Update DataExtraction.py

DataExtraction.py

@@ -1,75 +1,75 @@
-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)
+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)