物体追踪算法

约 129 个字 137 行代码 预计阅读时间 2 分钟

使用须知

在使用这段代码前，需要确保设备安装了python库：imutils 否则请输入pip命令

pip install imutils

遇到的坑

初次运行是出现了以下错误

AttributeError: module 'cv2' has no attribute 'TrackerBoosting_create'
# 或者
AttributeError: module 'cv2' has no attribute 'TrackerTLD_create'
# 或者
AttributeError: module 'cv2' has no attribute 'TrackerMedianFlow_create'
# 或者
AttributeError: module 'cv2' has no attribute 'TrackerMOSSE_create'

这是由于opencv版本包括4.5.1以上，不支持这些函数，网上的方法多是提出安装opencv-contrib-python,我试过了但无效。最终解决方案是： 将以下代码

        "boosting": cv2.legacy.TrackerBoosting_create,
        "mil": cv2.TrackerMIL_create,
        "tld": cv2.TrackerTLD_create,
        "medianflow": cv2.TrackerMedianFlow_create,
        "mosse": cv2.TrackerMOSSE_create

修改成

        "boosting": cv2.legacy.TrackerBoosting_create,
        "mil": cv2.legacy.TrackerMIL_create,
        "tld": cv2.legacy.TrackerTLD_create,
        "medianflow": cv2.legacy.TrackerMedianFlow_create,
        "mosse": cv2.legacy.TrackerMOSSE_create

修改后运行成功！

以下是物体追踪算法的全部代码：

from imutils.video import VideoStream
from imutils.video import FPS
import argparse
import imutils
import time
import cv2
import numpy as np

# 构造参数解析器
ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video", type=str,
    help="path to input video file")
ap.add_argument("-t", "--tracker", type=str, default="kcf",
    help="OpenCV object tracker type")
args = vars(ap.parse_args())

# 获取opencv版本信息
(major, minor) = cv2.__version__.split(".")[:2]
# 创建物体追踪器 直接使用Tracker_create，版本3.2及其之前直接使用
if int(major) == 3 and int(minor) < 3:
    tracker = cv2.Tracker_create(args["tracker"].upper())


else:
    OPENCV_OBJECT_TRACKERS = {
        "csrt": cv2.TrackerCSRT_create,
        "kcf": cv2.TrackerKCF_create,
        "boosting": cv2.legacy.TrackerBoosting_create,
        "mil": cv2.legacy.TrackerMIL_create,
        "tld": cv2.legacy.TrackerTLD_create,
        "medianflow": cv2.legacy.TrackerMedianFlow_create,
        "mosse": cv2.legacy.TrackerMOSSE_create
    }

    tracker = OPENCV_OBJECT_TRACKERS[args["tracker"]]()


initBB = None


if not args.get("video", False):
    print("[INFO] starting video stream...")
    vs = VideoStream(src=0).start()
    time.sleep(1.0)

else:
    vs = cv2.VideoCapture(args["video"])

fps = None


def video_mirror_output(video):
    new_img=np.zeros_like(video)
    h,w=video.shape[0],video.shape[1]
    for row in range(h):
        for i in range(w):
            new_img[row,i] = video[row,w-i-1]
    return new_img


while True:
    frame = vs.read()
    #翻转
    frame = cv2.flip(frame,1)
    frame = frame[1] if args.get("video", False) else frame
    # 检车是否 读取到视频流结尾
    if frame is None:
        break
    # 调整窗体大小，提高处理效率
    frame = imutils.resize(frame, width=500)
    (H, W) = frame.shape[:2]

    # 检查当前是否在追踪物体
    if initBB is not None:

        (success, box) = tracker.update(frame)

        if success:
            (x, y, w, h) = [int(v) for v in box]
            cv2.rectangle(frame, (x, y), (x + w, y + h),
                (0, 255, 0), 2)

        fps.update()
        fps.stop()

        info = [
            ("Tracker", args["tracker"]),
            ("Success", "Yes" if success else "No"),
            ("FPS", "{:.2f}".format(fps.fps())),
        ]

        for (i, (k, v)) in enumerate(info):
            text = "{}: {}".format(k, v)
            cv2.putText(frame, text, (10, H - ((i * 20) + 20)),
                cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 2)


    cv2.imshow("Frame", frame)
    key = cv2.waitKey(1) & 0xFF

    if key == ord("s"):

        initBB = cv2.selectROI("Frame", frame, fromCenter=False,
            showCrosshair=True)

        tracker.init(frame, initBB)
        fps = FPS().start()


    elif key == ord("q"):
        break

if not args.get("video", False):
    vs.stop()

else:
    vs.release()

cv2.destroyAllWindows()