# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
# COCO128 dataset https://www.kaggle.com/ultralytics/coco128 (first 128 images from COCO train2017) by Ultralytics
# Example usage: python train.py --data coco128.yaml
# parent
# ├── yolov5
# └── datasets
#     └── coco128  ← downloads here (7 MB)


# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: D:/YOLO/yolov5-master/corn/datasets  # dataset root dir  path是绝对路径
train: images/train  # train images (relative to 'path') 128 images train是在path绝对路径条件下的训练集路径，即：wzry/datasets/images/train
val: images/val  # val images (relative to 'path') 128 images  val同上，但是是验证集，这里我为了方便，让训练集和验证集是一个，也没啥大问题
#test:  # test images (optional)

# Classes
nc: 2  # number of classes
names: ['kedu', 'biaochi']  # class names


## Download script/URL (optional)
#download: https://ultralytics.com/assets/coco128.zip