| # 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 | |