├── README.md
└── traffic.py


/README.md:
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1 | # Real-Time-Traffic-Detection-with-YOLOv8-OpenCV-CUDA-


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/traffic.py:
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 1 | from ultralytics import YOLO
 2 | import torch
 3 | import cv2
 4 | 
 5 | device = "cuda" if torch.cuda.is_available() else "cpu"
 6 | print(f"Using device: {device}")
 7 | 
 8 | model = YOLO("yolov8n.pt").to(device)
 9 | 
10 | cap = cv2.VideoCapture("traffic.mp4")
11 | 
12 | frame_width = 640
13 | frame_height = 480
14 | 
15 | while cap.isOpened():
16 |     ret, frame = cap.read()
17 |     if not ret:
18 |         break
19 | 
20 |     
21 |     frame = cv2.resize(frame, (frame_width, frame_height))
22 | 
23 |     results = model(frame, device=device)  
24 |     vehicle_count = len(results[0].boxes)
25 | 
26 |     
27 |     for r in results:
28 |         for box in r.boxes:
29 |             x1, y1, x2, y2 = map(int, box.xyxy[0])  
30 |             cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
31 | 
32 |     
33 |     cv2.putText(frame, f"Vehicles: {vehicle_count}", (20, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 255), 2)
34 | 
35 |     cv2.imshow("Traffic Detection", frame)
36 |     if cv2.waitKey(1) & 0xFF == ord("q"):
37 |         break
38 | 
39 | cap.release()
40 | cv2.destroyAllWindows()
41 | 


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