# 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


# Download script/URL (optional)
# download: bash data/scripts/get_coco.sh

# train and val data as 1) directory: path/images/, 2) file: path/images.txt, or 3) list: [path1/images/, path2/images/]
path: /home/situ/Disk6T/dyy/work/Yolov5/yolov5/datasets/YuanJian2022
train: /home/situ/Disk6T/dyy/work/Yolov5/yolov5/input/yuanjian_0112/train_0112.txt # 118287 images
val: /home/situ/Disk6T/dyy/work/Yolov5/yolov5/input/yuanjian_0112/valid_0112.txt  # 5000 images


# Classes
nc: 6  # number of classes
names: ['id_front', 'id_back', 'zhiye_front', 'zhiye_back', 'file', 'phone']  # class names