# Ultralytics YOLOv5 🚀, AGPL-3.0 license
# ImageNet-1k dataset https://www.image-net.org/index.php by Stanford University
# Simplified class names from https://github.com/anishathalye/imagenet-simple-labels
# Example usage: python classify/train.py --data imagenet
# parent
# ├── yolov5
# └── datasets
#     └── imagenet10  ← 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/imagenet10 # dataset root dir
train: train # train images (relative to 'path') 1281167 images
val: val # val images (relative to 'path') 50000 images
test: # test images (optional)

# Classes
names:
  0: tench
  1: goldfish
  2: great white shark
  3: tiger shark
  4: hammerhead shark
  5: electric ray
  6: stingray
  7: cock
  8: hen
  9: ostrich

# Download script/URL (optional)
download: data/scripts/get_imagenet10.sh
