YOLOV8训练笔记

一、     Yolov8直接安装和conda安装

1.1安装

yolov8有两种安装方式，一种可直接安装U神的库，为了方便管理，还是在conda里面安装：

conda create -n yolov8 python=3.8

conda activate ylolv8

pip install ultralytics

1.2验证

安装完成之后，验证是否安装成功。

yolo task=segment mode=predict model=yolov8s-seg.pt source='1.jpg' show=True

yolo predict model=yolov8n.pt source='ultralytics.com/images/bus.…'

YOLOV8目标识别——详细记录从环境配置、自定义数据、模型训练到模型推理部署 (xdnf.cn)  

二、     Yolov8目标检测detect

2.1 yolov8s.pt预训练模型开始训练

数据集制作时，将数据存放在datasets里，从预训练的*.pt模型开始训练

yolo task=detect mode=train model=datasets/yolov8s.pt epochs=10 batch=-1 data=datasets/first/cow_data.yaml

yolo task=detect mode=train model=yolov8m.pt epochs=5000 batch=8 imgsz=640 data=A_dataset_fzz/cow_data.yaml  

yolo detect mode=train model=yolov8m.pt epochs=3500 batch=8 imgsz=1280 data=A_dataset_fzz/cow_data.yaml

yolo task=segment mode=train model=yolov8m.pt epochs=3500 batch=16 imgsz=1280 data=A_dataset_fzz/cow_data.yaml

yolo task=detect mode=val split=test model=runs/detect/train3/weights/best.pt  data=datasets/first/cow_data.yaml

2.2 coco.yaml模型直接训练

yolo task=detect mode=train model= /data/coding/fzz/ultralytics/ultralytics/cfg/models/v8/yolov8.yaml epochs=3500 batch=16 imgsz=1280 data=datasets/split_dir/myseg.yaml

2.3 模型预测

yolo predict model=yolov8n.pt imgsz=320 source='ultralytics.com/images/bus.…'

yolo predict model=yolov8n.pt imgsz=640 source='ultralytics.com/images/bus.…'

yolo predict model=yolov8n.pt imgsz=1280 source='ultralytics.com/images/bus.…'

适合于不同尺寸，如5120*5120

2.4中断继续训练

yolo train resume model=runs/detect/train3/weights/last.pt