当前位置：首页 > news >正文

YOLO11追踪简单应用

news 2025/10/30 8:48:27

准备工作，需要下载一下yolo模型，我这里用的时yolo11，下载链接Ultralytics YOLO11 - Ultralytics YOLO 文档

将上面的文件放到文件夹里，并用vscode打开，为该项目创建自己的虚拟环境 crtl+shift+p

选择刚才创建的虚拟环境，进入终端安装所需要的包

pip install torch torchvision torchaudio
pip install ultralytics
pip install opencv-python
pip install pyautogui
pip install lap>=0.5.12

新建一个track.py文件对视频进行抽帧处理

import cv2 as cv
from ultralytics import YOLO
from time import sleep
rec = cv.VideoCapture('rec.mp4')
i=0
while True:r,f = rec.read()if not r:print('没有更多的帧了')breakif cv.waitKey(1)==ord('q'):print('您按了q键')break#实际操作i += 1if i % 25 == 0:cv.imwrite(f'{i}.jpg',f)rec.release()
cv.destroyAllWindows()

对抽帧的图片进行统一改名,改名网址Rename - 批量文件重命名工具

对图片进行标注详细步骤看https://blog.csdn.net/qq_64556701/article/details/153980803?fromshare=blogdetail&sharetype=blogdetail&sharerId=153980803&sharerefer=PC&sharesource=qq_64556701&sharefrom=from_link

标注完成，将其分为训练集和验证集，其中（images和labels文件名不要进行修改）

创建shu.yaml，指定训练和验证集的目录

train: datasets/shu/images/train
val: datasets/shu/images/val
names:0: shu

创建train.py进行训练

from ultralytics import YOLO
yolo = YOLO('yolo11n.pt')
yolo.train(data='shu.yaml',workers=0,epochs=300,batch=16)

使用训练好的模型进行追踪

import cv2 as cv
from ultralytics import YOLO
import pyautogui as pg
import numpy as np
yolo = YOLO('shu.pt')while True:if cv.waitKey(1) == ord('q'):breakshot = pg.screenshot()shot_np = np.array(shot)shot_np = shot_np[:,:,::-1]result = yolo.track(shot_np,persist=True)for i in result[0].boxes.xywh:pos = (i[0],i[1])pg.click(pos)cv.waitKey(0)
cv.destroyAllWindows()

中间有延时，可能会导致有多个地鼠时，会来不及，可以进行下面优化，提高准确性能

import cv2 as cv
from ultralytics import YOLO
import pyautogui as pg
import numpy as np
import timeyolo = YOLO('shu.pt')
pg.FAILSAFE = False  # 禁用安全退出，提高点击速度
pg.PAUSE = 0  # 移除pyautogui的默认延迟# 设置鼠标移动参数
pg.MINIMUM_DURATION = 0
pg.MINIMUM_SLEEP = 0while True:if cv.waitKey(1) == ord('q'):breakstart_time = time.time()# 截图shot = pg.screenshot()shot_np = np.array(shot)shot_np = shot_np[:,:,::-1]# 推理检测result = yolo.track(shot_np, persist=True)# 批量处理所有检测到的地鼠if result[0].boxes is not None and len(result[0].boxes) > 0:# 获取所有地鼠中心坐标positions = []for i in result[0].boxes.xywh:x, y = int(i[0]), int(i[1])positions.append((x, y))# 快速点击所有检测到的位置for pos in positions:# 直接移动并点击，不添加延迟pg.moveTo(pos[0], pos[1], duration=0)pg.click()# 控制帧率，避免过度占用CPUelapsed = time.time() - start_timeif elapsed < 0.05:  # 最小20FPStime.sleep(0.05 - elapsed)cv.destroyAllWindows()

查看全文

http://www.dtcms.com/a/540001.html