import cv2 import numpy as np from ultralytics import YOLO # Import YOLO from ultralytics package import supervision as sv from django.db import transaction from myprofile.models import * from django.core.management.base import BaseCommand from django.core.files.base import ContentFile import requests from multiprocessing import Process import datetime from django.conf import settings import time from django.db import close_old_connections def intrusion_detection(camera_id): try: close_old_connections() # Initialize the YOLOv8 model model = YOLO("yolov8n.pt") # Load YOLOv8 model from ultralytics # Open the video file camera = Camera.objects.filter(id=camera_id).first() video_path = camera.rtsp_url if camera.rtsp_url else "/home/nettyfy/visnx/visnx-backend/Nettyfy_visnx/videos/danger_test.mp4" cap = cv2.VideoCapture(video_path) # Check if the video capture object is opened successfully if not cap.isOpened(): print("Error: Could not open video.") return # output_video_path = "/home/nettyfy/visnx/visnx-backend/Nettyfy_visnx/videos/danger_output.mp4" # Get ROI coordinates classes = ['person'] roi_objs = Roi.objects.filter(camera=camera) roi_coords_list = [np.array(roi_obj.coordinates['coordinates'], dtype=np.int32) for roi_obj in roi_objs] start_time = datetime.datetime.strptime("08:00", "%H:%M").time() end_time = datetime.datetime.strptime("17:00", "%H:%M").time() current_time_user = datetime.datetime.strptime("19:00", "%H:%M").time() people_enter_queue = {} skip_frames = 15 frame_skip_counter = 0 frame_count = 0 while cap.isOpened(): ret, frame = cap.read() if not ret: break frame_skip_counter += 1 if frame_skip_counter <= skip_frames: continue frame_skip_counter = 0 # Resize the frame to (1000, 700) frame = cv2.resize(frame, (1200, 700)) # Annotate the frame with ROI annotated_frame = frame.copy() for roi_coords in roi_coords_list: cv2.drawContours(annotated_frame, [roi_coords], -1, (255, 255, 0), 2) # Run YOLOv8 tracking on the frame results = model(annotated_frame) # Your existing detection logic here... for result in results: class_label = "" x1, y1, x2, y2, conf, class_idx = result.boxes.data.tolist()[0] class_idx = int(class_idx) if class_idx == 0: class_label = classes[class_idx] if class_label == "person": # Create a new person object with an empty labels set person = {"bbox": (x1, y1, x2, y2)} x1, y1, x2, y2 = person["bbox"] corners = [(x1, y1), (x1, y2), (x2, y1), (x2, y2)] def extract_bounding_box(corners): # Extract x and y coordinates x_coords = [point[0] for point in corners] y_coords = [point[1] for point in corners] # Determine the bounding box x1, y1 = min(x_coords), min(y_coords) x2, y2 = max(x_coords), max(y_coords) return x1, y1, x2, y2 def do_rois_interact(roi1_corners, roi2_coords): # Extract bounding boxes x1_A, y1_A, x2_A, y2_A = extract_bounding_box(roi1_corners) # Convert roi2_coords to a format suitable for bounding box extraction roi2_corners = [(x, y) for x, y in roi2_coords] x1_B, y1_B, x2_B, y2_B = extract_bounding_box(roi2_corners) # Check for overlap in 2D if (x1_A < x2_B and x2_A > x1_B and y1_A < y2_B and y2_A > y1_B): return True else: return False if do_rois_interact(corners, roi_coords_list[0]): if start_time < current_time_user < end_time: # cv2.putText(annotated_frame, "Intrusion Detected", (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2) cv2.rectangle(annotated_frame, (int(x1), int(y1)), (int(x2), int(y2)), (0, 255, 0), 2) # Draw the person bbox else: cv2.rectangle(annotated_frame, (int(x1), int(y1)), (int(x2), int(y2)), (0, 0, 255), 2) # Draw the person bbox cv2.putText(annotated_frame, "Intrusion Detected", (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2) org_obj = Organization.objects.all().first() loc_obj = Location.objects.filter(loc_name = camera.location.loc_name).first() if camera.location else '' area_obj = Area.objects.filter(area_name = camera.area.area_name).first() if camera.area else '' camera_event_obj = CameraEvent.objects.filter(camera_event='IntrusionDetected').first() _, encoded_frame = cv2.imencode('.jpg', annotated_frame, [int(cv2.IMWRITE_JPEG_QUALITY), 80]) image_file = ContentFile(encoded_frame.tobytes(), name="alert_image.jpg") alert = Alert( organization = org_obj, camera=camera, detection_choice='', alert_message=f"Intrusion detected", frame=image_file, camera_events=camera_event_obj ) if area_obj: alert.area = area_obj if loc_obj: alert.location = loc_obj alert.save() camera_incharge_list = Camera.objects.get(id=camera_id).camera_user.all() for user in camera_incharge_list: alert.camera_incharge.add(user) alert.save() # Define the API endpoint url = settings.URL+'/alert_image_upload' # Create a dictionary with the file files = {'image': (alert.frame.name.replace('alert_images/', ''), encoded_frame)} # Make the request response = requests.post(url, files=files) # Print the response print(response.json()) # cv2.imshow("Annotated Frame", annotated_frame) # if cv2.waitKey(1) & 0xFF == ord('q'): # break frame_count += 1 cap.release() # cv2.destroyAllWindows() # print(f"Output video saved at: {output_video_path}") finally: # Explicitly close the database connection for the current process close_old_connections() class Command(BaseCommand): help = 'Queue detection based on video analysis' def handle(self, *args, **options): while True: # Loop indefinitely close_old_connections() # Close old database connections before starting new processes cameras = Camera.objects.filter(is_enabled=True).order_by('created_at') processes = [] # Keep track of the processes so we can terminate them later. try: for device in cameras: print(f"devices: {device.id}") # Start a new process for each device. process = Process(target=intrusion_detection, args=(device.id,)) processes.append(process) process.start() print(f"Started {len(processes)} processes.") # Let the processes run for 10 seconds time.sleep(300) except Exception as e: print(f"Error occurred: {str(e)}") finally: # Terminate all the processes after 10 seconds for process in processes: if process.is_alive(): process.terminate() # Terminate the process process.join() # Ensure the process has finished print(f"Terminated process for camera {device.id}") print("Restarting processes...") # Wait briefly before restarting to ensure all processes are fully terminated time.sleep(2)