一、在yolo11源码文件夹创建一个train.py

内容如下：

from ultralytics import YOLOif __name__ == '__main__':model = YOLO(r'ultralytics/cfg/models/11/yolo11.yaml')model.train(data=r'D:/yolo11/WiderPerson_yolo/WiderPerson_yolo/WiderPerson_yolo.yaml',imgsz=(640,384),  # 训练图片大小，默认640workers=5,epochs=200,  # 训练轮次，默认100batch=5,   # 训练批次，默认16project='runs',  # 项目文件夹的名，默认为runsname='exp',      # 用于保存训练文件夹名，默认exp，依次累加device='0',    # 要运行的设备 device =0 是GPU显卡训练，device = cpu)

二、指定数据集路径

2.1 WiderPerson_yolo.yaml内容：

# train and val data as 1) directory: path/images/, 2) file: path/images.txt, or 3) list: [path1/images/, path2/images/]
train: images/train #8000张图片
val: images/val #1000张图片
test:# number of classes
nc: 1# class names
names: ["person"]

2.2 训练集图像

2.3 训练集标签

2.4 验证集图像

 

2.5 验证集标签

 

三、运行pycharm

 配置conda环境，然后点击运行