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. 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 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
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 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 click the New Issue button in the Issues tab in this 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-0.0.40.tar.gz (17.3 kB view details)

Uploaded Source

Built Distribution

ultralytics-0.0.40-py3-none-any.whl (16.8 kB view details)

Uploaded Python 3

File details

Details for the file ultralytics-0.0.40.tar.gz.

File metadata

  • Download URL: ultralytics-0.0.40.tar.gz
  • Upload date:
  • Size: 17.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.6

File hashes

Hashes for ultralytics-0.0.40.tar.gz
Algorithm Hash digest
SHA256 a35615ecd9c011fc529348bff49ae75085896be5929cbac0328f935bf69c9c3c
MD5 f6d6085950d75bda1784bf60f1d34409
BLAKE2b-256 b9f0f3542bae98e38f348ced84c78e249fd0d6636072b37b86d057bde5ab9883

See more details on using hashes here.

File details

Details for the file ultralytics-0.0.40-py3-none-any.whl.

File metadata

File hashes

Hashes for ultralytics-0.0.40-py3-none-any.whl
Algorithm Hash digest
SHA256 cb4587a73062db1123ec6cd1d481ff71cee0a6627a0617d5e6327132df4c69c4
MD5 88c6ceee524ac9c92a57eea4e1fe0a18
BLAKE2b-256 01d9d8d24a363390249d8bcdea49b0b4b87402a74a06191d16c15a846b004e5d

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