From 6eff43882de4b6832597340973beead61e444469 Mon Sep 17 00:00:00 2001 From: Ultralytics AI Assistant <135830346+UltralyticsAssistant@users.noreply.github.com> Date: Mon, 1 Jan 2024 22:58:51 +0100 Subject: [PATCH] Update format.yml (#516) Co-authored-by: glenn-jocher --- .github/workflows/format.yml | 15 +++++++++------ README.md | 3 +-- example_datasets/coco8-pose/README.md | 18 +++++------------- example_datasets/coco8-seg/README.md | 18 +++++------------- example_datasets/coco8/README.md | 18 +++++------------- 5 files changed, 25 insertions(+), 47 deletions(-) diff --git a/.github/workflows/format.yml b/.github/workflows/format.yml index 053645d..27b2c7d 100644 --- a/.github/workflows/format.yml +++ b/.github/workflows/format.yml @@ -1,6 +1,6 @@ -# Ultralytics 🚀, AGPL-3.0 license -# Ultralytics Format Workflow -# This workflow automatically formats code and documentation in pull requests and pushes to main branch +# Ultralytics 🚀 - AGPL-3.0 license +# Ultralytics Actions https://github.com/ultralytics/actions +# This workflow automatically formats code and documentation in PRs to official Ultralytics standards name: Ultralytics Actions @@ -14,7 +14,10 @@ jobs: format: runs-on: ubuntu-latest steps: - - name: Checkout Repository - uses: actions/checkout@v4 - - name: Run Ultralytics Formatting Actions + - name: Run Ultralytics Formatting uses: ultralytics/actions@main + with: + python: true + docstrings: true + markdown: true + spelling: true diff --git a/README.md b/README.md index ec6cad4..e56d30e 100644 --- a/README.md +++ b/README.md @@ -91,8 +91,7 @@ Connect to the Ultralytics HUB notebook and employ your model API key to embark ## 🌐 3. Deploy to the Real World -Transition your model to 13 different formats including TensorFlow, ONNX, OpenVINO, CoreML, Paddle, and more. Operate your models directly on your [iOS](https://apps.apple.com/xk/app/ultralytics/id1583935240) or -[Android](https://play.google.com/store/apps/details?id=com.ultralytics.ultralytics_app) mobile device by downloading the [Ultralytics App](https://ultralytics.com/app_install)! +Transition your model to 13 different formats including TensorFlow, ONNX, OpenVINO, CoreML, Paddle, and more. Operate your models directly on your [iOS](https://apps.apple.com/xk/app/ultralytics/id1583935240) or [Android](https://play.google.com/store/apps/details?id=com.ultralytics.ultralytics_app) mobile device by downloading the [Ultralytics App](https://ultralytics.com/app_install)! ## ❓ Have Issues or Questions? diff --git a/example_datasets/coco8-pose/README.md b/example_datasets/coco8-pose/README.md index 2ce8428..5f86fb1 100644 --- a/example_datasets/coco8-pose/README.md +++ b/example_datasets/coco8-pose/README.md @@ -2,14 +2,9 @@ ## Introduction -[Ultralytics](https://ultralytics.com) COCO8-pose is a small, but versatile pose detection dataset composed of the first -8 images of the COCO train 2017 set, 4 for training and 4 for validation. This dataset is ideal for testing and -debugging object detection models, or for experimenting with new detection approaches. With 8 images, it is small enough -to be easily manageable, yet diverse enough to test training pipelines for errors and act as a sanity check before -training larger datasets. +[Ultralytics](https://ultralytics.com) COCO8-pose is a small, but versatile pose detection dataset composed of the first 8 images of the COCO train 2017 set, 4 for training and 4 for validation. This dataset is ideal for testing and debugging object detection models, or for experimenting with new detection approaches. With 8 images, it is small enough to be easily manageable, yet diverse enough to test training pipelines for errors and act as a sanity check before training larger datasets. -This dataset is intended for use with Ultralytics [HUB](https://hub.ultralytics.com) -and [YOLOv8](https://github.com/ultralytics/ultralytics). +This dataset is intended for use with Ultralytics [HUB](https://hub.ultralytics.com) and [YOLOv8](https://github.com/ultralytics/ultralytics). ## Sample Images and Annotations @@ -19,15 +14,12 @@ Here are some examples of images from the dataset, along with their correspondin ## Resources -We hope that the variety of resources provided here will help you get the most out of HUB and maximize your experience -with HUB and COCO8-pose. +We hope that the variety of resources provided here will help you get the most out of HUB and maximize your experience with HUB and COCO8-pose. - Browse the [Docs](https://docs.ultralytics.com/) for details on usage and implementation. - Raise an issue on [GitHub](https://github.com/ultralytics/hub/issues/new/choose) for support and troubleshooting. -- Join our [Discord](https://ultralytics.com/discord) community for questions and discussions with fellow users and - developers. +- Join our [Discord](https://ultralytics.com/discord) community for questions and discussions with fellow users and developers. - Learn more about Ultralytics and our work at our [Community](https://community.ultralytics.com) page. -- Explore the Ultralytics YOLOv8 [GitHub](https://github.com/ultralytics/ultralytics) repository for additional tools - and resources. +- Explore the Ultralytics YOLOv8 [GitHub](https://github.com/ultralytics/ultralytics) repository for additional tools and resources. To request an Enterprise License, please complete the form at [Ultralytics Licensing](https://ultralytics.com/license). diff --git a/example_datasets/coco8-seg/README.md b/example_datasets/coco8-seg/README.md index 2c1f07a..5a4bc9b 100644 --- a/example_datasets/coco8-seg/README.md +++ b/example_datasets/coco8-seg/README.md @@ -2,14 +2,9 @@ ## Introduction -[Ultralytics](https://ultralytics.com) COCO8-seg is a small, but versatile instance segmentation dataset composed of the -first 8 images of the COCO train 2017 set, 4 for training and 4 for validation. This dataset is ideal for testing and -debugging segmentation models, or for experimenting with new detection approaches. With 8 images, it is small enough to -be easily manageable, yet diverse enough to test training pipelines for errors and act as a sanity check before training -larger datasets. +[Ultralytics](https://ultralytics.com) COCO8-seg is a small, but versatile instance segmentation dataset composed of the first 8 images of the COCO train 2017 set, 4 for training and 4 for validation. This dataset is ideal for testing and debugging segmentation models, or for experimenting with new detection approaches. With 8 images, it is small enough to be easily manageable, yet diverse enough to test training pipelines for errors and act as a sanity check before training larger datasets. -This dataset is intended for use with Ultralytics [HUB](https://hub.ultralytics.com) -and [YOLOv8](https://github.com/ultralytics/ultralytics). +This dataset is intended for use with Ultralytics [HUB](https://hub.ultralytics.com) and [YOLOv8](https://github.com/ultralytics/ultralytics). ## Sample Images and Annotations @@ -19,15 +14,12 @@ Here are some examples of images from the dataset, along with their correspondin ## Resources -We hope that the variety of resources provided here will help you get the most out of HUB and maximize your experience -with HUB and COCO8-seg. +We hope that the variety of resources provided here will help you get the most out of HUB and maximize your experience with HUB and COCO8-seg. - Browse the [Docs](https://docs.ultralytics.com/) for details on usage and implementation. - Raise an issue on [GitHub](https://github.com/ultralytics/hub/issues/new/choose) for support and troubleshooting. -- Join our [Discord](https://ultralytics.com/discord) community for questions and discussions with fellow users and - developers. +- Join our [Discord](https://ultralytics.com/discord) community for questions and discussions with fellow users and developers. - Learn more about Ultralytics and our work at our [Community](https://community.ultralytics.com) page. -- Explore the Ultralytics YOLOv8 [GitHub](https://github.com/ultralytics/ultralytics) repository for additional tools - and resources. +- Explore the Ultralytics YOLOv8 [GitHub](https://github.com/ultralytics/ultralytics) repository for additional tools and resources. To request an Enterprise License, please complete the form at [Ultralytics Licensing](https://ultralytics.com/license). diff --git a/example_datasets/coco8/README.md b/example_datasets/coco8/README.md index 1cb8583..28f9a31 100644 --- a/example_datasets/coco8/README.md +++ b/example_datasets/coco8/README.md @@ -2,14 +2,9 @@ ## Introduction -[Ultralytics](https://ultralytics.com) COCO8 is a small, but versatile object detection dataset composed of the first 8 -images of the COCO train 2017 set, 4 for training and 4 for validation. This dataset is ideal for testing and debugging -object detection models, or for experimenting with new detection approaches. With 8 images, it is small enough to be -easily manageable, yet diverse enough to test training pipelines for errors and act as a sanity check before training -larger datasets. +[Ultralytics](https://ultralytics.com) COCO8 is a small, but versatile object detection dataset composed of the first 8 images of the COCO train 2017 set, 4 for training and 4 for validation. This dataset is ideal for testing and debugging object detection models, or for experimenting with new detection approaches. With 8 images, it is small enough to be easily manageable, yet diverse enough to test training pipelines for errors and act as a sanity check before training larger datasets. -This dataset is intended for use with Ultralytics [HUB](https://hub.ultralytics.com) -and [YOLOv8](https://github.com/ultralytics/ultralytics). +This dataset is intended for use with Ultralytics [HUB](https://hub.ultralytics.com) and [YOLOv8](https://github.com/ultralytics/ultralytics). ## Sample Images and Annotations @@ -19,15 +14,12 @@ Here are some examples of images from the dataset, along with their correspondin ## Resources -We hope that the variety of resources provided here will help you get the most out of HUB and maximize your experience -with HUB and COCO8. +We hope that the variety of resources provided here will help you get the most out of HUB and maximize your experience with HUB and COCO8. - Browse the [Docs](https://docs.ultralytics.com/) for details on usage and implementation. - Raise an issue on [GitHub](https://github.com/ultralytics/hub/issues/new/choose) for support and troubleshooting. -- Join our [Discord](https://ultralytics.com/discord) community for questions and discussions with fellow users and - developers. +- Join our [Discord](https://ultralytics.com/discord) community for questions and discussions with fellow users and developers. - Learn more about Ultralytics and our work at our [Community](https://community.ultralytics.com) page. -- Explore the Ultralytics YOLOv8 [GitHub](https://github.com/ultralytics/ultralytics) repository for additional tools - and resources. +- Explore the Ultralytics YOLOv8 [GitHub](https://github.com/ultralytics/ultralytics) repository for additional tools and resources. To request an Enterprise License, please complete the form at [Ultralytics Licensing](https://ultralytics.com/license).