Skip to main content

No project description provided

Project description




👋 Hello from the Ultralytics Team! We've been working hard these last few months to launch Ultralytics HUB, a new web tool for training and deploying all your YOLOv5 🚀 models from one spot!

1. Create 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 https://hub.ultralytics.com/. 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/coco6.zip, then you should have a coco6.yaml inside your coco6/ directory, which should zip to create coco6.zip for upload:

zip -r coco6.zip coco6

The example coco6.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 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
nc: 80  # number of classes
names: [ 'person', 'bicycle', 'car', ...]

After zipping your dataset, sign in to HUB at https://hub.ultralytics.com and click on 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 signin using your Ultralytics API key to begin training your model. Open In Colab

❓ Issues

If you are a new Ultralytics HUB user and have questions or comments, you are in the right place! Please click the New Issue button in the Issues tab in this ultralytics/hub repo and let us know what we can do to make your life better 😃!


Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ultralytics-0.0.23.tar.gz (15.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ultralytics-0.0.23-py3-none-any.whl (14.5 kB view details)

Uploaded Python 3

File details

Details for the file ultralytics-0.0.23.tar.gz.

File metadata

  • Download URL: ultralytics-0.0.23.tar.gz
  • Upload date:
  • Size: 15.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.0 CPython/3.9.0

File hashes

Hashes for ultralytics-0.0.23.tar.gz
Algorithm Hash digest
SHA256 0df0806b3223101a6cbe7a5585e8c4a189c943808f2092fc3a30e28f5e15f5f9
MD5 08a7889403937ff7732540082933a7c5
BLAKE2b-256 54a01df23cfda9b286951814266afac94711a9bbf0a58aacdce9591177af9bbd

See more details on using hashes here.

File details

Details for the file ultralytics-0.0.23-py3-none-any.whl.

File metadata

  • Download URL: ultralytics-0.0.23-py3-none-any.whl
  • Upload date:
  • Size: 14.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.0 CPython/3.9.0

File hashes

Hashes for ultralytics-0.0.23-py3-none-any.whl
Algorithm Hash digest
SHA256 33f1ccb0913970a1cb518195242c0896422af94ca40ccd35a2c5ac43b5e970ce
MD5 7b70c3f4ae2067c6a6fb5d4635185e77
BLAKE2b-256 aa183dea72ea417359360de72557ef102ddd1bfebf95b02a186fde561de5aab7

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page