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| comments | description |
|---|---|
| true | Upload custom datasets to Ultralytics HUB for YOLOv5 and YOLOv8 models. Follow YAML structure, zip and upload. Scan & train new models. |
HUB Datasets
1. Upload a Dataset
Ultralytics HUB datasets are just like YOLOv5 and YOLOv8 🚀 datasets, they use the same structure and the same label formats to keep everything simple.
When you upload a dataset to Ultralytics HUB, make sure to place your dataset YAML inside the dataset root directory
as in the example shown below, and then zip for upload to https://hub.ultralytics.com. Your dataset YAML, directory
and zip should all share the same name. For example, if your dataset is called 'coco8' as in our
example ultralytics/hub/example_datasets/coco8.zip, then you should have a coco8.yaml inside your coco8/ directory, which should zip to create coco8.zip for upload:
zip -r coco8.zip coco8
The example_datasets/coco8.zip dataset in this repository can be downloaded and unzipped to see exactly how to structure your custom dataset.
The dataset YAML is the same standard YOLOv5 and YOLOv8 YAML format. See the YOLOv5 and YOLOv8 Train Custom Data tutorial for full details.
# 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: # dataset root dir (leave empty for HUB)
train: images/train # train images (relative to 'path') 8 images
val: images/val # val images (relative to 'path') 8 images
test: # test images (optional)
# Classes
names:
0: person
1: bicycle
2: car
3: motorcycle
...
After zipping your dataset, sign in to Ultralytics HUB and click the Datasets tab. Click 'Upload Dataset' to upload, scan and visualize your new dataset before training new YOLOv5 or YOLOv8 models on it!
