Multi-Object Tracking

from bytetrack import BYTETracker
import cv2
from ultralytics import YOLO

# Initialize detector and tracker
detector = YOLO('yolov8x.pt')
tracker = BYTETracker(
    track_thresh=0.5,      # High confidence threshold
    track_buffer=30,       # Frames to keep lost tracks
    match_thresh=0.8,      # IoU threshold for matching
    frame_rate=30
)

cap = cv2.VideoCapture('video.mp4')

while True:
    ret, frame = cap.read()
    if not ret:
        break

    # Get detections from YOLO
    results = detector(frame)
    detections = results[0].boxes

    # Format: [x1, y1, x2, y2, score, class]
    dets = []
    for box in detections:
        x1, y1, x2, y2 = box.xyxy[0].cpu().numpy()
        score = box.conf[0].cpu().numpy()
        cls = box.cls[0].cpu().numpy()
        dets.append([x1, y1, x2, y2, score, cls])

    # Update tracker
    tracks = tracker.update(
        np.array(dets),
        img_info=(frame.shape[0], frame.shape[1]),
        img_size=(frame.shape[0], frame.shape[1])
    )

    # Draw tracks
    for track in tracks:
        x1, y1, x2, y2 = track.tlbr.astype(int)
        track_id = track.track_id

        cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
        cv2.putText(frame, f'ID: {track_id}',
                    (x1, y1-10), cv2.FONT_HERSHEY_SIMPLEX,
                    0.7, (0, 255, 0), 2)