软硬件环境
- ubuntu 18.04 64bit
- anaconda3 with python 3.6.4
- opencv 3.4.2
视频看这里
跟踪算法
opencv
中总共有8种目标跟踪算法,分别是BOOSTING
、MIL
、KCF
、TLD
、MEDIANFLOW
、GOTURN
、CSRT
和MOSSE
。每种算法对opencv
的版本各有要求,需要注意。
目前使用的较多的跟踪算法是KCF
和CSRT
,前者速度很快,但准确率稍低;后者准确率较高不过速度较慢,在实际应用中,需要自行根据场景进行选择。
实例代码
# -*- coding: utf-8 -*-
# @Time : 18-12-19 下午8:08
# @Author : xugaoxiang
# @Email : xugx.ai@gmail.com
# @Website : https://xugaoxiang.com
# @File : tracker.py
# @Software: PyCharm
import sys
import cv2
import click
@click.command()
@click.option('--video', help = 'input video')
@click.option('--algorithm', help = 'tracker algorithm, BOOSTING、MIL、KCF、TLD、MEDIANFLOW、GOTURN、CSRT、MOSSE')
def main(video, algorithm):
'''
:param video: 待处理的视频文件
:param algorithm: 指定OpenCV中的跟踪算法
:return:
'''
major_ver, minor_ver, subminor_ver = (cv2.__version__).split('.')
# 根据opencv的不同版本,创建跟踪器
if int(minor_ver) < 3:
tracker = cv2.Tracker_create(algorithm)
else:
if algorithm == 'BOOSTING':
tracker = cv2.TrackerBoosting_create()
if algorithm == 'MIL':
tracker = cv2.TrackerMIL_create()
if algorithm == 'KCF':
tracker = cv2.TrackerKCF_create()
if algorithm == 'TLD':
tracker = cv2.TrackerTLD_create()
if algorithm == 'MEDIANFLOW':
tracker = cv2.TrackerMedianFlow_create()
if algorithm == 'GOTURN':
tracker = cv2.TrackerGOTURN_create()
if algorithm == "CSRT":
tracker = cv2.TrackerCSRT_create()
if algorithm == 'MOSSE':
tracker = cv2.TrackerMOSSE_create()
# 读取视频文件
video_cap = cv2.VideoCapture(video)
# 检查视频文件是否被正确打开
if not video_cap.isOpened():
print("Open video failed.")
sys.exit()
# 读取第一帧数据
ok, frame = video_cap.read()
if not ok:
print('Read video file failed.')
sys.exit()
# 手动选择关注的区域
bbox = cv2.selectROI(frame, False)
#
ok = tracker.init(frame, bbox)
while True:
# 读取下一帧数据
ok, frame = video_cap.read()
if not ok:
break
# 开始计时器
timer = cv2.getTickCount()
# 更新跟踪器
ok, bbox = tracker.update(frame)
# 计算fps
fps = cv2.getTickFrequency() / (cv2.getTickCount() - timer)
# 画出 bounding box
if ok:
p1 = (int(bbox[0]), int(bbox[1]))
p2 = (int(bbox[0] + bbox[2]), int(bbox[1] + bbox[3]))
cv2.rectangle(frame, p1, p2, (255, 0, 0), 2, 1)
else:
# Tracking failure
cv2.putText(frame, "Tracking failure detected", (100, 80), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (0, 0, 255), 2)
# 显示
cv2.putText(frame, algorithm + " Tracker", (100, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (50, 170, 50), 2)
cv2.putText(frame, "FPS : " + str(int(fps)), (100, 50), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (50, 170, 50), 2)
cv2.imshow("Tracking", frame)
# 接收到q键,退出循环
if cv2.waitKey(1) & 0xFF == ord('q'):
break
if __name__ == '__main__':
main()
然后执行脚步
python tracker.py --video liuxiang_22s.mp4 --algorithm CSRT
其它算法使用,可以通过python tracker.py --help
来查看,最后运行的效果,我丢到了youtube
上了,https://youtu.be/Xl4PUT5vRDY