Python: Detecting the Vehicle on the real-time footage

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#!/usr/bin/env python3 """ Vehicle Detector with Timestamp Logging Enhanced version: Logs timestamps for each vehicle and saves to daily log files """ import cv2 import numpy as np from picamera2 import Picamera2 import time import os from datetime import datetime, timedelta import json class VehicleDetectorLogger: def __init__(self): # Create log directory self.log_dir = "vehicle_logs" os.makedirs(self.log_dir, exist_ok=True) # Current log file self.current_log_date = datetime.now().date() self.log_file = self.get_log_file_path() # Initialize statistics self.vehicle_count = 0 self.vehicle_records = [] # Store all vehicle records self.daily_stats = self.load_daily_stats() # Detection parameters self.last_count_time = time.time() self.frame_count = 0 self.start_time = time.time() # Initialize camera print("Initializing camera...") self.picam2 = Picamera2() config = self.picam2.create_video_configuration( main={"size": (640, 480), "format": "RGB888"} ) self.picam2.configure(config) # Background subtractor self.fgbg = cv2.createBackgroundSubtractorMOG2(history=50, varThreshold=25) print("System ready!") print(f"Log file: {self.log_file}") print("-" * 50) def get_log_file_path(self): """Get log file path for current date""" date_str = datetime.now().strftime("%Y%m%d") return os.path.join(self.log_dir, f"vehicles_{date_str}.txt") def load_daily_stats(self): """Load daily statistics""" stats_file = os.path.join(self.log_dir, "daily_stats.json") if os.path.exists(stats_file): try: with open(stats_file, 'r') as f: stats = json.load(f) # Keep only last 7 days of data seven_days_ago = (datetime.now() - timedelta(days=7)).strftime("%Y%m%d") stats = {k: v for k, v in stats.items() if k >= seven_days_ago} return stats except: return {} return {} def save_daily_stats(self): """Save daily statistics""" stats_file = os.path.join(self.log_dir, "daily_stats.json") date_str = datetime.now().strftime("%Y%m%d") self.daily_stats[date_str] = { "total_vehicles": self.vehicle_count, "records_count": len(self.vehicle_records), "date": datetime.now().strftime("%Y-%m-%d") } with open(stats_file, 'w') as f: json.dump(self.daily_stats, f, indent=2) def log_vehicle(self, vehicle_id, timestamp, position=None): """Log vehicle detection to file""" # Check if need to switch to new day's log file current_date = datetime.now().date() if current_date != self.current_log_date: self.current_log_date = current_date self.log_file = self.get_log_file_path() print(f"New day! Switching to log file: {self.log_file}") # Format timestamp time_str = timestamp.strftime("%Y-%m-%d %H:%M:%S.%f")[:-3] # Create record record = { "id": vehicle_id, "timestamp": time_str, "unix_time": timestamp.timestamp(), "date": timestamp.strftime("%Y-%m-%d"), "time": timestamp.strftime("%H:%M:%S"), "position": position } # Add to records list self.vehicle_records.append(record) # Save to text file with open(self.log_file, 'a') as f: log_line = f"[{time_str}] Vehicle #{vehicle_id:04d} detected" if position: log_line += f" at position {position}" log_line += "\n" f.write(log_line) # Also save to JSON file (for easy analysis) json_file = self.log_file.replace('.txt', '.json') with open(json_file, 'w') as f: json.dump(self.vehicle_records, f, indent=2) # Print to console print(f"[{timestamp.strftime('%H:%M:%S')}] 🚗 Vehicle #{vehicle_id:04d} detected") return record def detect_and_count(self, frame): """Detect and count vehicles""" # Convert to grayscale gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) # Apply background subtraction fgmask = self.fgbg.apply(gray) # Morphological operations kernel = np.ones((5,5), np.uint8) fgmask = cv2.morphologyEx(fgmask, cv2.MORPH_CLOSE, kernel) fgmask = cv2.morphologyEx(fgmask, cv2.MORPH_OPEN, kernel) # Find contours contours, _ = cv2.findContours(fgmask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) detected_vehicles = [] for contour in contours: area = cv2.contourArea(contour) if area > 1000: # Only process large enough areas x, y, w, h = cv2.boundingRect(contour) # Only focus on bottom half of screen if y > 240 and w > 50 and h > 50: # Calculate center point center_x = x + w // 2 center_y = y + h // 2 # Check if new vehicle (avoid duplicate counting) current_time = time.time() if current_time - self.last_count_time > 2.0: self.vehicle_count += 1 self.last_count_time = current_time # Log vehicle timestamp = datetime.now() position = {"x": center_x, "y": center_y, "w": w, "h": h} record = self.log_vehicle(self.vehicle_count, timestamp, position) detected_vehicles.append({ "bbox": (x, y, w, h), "center": (center_x, center_y), "area": area, "record": record }) else: # Just draw, don't count detected_vehicles.append({ "bbox": (x, y, w, h), "center": (center_x, center_y), "area": area, "record": None }) return detected_vehicles, fgmask def draw_detection_info(self, frame, vehicles, fgmask): """Draw detection information on frame""" # Draw detected vehicles for vehicle in vehicles: x, y, w, h = vehicle["bbox"] center_x, center_y = vehicle["center"] # Draw bounding box color = (0, 255, 0) if vehicle["record"] else (0, 200, 200) thickness = 2 if vehicle["record"] else 1 cv2.rectangle(frame, (x, y), (x + w, y + h), color, thickness) # Draw center point cv2.circle(frame, (center_x, center_y), 4, (0, 0, 255), -1) # If counted vehicle, show ID if vehicle["record"]: cv2.putText(frame, f"#{vehicle['record']['id']}", (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 2) # Draw detection line detection_line_y = 320 cv2.line(frame, (0, detection_line_y), (640, detection_line_y), (0, 255, 255), 2) cv2.putText(frame, "Detection Line", (10, detection_line_y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 255), 1) # Display statistics stats_y = 30 cv2.putText(frame, f"Vehicles: {self.vehicle_count}", (10, stats_y), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2) # Display FPS self.frame_count += 1 if self.frame_count % 30 == 0: fps = self.frame_count / (time.time() - self.start_time) cv2.putText(frame, f"FPS: {fps:.1f}", (10, stats_y + 40), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 255, 0), 2) # Display current time current_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S") cv2.putText(frame, current_time, (350, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 255, 255), 2) # Display today's date date_str = datetime.now().strftime("%Y-%m-%d") cv2.putText(frame, f"Today: {date_str}", (350, 70), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 255, 255), 2) # Display log status log_status = f"Log: {os.path.basename(self.log_file)}" cv2.putText(frame, log_status, (10, stats_y + 80), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (200, 200, 255), 1) return frame def generate_daily_report(self): """Generate daily report""" if not self.vehicle_records: return # Count by hour hourly_counts = {} for record in self.vehicle_records: hour = datetime.fromtimestamp(record["unix_time"]).strftime("%H:00") hourly_counts[hour] = hourly_counts.get(hour, 0) + 1 # Generate report file report_file = self.log_file.replace('.txt', '_report.txt') with open(report_file, 'w') as f: f.write("=" * 60 + "\n") f.write(f"Daily Vehicle Detection Report\n") f.write(f"Date: {datetime.now().strftime('%Y-%m-%d')}\n") f.write("=" * 60 + "\n\n") f.write(f"Total Vehicles Detected: {self.vehicle_count}\n") f.write(f"Detection Start Time: {datetime.fromtimestamp(self.start_time).strftime('%Y-%m-%d %H:%M:%S')}\n") f.write(f"Report Generated: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n\n") f.write("Hourly Statistics:\n") f.write("-" * 30 + "\n") for hour in sorted(hourly_counts.keys()): f.write(f"{hour}: {hourly_counts[hour]} vehicles\n") f.write("\nDetailed Records:\n") f.write("-" * 60 + "\n") for i, record in enumerate(self.vehicle_records, 1): f.write(f"{i:3d}. [{record['time']}] Vehicle #{record['id']:04d}\n") print(f"Daily report generated: {report_file}") def run(self): """Main detection loop""" print("Vehicle Detection System Starting") print("Controls:") print(" 'q' - Quit program") print(" 'r' - Reset counter") print(" 's' - Save current frame") print(" 'p' - Generate daily report") print(" '+' - Increase sensitivity") print(" '-' - Decrease sensitivity") print("-" * 50) # Start camera self.picam2.start() time.sleep(1) # Let camera stabilize try: while True: # Capture frame frame = self.picam2.capture_array() frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR) # Detect and count vehicles vehicles, fgmask = self.detect_and_count(frame) # Draw detection info frame = self.draw_detection_info(frame, vehicles, fgmask) # Display frames cv2.imshow("Vehicle Detector with Logger", frame) cv2.imshow("Motion Mask", fgmask) # Handle keyboard input key = cv2.waitKey(1) & 0xFF if key == ord('q'): print("\nQuitting program") break elif key == ord('r'): self.vehicle_count = 0 self.vehicle_records.clear() self.last_count_time = time.time() self.fgbg = cv2.createBackgroundSubtractorMOG2(history=50, varThreshold=25) print("Counter reset") elif key == ord('s'): timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") filename = f"snapshot_{timestamp}.jpg" cv2.imwrite(filename, frame) print(f"Frame saved: {filename}") elif key == ord('p'): self.generate_daily_report() elif key == ord('+'): # Increase sensitivity self.fgbg.setVarThreshold(max(10, self.fgbg.getVarThreshold() - 5)) print(f"Sensitivity increased: varThreshold={self.fgbg.getVarThreshold()}") elif key == ord('-'): # Decrease sensitivity self.fgbg.setVarThreshold(min(100, self.fgbg.getVarThreshold() + 5)) print(f"Sensitivity decreased: varThreshold={self.fgbg.getVarThreshold()}") except KeyboardInterrupt: print("\nUser interrupted") finally: # Cleanup resources self.picam2.stop() cv2.destroyAllWindows() # Save statistics self.save_daily_stats() # Generate final report self.generate_daily_report() # Output summary total_time = time.time() - self.start_time fps = self.frame_count / total_time if total_time > 0 else 0 print("\n" + "=" * 60) print("Detection System Stopped") print("=" * 60) print(f"Total Runtime: {total_time:.1f} seconds") print(f"Frames Processed: {self.frame_count}") print(f"Average FPS: {fps:.1f}") print(f"Total Vehicles Detected: {self.vehicle_count}") print(f"Log File: {self.log_file}") print(f"JSON Data: {self.log_file.replace('.txt', '.json')}") print("=" * 60) def main(): """Main function""" print("=" * 60) print("Raspberry Pi Vehicle Detection System - With Logging") print("=" * 60) # Create detector and run detector = VehicleDetectorLogger() detector.run() if __name__ == "__main__": main()