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Manual Execution #12927

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kbkabadayi opened this issue Apr 15, 2024 · 2 comments
Closed

Manual Execution #12927

kbkabadayi opened this issue Apr 15, 2024 · 2 comments

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@kbkabadayi
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File: https://github.com/ultralytics/yolov5/blob/master/.github/workflows/codeql-analysis.yml
Smell Description:
This smell occurs when a workflow is set to be run manually using on: workflow_dispatch keyword. It is a bad practice to run workflows manually.
Fix:
Remove workflow_dispatch at line 4

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👋 Hello @kbkabadayi, thank you for your interest in YOLOv5 🚀! Please visit our ⭐️ Tutorials to get started, where you can find quickstart guides for simple tasks like Custom Data Training all the way to advanced concepts like Hyperparameter Evolution.

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Requirements

Python>=3.8.0 with all requirements.txt installed including PyTorch>=1.8. To get started:

git clone https://github.com/ultralytics/yolov5  # clone
cd yolov5
pip install -r requirements.txt  # install

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YOLOv5 may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):

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If this badge is green, all YOLOv5 GitHub Actions Continuous Integration (CI) tests are currently passing. CI tests verify correct operation of YOLOv5 training, validation, inference, export and benchmarks on macOS, Windows, and Ubuntu every 24 hours and on every commit.

Introducing YOLOv8 🚀

We're excited to announce the launch of our latest state-of-the-art (SOTA) object detection model for 2023 - YOLOv8 🚀!

Designed to be fast, accurate, and easy to use, YOLOv8 is an ideal choice for a wide range of object detection, image segmentation and image classification tasks. With YOLOv8, you'll be able to quickly and accurately detect objects in real-time, streamline your workflows, and achieve new levels of accuracy in your projects.

Check out our YOLOv8 Docs for details and get started with:

pip install ultralytics

@glenn-jocher
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Hey there 👋! Thanks for reaching out with your observation.

Actually, the use of workflow_dispatch in the .github/workflows/codeql-analysis.yml allows for a higher degree of flexibility by enabling manual triggers of the workflow. This can be particularly useful for testing or debugging purposes without the need to push commits just to trigger the workflow. It's a deliberate choice to balance automation with manual control where necessary.

We aim to maintain practicality alongside efficiency in our workflows, and this approach has shown benefits in various scenarios. Nonetheless, we appreciate your input and are always evaluating our practices for improvements!

Let us know if you have any more suggestions or questions!

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