Retrieving trained YOLOv5 weights from WandB

[aniruddh10124]

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Question

After training the weights on YOLOv5 and saving the results on WandB, how do I save and retrieve those weights from WandB for using the trained weights to detect images in the test set? I know that some change needs to be done in the argument of !python detect.py --weight <argument>, but what should I write in place of <argument>?
Just to be clear, I am able to retrieve the trained weights from Google Drive, but my teams requires the weights to be stored and retrieved from WandB to streamline our work, which I am not able to do.
Thank you for your time.

Additional

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[github-actions]

👋 Hello @aniruddh10124, 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>=3.6.0 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

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[glenn-jocher]

@aniruddh10124 thanks for your question! Our W&B expert @AyushExel should be able to help here.

[AyushExel]

@aniruddh10124 Hey, are you asking if you can directly pass artifact links to perform inference like you can to resume runs?
python detect.py --weights wandb-artifact://{artifact link} ? This isn't supported currently. wandb is only supported in training tasks.

How can you access the weights uploaded as W&B artifact?

Each artifact comes with an API. If you go to your dashboard where model is saved, you should see something like this:

You can copy and execute this api in your system and it'll download the weights. You can then use the the weights normally. Example:
python detect.py --weight {path to downloaded model}

Hope this helps :)

[aniruddh10124]

@AyushExel So, I guess what we are trying to do is not currently supported by WandB. Thank you for your clarification.

[AyushExel]

@glenn-jocher are there any plans to support passing weights links for inference as Anirudh is describing? Not just for artifacts but also things like s3 bucket, GCP etc. links

[glenn-jocher]

@AyushExel that's funny, that's probably the only argument that doesn't allow direct URL passing, because we already have the autodownload handling for the release assets. I tested it out just now and it seems to already be partially enabled, but the workflow has issues. I can take a look at it this week, I'll add a TODO.

[glenn-jocher]

TODO: URL --weights argument, i.e.:

python detect.py --weights https://github.com/ultralytics/yolov5/releases/download/v6.0/yolov5s6.pt

[glenn-jocher]

@AyushExel @aniruddh10124 good news 😃! Your original issue may now be fixed ✅ in PR #5991. This PR allows train.py, val.py, detect.py, export.py to pass a URL for the --weights argument, allowing download of custom YOLOv5 weights from any URL:

# Download arbitrary weights from any URL
python detect.py --weights https://github.com/ultralytics/yolov5/releases/download/v6.0/yolov5s.pt 

# Autodownload official weights from YOLOv5 assets
python detect.py --weights yolov5s.pt

Weights will only download if not already found locally in root directory (they will not download twice by running command twice).

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 🚀!