import streamlit as st
from PIL import Image, ImageDraw
import face_recognition
import numpy as np

# Load known face encodings and names
ruthchild_image = face_recognition.load_image_file("picturesofknownpeople/ruthchild.jpg")
ruthchild_face_encoding = face_recognition.face_encodings(ruthchild_image)[0]

harryking_image = face_recognition.load_image_file("picturesofknownpeople/harryking.jpg")
harryking_face_encoding = face_recognition.face_encodings(harryking_image)[0]

barackobama_image = face_recognition.load_image_file("picturesofknownpeople/barack_obama.jpg")
barackobama_face_encoding = face_recognition.face_encodings(barackobama_image)[0]

michelleobama_image = face_recognition.load_image_file("picturesofknownpeople/michelle_obama.jpg")
michelleobama_face_encoding = face_recognition.face_encodings(michelleobama_image)[0]

biden_image = face_recognition.load_image_file("picturesofknownpeople/biden.jpg")
biden_face_encoding = face_recognition.face_encodings(biden_image)[0]

known_face_encodings = [
    ruthchild_face_encoding,
    harryking_face_encoding,
    barackobama_face_encoding,
    michelleobama_face_encoding,
    biden_face_encoding
]
known_face_names = [
    "ruthchild",
    "harryking",
    "barackobama",
    "michelleobama",
    "biden"
]

def main():
    st.set_page_config(page_title="Insightly", page_icon="https://i.ibb.co/bX6GdqG/insightly-wbg.png")
    st.sidebar.image("https://i.ibb.co/bX6GdqG/insightly-wbg.png", use_column_width=True)
    st.title("Face Recognition with Streamlit")
    
    uploaded_image = st.file_uploader("Upload an image", type=["jpg", "png", "jpeg"])
    
    if uploaded_image is not None:
        unknown_image = face_recognition.load_image_file(uploaded_image)

        # Find faces in the uploaded image
        face_locations = face_recognition.face_locations(unknown_image)
        face_encodings = face_recognition.face_encodings(unknown_image, face_locations)

        # Create a Pillow ImageDraw Draw instance to draw on the image
        pil_image = Image.fromarray(unknown_image)
        draw = ImageDraw.Draw(pil_image)

        for (top, right, bottom, left), face_encoding in zip(face_locations, face_encodings):
            matches = face_recognition.compare_faces(known_face_encodings, face_encoding)

            name = "Unknown"
            face_distances = face_recognition.face_distance(known_face_encodings, face_encoding)
            best_match_index = np.argmin(face_distances)

            if matches[best_match_index]:
                name = known_face_names[best_match_index]

            # Draw a box and label on the image
            draw.rectangle(((left, top), (right, bottom)), outline=(0, 0, 255))
            text_width, text_height = draw.textsize(name)
            draw.rectangle(((left, bottom - text_height - 10), (right, bottom)), fill=(0, 0, 255), outline=(0, 0, 255))
            draw.text((left + 6, bottom - text_height - 5), name, fill=(255, 255, 255, 255))

        st.image(pil_image, caption="Processed Image", use_column_width=True)

if __name__ == "__main__":
    main()