import streamlit as st
import PyPDF2
from PIL import Image, ExifTags
import pytesseract
import hashlib
import cv2
import numpy as np
import io

# Set up Streamlit app title
st.title("DocuVerify - Advanced Document Authentication")

# File uploader
uploaded_file = st.file_uploader("Upload a PDF or Image file", type=["pdf", "jpg", "jpeg", "png", "gif"])

def compute_hash(file):
    hasher = hashlib.sha256()
    file.seek(0)
    hasher.update(file.read())
    return hasher.hexdigest()

def extract_text_from_image(image):
    return pytesseract.image_to_string(image)

def analyze_pdf(file):
    try:
        reader = PyPDF2.PdfReader(file)
        info = reader.metadata
        text = ""
        for page in reader.pages:
            text += page.extract_text() or ""
        
        st.subheader("PDF Metadata")
        if info:
            for key, value in info.items():
                st.write(f"{key}: {value}")
        else:
            st.write("No metadata found.")
        
        st.subheader("Extracted Text from PDF")
        st.text_area("Extracted Text", text[:10000])  # Display first 10000 chars

        file_hash = compute_hash(file)
        st.write(f"File Integrity Hash (SHA-256): {file_hash}")
        
        if info and info.get('/Producer') and info.get('/CreationDate'):
            return "Legit"
        else:
            return "Forged (Missing key metadata)"
    except Exception as e:
        st.write(f"Error analyzing PDF: {str(e)}")
        return "Forged (Error reading PDF)"

def analyze_image(file):
    try:
        img = Image.open(file)
        exif_data = img._getexif()
        
        st.subheader("Image Metadata")
        if exif_data:
            for tag, value in exif_data.items():
                tag_name = ExifTags.TAGS.get(tag, tag)
                st.write(f"{tag_name}: {value}")
        else:
            st.write("No EXIF metadata found.")
        
        text = extract_text_from_image(img)
        st.subheader("Extracted Text from Image")
        st.text_area("Extracted Text", text[:1000])
        
        file_hash = compute_hash(file)
        st.write(f"File Integrity Hash (SHA-256): {file_hash}")
        
        img_cv = cv2.cvtColor(np.array(img), cv2.COLOR_RGB2BGR)
        gray = cv2.cvtColor(img_cv, cv2.COLOR_BGR2GRAY)
        edges = cv2.Canny(gray, 50, 150)
        
        st.subheader("Edge Detection Preview")
        st.image(edges, caption="Edges Detected", use_column_width=True, channels="GRAY")
        
        if exif_data:
            return "Legit"
        else:
            return "Forged (No EXIF metadata)"
    except Exception as e:
        st.write(f"Error analyzing image: {str(e)}")
        return "Forged (Error processing image)"

# Analyze uploaded file
if uploaded_file is not None:
    file_extension = uploaded_file.name.split(".")[-1].lower()
    
    if file_extension == "pdf":
        st.write("Analyzing PDF file...")
        status = analyze_pdf(uploaded_file)
    elif file_extension in ["jpg", "jpeg", "png", "gif"]:
        st.write("Analyzing Image file...")
        status = analyze_image(uploaded_file)
    else:
        st.write("Unsupported file format.")
        status = "Unsupported Format"
    
    st.subheader("Final Status: ")
    st.write(f"**{status}**")
else:
    st.write("Please upload a PDF or Image file to analyze.")