Question : how can i run the training with my GPU RTx 3060 ?

[KhalladiSofianeIT]

How can i run the training with device GPU rtx 3060 ?

[glenn-jocher]

@KhalladiSofianeIT YOLOv5 commands use CUDA device 0 by default, so no additional action is required on your part to use your GPU, just run normal commands, i.e. python detect.py

[KhalladiSofianeIT]

Thanks but i begin training i had this bug he stopped in this step : how i can solve it ?

[glenn-jocher]

@KhalladiSofianeIT 👋 hi, thanks for letting us know about this possible problem with YOLOv5 🚀. 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! 😃

[Jocassio]

Hi, i hade a similar problem whit the same video configurate. when a chose the "python detect.py --source 0 " when try to connect with the webcam and the folow mensage came :

... lib\site-packages\torch\nn\modules\module.py", line 1186, in getattr
raise AttributeError("'{}' object has no attribute '{}'".format(
AttributeError: 'Upsample' object has no attribute 'recompute_scale_factor'

The same problem occurs when I choose different video sources. As I bought the computer recently, I'm still installing the programs, if someone can help me identify the help of installing a package or something missing. Thanks for the attention

[glenn-jocher]

@Jocassio it appears you may have environment problems. Please ensure you meet all dependency requirements if you are attempting to run YOLOv5 locally. If in doubt, create a new virtual Python 3.9 environment, clone the latest repo (code changes daily), and pip install requirements.txt again from scratch.

💡 ProTip! Try one of our verified environments below if you are having trouble with your local environment.

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

Models and datasets download automatically from the latest YOLOv5 release when first requested.

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]

@Jocassio @KhalladiSofianeIT good news 😃! Your original issue may now be fixed ✅ in PR #6932. This PR implements PyTorch 1.11.0 compatibility updates and resolves AttributeError: 'Upsample' object has no attribute 'recompute_scale_factor' errors.

To receive this update:

• Git – git pull from within your yolov5/ directory or git clone https://github.com/ultralytics/yolov5 again
• PyTorch Hub – Force-reload model = torch.hub.load('ultralytics/yolov5', 'yolov5s', force_reload=True)
• Notebooks – View updated notebooks
• Docker – sudo docker pull ultralytics/yolov5:latest to update your image

Thank you for spotting this issue and informing us of the problem. Please let us know if this update resolves the issue for you, and feel free to inform us of any other issues you discover or feature requests that come to mind. Happy trainings with YOLOv5 🚀!