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# YOLOv5 π 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 | |
# βββ yolov5 | |
# βββ datasets | |
# βββ imagenet10 β 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 | |