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Documentation of methods, parameters, allowed values, term definitions, etc, etc #9584

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jmiller-dr opened this issue Sep 25, 2022 · 4 comments
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enhancement New feature or request Stale

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@jmiller-dr
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  • I have searched the YOLOv5 issues and found no similar feature requests.

Description

There's a documentation webpage and some tutorials, but no actual documentation. Please provide documentation for each method, argument, etc.

Custom detection is particularly poorly documented and highly glossed over in the little tutorials.

Use case

No response

Additional

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Are you willing to submit a PR?

  • Yes I'd like to help by submitting a PR!
@jmiller-dr jmiller-dr added the enhancement New feature or request label Sep 25, 2022
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github-actions bot commented Sep 25, 2022

👋 Hello @jmiller-dr, 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.

If this is a 🐛 Bug Report, please provide screenshots and minimum viable code to reproduce your issue, otherwise we can not help you.

If this is a custom training ❓ Question, please provide as much information as possible, including dataset images, training logs, screenshots, and a public link to online W&B logging if available.

For business inquiries or professional support requests please visit https://ultralytics.com or email [email protected].

Requirements

Python>=3.7.0 with all requirements.txt installed including PyTorch>=1.7. To get started:

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

Environments

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

Status

CI CPU testing

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

@glenn-jocher
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glenn-jocher commented Sep 25, 2022

@jmiller-dr thanks for your feedback! Yes, docs are something have highlighted for improvement in our roadmap, particularly for the high level classes and functions. For custom python inference I'd recommend the PyTorch Hub tutorial, as this provides the most deployment flexibility and also offers many usage examples:

Tutorials

Good luck 🍀 and let us know if you have any other questions!

@jmiller-dr
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jmiller-dr commented Sep 25, 2022 via email

@github-actions
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github-actions bot commented Oct 26, 2022

👋 Hello, this issue has been automatically marked as stale because it has not had recent activity. Please note it will be closed if no further activity occurs.

Access additional YOLOv5 🚀 resources:

Access additional Ultralytics ⚡ resources:

Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed!

Thank you for your contributions to YOLOv5 🚀 and Vision AI ⭐!

@github-actions github-actions bot added the Stale label Oct 26, 2022
@github-actions github-actions bot closed this as not planned Won't fix, can't repro, duplicate, stale Nov 6, 2022
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