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

p1 = "raavi.jpg"
p2 = "jivan.jpg"

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

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

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

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

# take  image from user  
# Take picture using the camera 
img_file_buffer = st.camera_input("Take a 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)
        
    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
            if not image.flags.writeable:
              image.setflags(write=True)
            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)

            # display_image_with_overlay(image, name)
            st.image(image , use_column_width=True, output_format="PNG")
            faceMatchedflag = 1
            
    if(faceMatchedflag == 0) : 
        st.warning("No faces detected in the image.")