yolov8 下载及使用

1. YOLOV8环境配置

1.1 conda创建新的虚拟环境

 conda creat -name YOLOv8 python=3.9 

1.2 查看创建的虚拟环境

conda env list

1.3 激活虚拟环境

conda activate YOLOv8

1.4 更新pip

防止下载版本过低而无法正常下载，此步骤也可以省略。

 pip install --upgrade pip pip install setuptools wheel

1.5 清除缓存

这一步可以大大提过下载速度，防止安装OpenCV时过卡。

 pip cache purge  

1.6 安装ultralytics

其中，–verbose用来显示安装进度

pip install ultralytics -i https://pypi.tuna.tsinghua.edu.cn/simple  --verbose

2.使用

from collections import defaultdictimport cv2
import numpy as npfrom ultralytics import YOLO# Load the YOLOv8 model
model = YOLO("yolov8n.pt")# Open the video file
video_path = "trafic.mp4"
cap = cv2.VideoCapture(video_path)# Store the track history
track_history = defaultdict(lambda: [])while cap.isOpened():# Read a frame from the videosuccess, frame = cap.read()if success:# Run YOLOv8 tracking on the frame, persisting tracks between framesresults = model.track(frame, persist=True)# Visualize the results on the frameannotated_frame = results[0].plot()# Display the annotated framecv2.imshow("YOLOv8 Tracking", annotated_frame)# Break the loop if 'q' is pressedif cv2.waitKey(1) & 0xFF == ord("q"):breakelse:# Break the loop if the end of the video is reachedbreak# Release the video capture object and close the display window
cap.release()
cv2.destroyAllWindows()