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# Ultralytics HUB Datasets

Ultralytics HUB datasets are a practical solution for managing and leveraging your custom datasets.

Once uploaded, datasets can be immediately utilized for model training. This integrated approach facilitates a seamless transition from dataset management to model training, significantly simplifying the entire process.

Watch: Upload Datasets to Ultralytics HUB | Complete Walkthrough of Dataset Upload Feature

## Upload 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.

Before you upload a dataset to Ultralytics HUB, make sure to place your dataset YAML file inside the dataset root directory and that your dataset YAML, directory and ZIP have the same name, as shown in the example below, and then zip the dataset directory.

For example, if your dataset is called "coco8", as our COCO8 example dataset, then you should have a `coco8.yaml` inside your `coco8/` directory, which will create a `coco8.zip` when zipped:

    zip -r coco8.zip coco8

You can download our COCO8 example dataset and unzip it to see exactly how to structure your dataset.

The dataset YAML is the same standard YOLOv5 and YOLOv8 YAML format.

coco8.yaml

    # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license

    # COCO8 dataset (first 8 images from COCO train2017) by Ultralytics
    # Documentation: https://docs.ultralytics.com/datasets/detect/coco8/
    # Example usage: yolo train data=coco8.yaml
    # parent
    # ├── ultralytics
    # └── datasets
    #     └── coco8 ← downloads here (1 MB)

    # 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: coco8 # dataset root dir
    train: images/train # train images (relative to 'path') 4 images
    val: images/val # val images (relative to 'path') 4 images
    test: # test images (optional)

    # Classes
    names:
      0: person
      1: bicycle
      2: car
      3: motorcycle
      4: airplane
      5: bus
      6: train
      7: truck
      8: boat
      9: traffic light
      10: fire hydrant
      11: stop sign
      12: parking meter
      13: bench
      14: bird
      15: cat
      16: dog
      17: horse
      18: sheep
      19: cow
      20: elephant
      21: bear
      22: zebra
      23: giraffe
      24: backpack
      25: umbrella
      26: handbag
      27: tie
      28: suitcase
      29: frisbee
      30: skis
      31: snowboard
      32: sports ball
      33: kite
      34: baseball bat
      35: baseball glove
      36: skateboard
      37: surfboard
      38: tennis racket
      39: bottle
      40: wine glass
      41: cup
      42: fork
      43: knife
      44: spoon
      45: bowl
      46: banana
      47: apple
      48: sandwich
      49: orange
      50: broccoli
      51: carrot
      52: hot dog
      53: pizza
      54: donut
      55: cake
      56: chair
      57: couch
      58: potted plant
      59: bed
      60: dining table
      61: toilet
      62: tv
      63: laptop
      64: mouse
      65: remote
      66: keyboard
      67: cell phone
      68: microwave
      69: oven
      70: toaster
      71: sink
      72: refrigerator
      73: book
      74: clock
      75: vase
      76: scissors
      77: teddy bear
      78: hair drier
      79: toothbrush

    # Download script/URL (optional)
    download: https://github.com/ultralytics/assets/releases/download/v0.0.0/coco8.zip

After zipping your dataset, you should validate it before uploading it to Ultralytics HUB. Ultralytics HUB conducts the dataset validation check post-upload, so by ensuring your dataset is correctly formatted and error-free ahead of time, you can forestall any setbacks due to dataset rejection.

    from ultralytics.hub import check_dataset

    check_dataset("path/to/dataset.zip", task="detect")

Once your dataset ZIP is ready, navigate to the Datasets page by clicking on the Datasets button in the sidebar and click on the Upload Dataset button on the top right of the page.

Tip

You can upload a dataset directly from the Home page.

This action will trigger the Upload Dataset dialog.

Select the dataset task of your dataset and upload it in the Dataset .zip file field.

You have the additional option to set a custom name and description for your Ultralytics HUB dataset.

When you're happy with your dataset configuration, click Upload.

After your dataset is uploaded and processed, you will be able to access it from the Datasets page.

You can view the images in your dataset grouped by splits (Train, Validation, Test).

Tip

Each image can be enlarged for better visualization.

Also, you can analyze your dataset by click on the Overview tab.

Next, train a model on your dataset.

## Download Dataset

Navigate to the Dataset page of the dataset you want to download, open the dataset actions dropdown and click on the Download option. This action will start downloading your dataset.

Tip

You can download a dataset directly from the Datasets page.

## Share Dataset

Info

Ultralytics HUB's sharing functionality provides a convenient way to share datasets with others. This feature is designed to accommodate both existing Ultralytics HUB users and those who have yet to create an account.

Note

You have control over the general access of your datasets.

You can choose to set the general access to "Private", in which case, only you will have access to it. Alternatively, you can set the general access to "Unlisted" which grants viewing access to anyone who has the direct link to the dataset, regardless of whether they have an Ultralytics HUB account or not.

Navigate to the Dataset page of the dataset you want to share, open the dataset actions dropdown and click on the Share option. This action will trigger the Share Dataset dialog.

Tip

You can share a dataset directly from the Datasets page.

Set the general access to "Unlisted" and click Save.

Now, anyone who has the direct link to your dataset can view it.

Tip

You can easily click on the dataset's link shown in the Share Dataset dialog to copy it.

## Edit Dataset

Navigate to the Dataset page of the dataset you want to edit, open the dataset actions dropdown and click on the Edit option. This action will trigger the Update Dataset dialog.

Tip

You can edit a dataset directly from the Datasets page.

Apply the desired modifications to your dataset and then confirm the changes by clicking Save.

## Delete Dataset

Navigate to the Dataset page of the dataset you want to delete, open the dataset actions dropdown and click on the Delete option. This action will delete the dataset.

Tip

You can delete a dataset directly from the Datasets page.

Note

If you change your mind, you can restore the dataset from the Trash page.

📅 Created 1 year ago ✏️ Updated 6 months ago

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