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yolo11训练模型与测试

article 2025/2/11 0:19:06

首先先要导入yolo的模型，如下

在这里插入图片描述

数据集中yaml

path: .
train: data/train/images
val: data/valid/images
test: data/test/images

nc: 10
names: ['cat', 'chicken', 'cow', 'dog', 'fox', 'goat', 'horse', 'person', 'racoon', 'skunk']

#roboflow:
#  workspace: yolo-ccdgk
#  project: test_3-qm1g6
#  version: 3
#  license: CC BY 4.0
#  url: https://universe.roboflow.com/yolo-ccdgk/test_3-qm1g6/dataset/3

截图如下

在这里插入图片描述

训练代码

from ultralytics import YOLO
import os
os.environ['KMP_DUPLICATE_LIB_OK']='TRUE'
if __name__ == '__main__':
    model = YOLO('yolo11n.pt')
    model.train(
        data='data4/data.yaml',
        imgsz=640,
        batch=4,
        epochs=10,
        workers=16)

测试代码

from ultralytics import YOLO

if __name__ == '__main__':
    model = YOLO('best.pt')

    result = model(r"data/train/images/516_jpg.rf.cea0ff4bc1596f406d0a83af4ce9332f.jpg")
    result[0].show()
    pass