Update app.py

app.py

@@ -1,61 +1,94 @@
 import streamlit as st
 import pandas as pd
+import cv2
+import easyocr
+import tempfile
+import requests
+import os
 from datetime import datetime
-import smtplib
-from email.message import EmailMessage
-
-# Set email credentials and receiver
-EMAIL_SENDER = st.secrets.get("EMAIL_SENDER", "your_email@example.com")
-EMAIL_PASSWORD = st.secrets.get("EMAIL_PASSWORD", "your_app_password")
-EMAIL_RECEIVER = st.secrets.get("EMAIL_RECEIVER", "receiver@example.com")
-
-def send_email_alert(vehicle_number, duration_hours):
-    msg = EmailMessage()
-    msg['Subject'] = f'🚨 Alert: Vehicle {vehicle_number} > 24 hrs'
-    msg['From'] = EMAIL_SENDER
-    msg['To'] = EMAIL_RECEIVER
-    msg.set_content(f"Vehicle {vehicle_number} has been inside for {duration_hours:.2f} hours.")
-
-    try:
-        with smtplib.SMTP_SSL('smtp.gmail.com', 465) as smtp:
-            smtp.login(EMAIL_SENDER, EMAIL_PASSWORD)
-            smtp.send_message(msg)
-        return True
-    except Exception as e:
-        st.error(f"Email sending failed: {e}")
-        return False
-
-st.title("🚗 Vehicle Entry Monitoring")
-
-uploaded_file = st.file_uploader("Upload Excel File", type=["xlsx"])
-
-if uploaded_file:
-    try:
-        df = pd.read_excel(uploaded_file)
-
-        required_cols = ['Vehicle Number', 'Entry Time', 'Exit Time']
-        if not all(col in df.columns for col in required_cols):
-            st.error(f"Missing required columns. Must include: {required_cols}")
+from urllib.parse import urlparse, parse_qs
+
+# CONFIG
+API_KEY = st.secrets.get("GDRIVE_API_KEY", "your_google_api_key")
+FOLDER_ID = st.text_input("🔗 Google Drive Folder ID", "")
+
+LOG_FILE = "vehicle_log.csv"
+FRAME_SKIP = 30
+
+reader = easyocr.Reader(['en'], gpu=False)
+
+# Ensure log file
+if not os.path.exists(LOG_FILE):
+    pd.DataFrame(columns=["Vehicle Number", "Timestamp", "Video File"]).to_csv(LOG_FILE, index=False)
+
+def list_drive_files(folder_id):
+    url = f"https://www.googleapis.com/drive/v3/files?q='{folder_id}'+in+parents+and+(mimeType='video/mp4'+or+mimeType='video/avi')&key={API_KEY}&fields=files(id,name)"
+    resp = requests.get(url)
+    if resp.status_code != 200:
+        st.error(f"Drive API Error: {resp.text}")
+        return []
+    return resp.json().get("files", [])
+
+def download_drive_video(file_id):
+    download_url = f"https://www.googleapis.com/drive/v3/files/{file_id}?alt=media&key={API_KEY}"
+    resp = requests.get(download_url, stream=True)
+    if resp.status_code != 200:
+        return None
+    temp = tempfile.NamedTemporaryFile(delete=False, suffix=".mp4")
+    for chunk in resp.iter_content(chunk_size=8192):
+        if chunk:
+            temp.write(chunk)
+    temp.close()
+    return temp.name
+
+def process_video(video_path, video_name, logged_plates):
+    cap = cv2.VideoCapture(video_path)
+    frame_num = 0
+    new_logs = []
+
+    while cap.isOpened():
+        ret, frame = cap.read()
+        if not ret:
+            break
+        if frame_num % FRAME_SKIP == 0:
+            gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+            results = reader.readtext(gray)
+            for (_, text, _) in results:
+                text = text.replace(" ", "").upper()
+                if len(text) >= 6 and any(char.isdigit() for char in text) and text not in logged_plates:
+                    timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+                    new_logs.append([text, timestamp, video_name])
+                    logged_plates.add(text)
+                    st.success(f"Detected: {text} at {timestamp}")
+        frame_num += 1
+    cap.release()
+    return new_logs
+
+st.title("🚓 Vehicle Number Detection from Google Drive CCTV")
+
+if FOLDER_ID:
+    files = list_drive_files(FOLDER_ID)
+    if not files:
+        st.warning("No video files found in the folder.")
+    else:
+        log_df = pd.read_csv(LOG_FILE)
+        logged_plates = set(log_df["Vehicle Number"])
+        all_new_logs = []
+
+        for file in files:
+            st.info(f"Processing: {file['name']}")
+            local_path = download_drive_video(file['id'])
+            if local_path:
+                new_logs = process_video(local_path, file['name'], logged_plates)
+                all_new_logs.extend(new_logs)
+                os.remove(local_path)
+
+        if all_new_logs:
+            pd.DataFrame(all_new_logs, columns=["Vehicle Number", "Timestamp", "Video File"]).to_csv(LOG_FILE, mode='a', index=False, header=False)
+            st.success("✅ Logs updated.")
         else:
-            df['Entry Time'] = pd.to_datetime(df['Entry Time'])
-            df['Exit Time'] = pd.to_datetime(df['Exit Time'])
-            df['Duration (Hours)'] = (df['Exit Time'] - df['Entry Time']).dt.total_seconds() / 3600
-
-            st.subheader("📋 Full Log")
-            st.dataframe(df)
-
-            over_24 = df[df['Duration (Hours)'] > 24]
-
-            if not over_24.empty:
-                st.subheader("⚠️ Vehicles > 24 Hours")
-                st.dataframe(over_24)
-
-                if st.button("Send Email Alerts"):
-                    for _, row in over_24.iterrows():
-                        success = send_email_alert(row['Vehicle Number'], row['Duration (Hours)'])
-                        if success:
-                            st.success(f"Alert sent for {row['Vehicle Number']}")
-            else:
-                st.info("✅ No vehicles exceeding 24-hour duration.")
-    except Exception as e:
-        st.error(f"Failed to process file: {e}")
+            st.info("No new vehicles detected.")
+
+    if os.path.exists(LOG_FILE):
+        st.subheader("📄 Vehicle Entry Log")
+        st.dataframe(pd.read_csv(LOG_FILE))