detect.py

import cv2
from ultralytics import YOLO

# Load the YOLOv8 model
model = YOLO('best.pt')
print(model.model.names)

# Open the video file
video_path = "Samples/tracking.mp4"
cap = cv2.VideoCapture(video_path)

# Loop through the video frames
while cap.isOpened():
    # Read a frame from the video
    success, frame = cap.read()
    if success:
        # Run YOLOv8 tracking on the frame, persisting tracks between frames
        results = model.predict(frame,conf = 0.5)
        # print(results[0].boxes.xyxy)
        bbox_data = results[0].boxes.xyxy.cpu().numpy()
        print(bbox_data)
        # print(results[0].plot())
        # Visualize the results on the frame
        annotated_frame = results[0].plot()

        # Display the annotated frame
        cv2.imshow("YOLOv8 Tracking", annotated_frame)

        # Break the loop if 'q' is pressed
        if cv2.waitKey(1) & 0xFF == ord("q"):
            break
    else:
        # Break the loop if the end of the video is reached
        break

# Release the video capture object and close the display window
cap.release()
cv2.destroyAllWindows()