实现步骤：

1. 安装ultralytics
2. 安装 deep_sort
3. 设置视频地址

import cv2
from ultralytics import YOLO
from deep_sort_realtime.deepsort_tracker import DeepSort

# 1. 初始化 YOLOv8（只保留 person 类）
model = YOLO("yolov8n.pt")
model.model.names          # 查看 80 类索引
PERSON_ID = 0              # COCO 中 person 对应索引 0

# 2. 初始化 DeepSORT
tracker = DeepSort(
    max_age=30,            # 丢失 30 帧才删除轨迹
    n_init=3,              # 连续 3 帧命中才确认轨迹
    max_iou_distance=0.7,
    max_cosine_distance=0.2,
    nn_budget=100,
)

# 3. 打开视频
in_video  = "运动会无人机拍摄_p1.mp4"
cap       = cv2.VideoCapture(in_video)
fps       = int(cap.get(cv2.CAP_PROP_FPS))
w         = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
h         = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
fourcc    = cv2.VideoWriter_fourcc(*"mp4v")
out_video = cv2.VideoWriter("output/street_tracked_sport.mp4", fourcc, fps, (w, h))

frame_id = 0
while cap.isOpened():
    ret, frame = cap.read()
    if not ret:
        break
    frame_id += 1

    print(frame_id)
    # 3.1 YOLOv8 推理
    results = model(frame, classes=[PERSON_ID], verbose=False)[0]  # 只检测行人
    detections = []
    for *xyxy, conf, cls in results.boxes.data.tolist():
        x1, y1, x2, y2 = map(int, xyxy)
        w_box = x2 - x1
        h_box = y2 - y1
        detections.append([[x1, y1, w_box, h_box], conf])

    # 3.2 DeepSORT 更新
    tracks = tracker.update_tracks(detections, frame=frame)

    # 3.3 画框 + ID
    for track in tracks:
        if not track.is_confirmed():
            continue
        x1, y1, x2, y2 = map(int, track.to_ltrb())
        tid = track.track_id
        cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
        cv2.putText(frame, f"id:{tid}", (x1, y1 - 10),
                    cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 0), 2)

    # 3.4 写入结果
    out_video.write(frame)
    # 可选：实时预览
    # cv2.imshow("YOLOv8+DeepSORT", frame)
    # if cv2.waitKey(1) & 0xFF == 27:   # ESC 退出
    #     break

cap.release()
out_video.release()
cv2.destroyAllWindows()
print("Done! 结果已保存到 output/street_tracked_sport.mp4")