KeyError: 'anchors'

[amadeok]

Hello i'm getting KeyError: 'anchors' when trying to evolve a model trained for about 900 epochs. I've tried commenting out the line 509 'anchors': (2, 2.0, 10.0), # anchors per output grid (0 to ignore) from train.py as suggested in the hyperparameter thread but it does not fix it. Complete error:

Traceback (most recent call last):
  File "train.py", line 551, in <module>
    hyp[k] = max(hyp[k], v[1])  # lower limit
KeyError: 'anchors'

Any help?
thanks

[glenn-jocher]

@amadeok uncomment anchors in hyp.scratch.yaml and then evolve.

[amadeok]

@amadeok uncomment anchors in hyp.scratch.yaml and then evolve.

Hi thansk for reply.
Still wasn't working, it seems it wasn't able to find the yaml file. I added --hyp "/content/yolov5/data/hyp.scratch.yaml" and now it seems to work.

[dubbsbrandon]

I'm still having the same issue despite trying both solutions mentioned above. Are there other issues possibly linked to this issue?

[glenn-jocher]

@dubbsbrandon hi, thanks for the feedback. Please note that most technical problems are due to:

• Your modified or out-of-date code. If your issue is not reproducible in a new git clone version of this repo we can not debug it. Before going further run this code and verify your issue persists:

$ git clone https://github.com/ultralytics/yolov5 yolov5_new  # clone latest
$ cd yolov5_new
$ python detect.py  # verify detection

# CODE TO REPRODUCE YOUR ISSUE HERE

• Your custom data. If your issue is not reproducible in one of our 3 common datasets (COCO, COCO128, or VOC) we can not debug it. Visit our Custom Training Tutorial for guidelines on training your custom data. Examine train_batch0.jpg and test_batch0.jpg for a sanity check of your labels and images.

• Your environment. If your issue is not reproducible in one of the verified environments below we can not debug it. If you are running YOLOv5 locally, verify your environment meets all of the requirements.txt dependencies specified below. If in doubt, download Python 3.8.0 from https://www.python.org/, create a new venv, and then install requirements.

If none of these apply to you, we suggest you close this issue and raise a new one using the Bug Report template, providing screenshots and minimum viable code to reproduce your issue. Thank you!

Requirements

Python 3.8 or later with all requirements.txt dependencies installed, including torch>=1.6. To install run:

$ 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 Notebook with free GPU:
• Kaggle Notebook with free GPU: https://www.kaggle.com/ultralytics/yolov5
• Google Cloud Deep Learning VM. See GCP Quickstart Guide
• Docker Image https://hub.docker.com/r/ultralytics/yolov5. See Docker Quickstart Guide

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[github-actions]

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.

[glenn-jocher]

@amadeok @dubbsbrandon good news 😃! Your original issue may now be fixed ✅ in PR #3887. This PR adds hyp['anchors']=3 if the anchors key is missing/commented in your hyperparameter file, fixing a long-running problem when starting hyp evolution using the default command:

python train.py --evolve

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 with 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 🚀!