# YOLOv5 🚀 by Ultralytics https://ultralytics.com, licensed under GNU GPL v3.0
# COCO128 dataset https://www.kaggle.com/ultralytics/coco128 (first 128 images from COCO train2017)
# Example usage: python train.py --data coco128.yaml
# parent
# ├── yolov5
# └── datasets
#     └── coco128  ← downloads here


# 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: ../datasets/coco128  # dataset root dir
train: I:/daima/yolov5-master/pascal/train.txt # train images (relative to 'path') 128 images
val: I:/daima/yolov5-master/pascal/val.txt  # val images (relative to 'path') 128 images
test: I:/daima/yolov5-master/pascal/test.txt  # test images (optional)

# Classes
nc: 20  # number of classes

names: ['aeroplane','bicycle','bird','boat','bottle','bus','car','cat','chair','cow','diningtable','dog','horse','motorbike','person','pottedplant','sheep','sofa','train','tvmonitor']  #类别数目



