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import streamlit as st
from PIL import Image
import numpy as np
import easyocr
import pandas as pd
import base64
import re
from datetime import datetime, timedelta
def process_image(image):
reader = easyocr.Reader(['en'], gpu=False)
img_np = np.array(image)
result = reader.readtext(img_np)
extracted_data = {
"Name": None,
"Father Name": None,
"Gender": None,
"Country of Stay": "Pakistan",
"Identity Number": None,
"Date of Birth": None,
"Date of Issue": None,
"Date of Expiry": None
}
for i, detection in enumerate(result):
text = detection[1].strip()
if "name" in text.lower() and not "father" in text.lower():
extracted_data["Name"] = result[i+1][1].strip() if i+1 < len(result) else None
elif "father" in text.lower():
extracted_data["Father Name"] = result[i+1][1].strip() if i+1 < len(result) else None
elif text.lower() in ["m", "f"]:
extracted_data["Gender"] = text.upper()
elif re.match(r'\d{5}-\d{7}-\d', text):
extracted_data["Identity Number"] = text
elif re.match(r'\d{2}\.\d{2}\.\d{4}', text):
if extracted_data["Date of Birth"] is None:
extracted_data["Date of Birth"] = text
elif extracted_data["Date of Issue"] is None:
extracted_data["Date of Issue"] = text
if extracted_data["Date of Issue"] and not extracted_data["Date of Expiry"]:
try:
date_of_issue = datetime.strptime(extracted_data["Date of Issue"], "%d.%m.%Y")
date_of_expiry = date_of_issue.replace(year=date_of_issue.year + 10)
extracted_data["Date of Expiry"] = date_of_expiry.strftime("%d.%m.%Y")
except ValueError:
pass
return extracted_data
def display_table(extracted_data):
fields = ["Name", "Father Name", "Gender", "Country of Stay", "Identity Number", "Date of Birth", "Date of Issue", "Date of Expiry"]
values = [extracted_data[field] if extracted_data[field] else "" for field in fields]
df = pd.DataFrame(list(zip(fields, values)), columns=['Field', 'Value'])
st.dataframe(df)
def get_csv_download_link(df):
csv = df.to_csv(index=False)
b64 = base64.b64encode(csv.encode()).decode()
href = f'<a href="data:file/csv;base64,{b64}" download="extracted_data.csv">Download CSV File</a>'
return href
def data_extraction_page():
st.title('ID Card Text Extraction')
uploaded_file = st.file_uploader("Upload an image of your ID card to Extract Data", type=["jpg", "jpeg", "png"])
if uploaded_file is not None:
image = Image.open(uploaded_file)
st.image(image, caption='Wait...! We Are Extracting Data For You', use_column_width=True)
extracted_data = process_image(image)
display_table(extracted_data)
st.markdown(get_csv_download_link(pd.DataFrame(list(extracted_data.items()), columns=['Field', 'Value'])), unsafe_allow_html=True)
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