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-0.0.19.tar.gz (14.0 kB view details)

Uploaded Source

Built Distribution

ultralytics-0.0.19-py3-none-any.whl (13.7 kB view details)

Uploaded Python 3

File details

Details for the file ultralytics-0.0.19.tar.gz.

File metadata

  • Download URL: ultralytics-0.0.19.tar.gz
  • Upload date:
  • Size: 14.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.0 CPython/3.9.0

File hashes

Hashes for ultralytics-0.0.19.tar.gz
Algorithm Hash digest
SHA256 28f7068e3ce79b5c48ad73c88807259e5858d648846b7fae290a959f3d212426
MD5 c1069031270210526e173ba931596ba4
BLAKE2b-256 c04320a03afd9adf13e705acfc98c337e44b17e559f5961bfc8a9bc79073a594

See more details on using hashes here.

File details

Details for the file ultralytics-0.0.19-py3-none-any.whl.

File metadata

File hashes

Hashes for ultralytics-0.0.19-py3-none-any.whl
Algorithm Hash digest
SHA256 6a4d958c1b2e7dcb8f1e9332f17c323135f577bff1e23d89f5a81a9b4ef0584c
MD5 059090c880b9dc22d516f33bf73d7146
BLAKE2b-256 8d6027294da37e30d78b698c0185d6e095bd94e3ff4217945cca72e00650bbd4

See more details on using hashes here.

Supported by

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