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Ultralytics HUB

Ultralytics HUB is a new no-code online tool developed by Ultralytics, the creators of the popular YOLOv5 object detection and image segmentation models. With Ultralytics HUB, users can easily train and deploy YOLOv5 models without any coding or technical expertise.

Ultralytics HUB is designed to be user-friendly and intuitive, with a drag-and-drop interface that allows users to easily upload their data and select their model configurations. It also offers a range of pre-trained models and templates to choose from, making it easy for users to get started with training their own models. Once a model is trained, it can be easily deployed and used for real-time object detection and image segmentation tasks. Overall, Ultralytics HUB is an essential tool for anyone looking to use YOLOv5 for their object detection and image segmentation projects.

Get started now and experience the power and simplicity of Ultralytics HUB for yourself. Sign up for a free account and start building, training, and deploying YOLOv5 and YOLOv8 models today.

1. Upload a Dataset

Ultralytics HUB datasets are just like YOLOv5 🚀 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 Your dataset YAML, directory and zip should all share the same name. For example, if your dataset is called 'coco6' as in our example ultralytics/hub/, then you should have a coco6.yaml inside your coco6/ directory, which should zip to create for upload:

zip -r coco6

The example 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 YAML format. See the YOLOv5 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
  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 models on it!

HUB Dataset Upload

2. Train a Model

Connect to the Ultralytics HUB notebook and use your model API key to begin training! Open In Colab

3. Deploy to Real World

Export your model to 13 different formats, including TensorFlow, ONNX, OpenVINO, CoreML, Paddle and many others. Run models directly on your mobile device by downloading the Ultralytics App!

Ultralytics mobile app

❓ Issues

If you are a new Ultralytics HUB user and have questions or comments, you are in the right place! Please raise a New Issue and let us know what we can do to make your life better 😃!