Ultralytics YOLOv8 🚀을 사용한 대기열 관리

import cv2
from ultralytics import YOLO
from ultralytics.solutions import queue_management

model = YOLO("yolov8n.pt")
cap = cv2.VideoCapture("path/to/video/file.mp4")

assert cap.isOpened(), "Error reading video file"
w, h, fps = (int(cap.get(x)) for x in (cv2.CAP_PROP_FRAME_WIDTH,
                                       cv2.CAP_PROP_FRAME_HEIGHT,
                                       cv2.CAP_PROP_FPS))

video_writer = cv2.VideoWriter("queue_management.avi",
                               cv2.VideoWriter_fourcc(*'mp4v'),
                               fps,
                               (w, h))

queue_region = [(20, 400), (1080, 404), (1080, 360), (20, 360)]

queue = queue_management.QueueManager()
queue.set_args(classes_names=model.names,
               reg_pts=queue_region,
               line_thickness=3,
               fontsize=1.0,
               region_color=(255, 144, 31))

while cap.isOpened():
    success, im0 = cap.read()

    if success:
        tracks = model.track(im0, show=False, persist=True,
                             verbose=False)
        out = queue.process_queue(im0, tracks)

        video_writer.write(im0)
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break
        continue

    print("Video frame is empty or video processing has been successfully completed.")
    break

cap.release()
cv2.destroyAllWindows()

import cv2
from ultralytics import YOLO
from ultralytics.solutions import queue_management

model = YOLO("yolov8n.pt")
cap = cv2.VideoCapture("path/to/video/file.mp4")

assert cap.isOpened(), "Error reading video file"
w, h, fps = (int(cap.get(x)) for x in (cv2.CAP_PROP_FRAME_WIDTH,
                                       cv2.CAP_PROP_FRAME_HEIGHT,
                                       cv2.CAP_PROP_FPS))

video_writer = cv2.VideoWriter("queue_management.avi",
                               cv2.VideoWriter_fourcc(*'mp4v'),
                               fps,
                               (w, h))

queue_region = [(20, 400), (1080, 404), (1080, 360), (20, 360)]

queue = queue_management.QueueManager()
queue.set_args(classes_names=model.names,
               reg_pts=queue_region,
               line_thickness=3,
               fontsize=1.0,
               region_color=(255, 144, 31))

while cap.isOpened():
    success, im0 = cap.read()

    if success:
        tracks = model.track(im0, show=False, persist=True,
                             verbose=False, classes=0)  # Only person class
        out = queue.process_queue(im0, tracks)

        video_writer.write(im0)
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break
        continue

    print("Video frame is empty or video processing has been successfully completed.")
    break

cap.release()
cv2.destroyAllWindows()