Reduce dependencies for model only usage

[maxstrobel]

🚀 Feature

If I just want to use your models for inference, I don't need all additional features like:

• visualizations
• profiling
• type conversions to pandas
• ...

However, those useful features are (partially) built-in to the model architecture. Therefore I need to install additional libraries like

• matplotlib
• seaborn
• pandas

even if I don't use them at all. Also downloading the additional font (Arial.ttf) can be a problem in restricted environments.

I think it would be nice to have an operable core model that runs with only a subset of required dependencies.

Motivation

Less dependencies & simpler integration in other projects.

Pitch

I'd suggest to disentangle the core model (inference only) and the additional features (plotting, profiling, ...).

Alternatives

Leave it as it is and require all dependencies

[github-actions]

👋 Hello @maxstrobel, 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.

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Requirements

Python>=3.6.0 with all requirements.txt installed including PyTorch>=1.7. To get started:

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

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):

• Google Colab and Kaggle notebooks with free GPU:
• Google Cloud Deep Learning VM. See GCP Quickstart Guide
• Amazon Deep Learning AMI. See AWS Quickstart Guide
• Docker Image. See Docker Quickstart Guide

Status

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]

@maxstrobel hi, thank you for your feature suggestion on how to improve YOLOv5 🚀!

We already use a semi-requirements method of auto-installing dependencies on demand depending on purpose, i.e. when using YOLOv5 with PyTorch Hub we omit all unnecessary packages we can from requirements checks:

yolov5/hubconf.py

Line 37 in fad57c2

check_requirements(requirements=file.parent / 'requirements.txt', exclude=('tensorboard', 'thop', 'opencv-python'))

But we are always open to improvements! The fastest and easiest way to incorporate your ideas into the official codebase is to submit a Pull Request (PR) implementing your idea, and if applicable providing before and after profiling/inference/training results to help us understand the improvement your feature provides. This allows us to directly see the changes in the code and to understand how they affect workflows and performance.

Please see our ✅ Contributing Guide to get started.

[github-actions]

👋 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:

• Wiki – https://github.com/ultralytics/yolov5/wiki
• Tutorials – https://docs.ultralytics.com/yolov5
• Docs – https://docs.ultralytics.com

Access additional Ultralytics ⚡ resources:

• Ultralytics HUB – https://ultralytics.com
• Vision API – https://ultralytics.com/yolov5
• About Us – https://ultralytics.com/about
• Join Our Team – https://ultralytics.com/work
• Contact Us – https://ultralytics.com/contact

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 ⭐!

[mohammad69h94]

check_requirements

@maxstrobel hi, thank you for your feature suggestion on how to improve YOLOv5 🚀!

We already use a semi-requirements method of auto-installing dependencies on demand depending on purpose, i.e. when using YOLOv5 with PyTorch Hub we omit all unnecessary packages we can from requirements checks:

yolov5/hubconf.py

Line 37 in fad57c2

check_requirements(requirements=file.parent / 'requirements.txt', exclude=('tensorboard', 'thop', 'opencv-python'))

But we are always open to improvements! The fastest and easiest way to incorporate your ideas into the official codebase is to submit a Pull Request (PR) implementing your idea, and if applicable providing before and after profiling/inference/training results to help us understand the improvement your feature provides. This allows us to directly see the changes in the code and to understand how they affect workflows and performance.

Please see our ✅ Contributing Guide to get started.

How to disable arial.ttf font downloading?
Because i get error: urllib.error.URLError: <urlopen error EOF occurred in violation of protocol (_ssl.c:1131)> when downloading font.

[glenn-jocher]

@mohammad69h94 👋 hi, thanks for letting us know about this possible problem with YOLOv5 🚀 and Arial.ttf. We've created a few short guidelines below to help users provide what we need in order to get started investigating a possible problem.

How to create a Minimal, Reproducible Example

When asking a question, people will be better able to provide help if you provide code that they can easily understand and use to reproduce the problem. This is referred to by community members as creating a minimum reproducible example. Your code that reproduces the problem should be:

• ✅ Minimal – Use as little code as possible to produce the problem
• ✅ Complete – Provide all parts someone else needs to reproduce the problem
• ✅ Reproducible – Test the code you're about to provide to make sure it reproduces the problem

For Ultralytics to provide assistance your code should also be:

• ✅ Current – Verify that your code is up-to-date with GitHub master, and if necessary git pull or git clone a new copy to ensure your problem has not already been solved in master.
• ✅ Unmodified – Your problem must be reproducible using official YOLOv5 code without changes. Ultralytics does not provide support for custom code ⚠️.

If you believe your problem meets all the above criteria, please close this issue and raise a new one using the 🐛 Bug Report template with a minimum reproducible example to help us better understand and diagnose your problem.

Thank you! 😃

[maxstrobel]

check_requirements

@maxstrobel hi, thank you for your feature suggestion on how to improve YOLOv5 🚀!
We already use a semi-requirements method of auto-installing dependencies on demand depending on purpose, i.e. when using YOLOv5 with PyTorch Hub we omit all unnecessary packages we can from requirements checks:

yolov5/hubconf.py

Line 37 in fad57c2

check_requirements(requirements=file.parent / 'requirements.txt', exclude=('tensorboard', 'thop', 'opencv-python'))

But we are always open to improvements! The fastest and easiest way to incorporate your ideas into the official codebase is to submit a Pull Request (PR) implementing your idea, and if applicable providing before and after profiling/inference/training results to help us understand the improvement your feature provides. This allows us to directly see the changes in the code and to understand how they affect workflows and performance.
Please see our ✅ Contributing Guide to get started.

How to disable arial.ttf font downloading? Because i get error: urllib.error.URLError: <urlopen error EOF occurred in violation of protocol (_ssl.c:1131)> when downloading font.

Sorry for the late replay, you can download the file manually & place it in ~/.config/Ultralytics