# YOLOv5 🚀 by Ultralytics, 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