COLOR_BGR2RGB)
    facesCurFrame   = face_recognition.face_locations(imgS)
    encodesCurFrame = face_recognition.face_encodings(imgS, facesCurFrame)
    faceMatchedflag = 0
    # run looop to find match in encodeListknown  list
    for encodeFace, faceLoc in zip(encodesCurFrame, facesCurFrame):
        # Assuming that encodeListknown is defined and populated in your code
        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)
            # show the name on image to user 
            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 website 
            # using Get Method 
            # Construct the URL
            url = "https://fc11.glitch.me/submit?email=pm&message=faceReco&name="
            url = url + name
            st.write("Constructed URL:", url)
            
            # Try to send the request and handle errors
            # try:
            #     res = urllib.request.urlopen(url)
            #     response = requests.post(url)
            #     st.write("Data updated successfully.")
            # except urllib.error.URLError as e:
            #     st.error(f"Failed to open URL: {e}")
            # except requests.exceptions.RequestException as e:
            #     st.error(f"Request failed: {e}")

            url  = "https://fc11.glitch.me/submit?email=pm&message=faceReco&name="
            url = url + name
            st.write(url)
            res = urllib.request.urlopen(url)
            response = requests.post(url )

            # # using post method
            # url = "https://aimljul24f.glitch.me/submit?email=pm&message=faceReco&name="
            # url1 = "/save"
            # data = {'rollno': '99','name': name, 'email': 'p@g.com','pwd': '**'  }
            # response = requests.post(url +url1 , data=data)
            # if response.status_code == 200:
            #     st.success("Data updated on: " + "https://aimljul24f.glitch.me/")
            # else:
            #     st.warning("Data not updated")
            ########### end update website 
            faceMatchedflag = 1
     
    st.image(image , use_column_width=True, output_format="PNG")       
            
    if(faceMatchedflag == 0) : 
        st.warning("No faces detected in the image.")