Uploaded Projec Files

DataExtraction.py

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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", type=["jpg", "jpeg", "png"])
+
+    if uploaded_file is not None:
+        image = Image.open(uploaded_file)
+        st.image(image, caption='Uploaded Image', 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)

Home.py

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+import streamlit as st
+
+def home_page():
+    st.title("eKYC using Computer Vision")
+    st.write("""
+        Welcome to the eKYC application! This project consists of two main modules:
+        1. **Data Extraction**: Upload an image of a CNIC card to extract data.
+        2. **Face Comparison**: Upload an image of a CNIC card and another image of the person to verify if they match.
+    """)

app.py

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+import streamlit as st
+from Home import home_page
+from DataExtraction import data_extraction_page
+from FaceComparison import face_comparison_page
+
+PAGES = {
+    "Home": home_page,
+    "Data Extraction": data_extraction_page,
+    "Face Comparison": face_comparison_page
+}
+
+st.sidebar.title('Navigation')
+selection = st.sidebar.radio("Go to", list(PAGES.keys()))
+
+page = PAGES[selection]
+page()

compare_faces.py

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+from deepface import DeepFace
+
+def compare_faces(id_card_image_path, face_image_path):
+    result = DeepFace.verify(id_card_image_path, face_image_path)
+    return "Match" if result["verified"] else "No Match"

face_comparison.py

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+import streamlit as st
+from PIL import Image
+from compare_faces import compare_faces
+import tempfile
+
+def face_comparison_page():
+    st.title("ID Card and Face Verification")
+
+    id_card_image = st.file_uploader("Upload your ID card image", type=["jpg", "jpeg", "png"])
+    face_image = st.file_uploader("Upload your face image", type=["jpg", "jpeg", "png"])
+
+    if id_card_image and face_image:
+        with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as id_temp:
+            id_temp.write(id_card_image.read())
+            id_temp_path = id_temp.name
+        
+        with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as face_temp:
+            face_temp.write(face_image.read())
+            face_temp_path = face_temp.name
+
+        result = compare_faces(id_temp_path, face_temp_path)
+        st.write(result)

requirements.txt

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+streamlit
+deepface
+easyocr
+pillow
+numpy
+pandas
+mysql-connector-python