utils/general.py print_mutation variable keys does not correspond to output of seg train/val

[AdrianStkr]

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• I have searched the YOLOv5 issues and found no similar bug report.

YOLOv5 Component

Other

Bug

File ".../yolov5-master/segment/train.py", line 674, in
main(opt)
File ".../yolov5-master/segment/train.py", line 654, in main
print_mutation(results, hyp.copy(), save_dir, opt.bucket)
File ".../yolov5-master/utils/general.py", line 979, in print_mutation
f.write(s + ('%s,' * n % vals).rstrip(',') + '\n')
TypeError: not all arguments converted during string formatting

Environment

• yolov5 v6.2
• torchvision 0.13.1
• torch 1.12.1
• Python 3.10.6
• Ubuntu 20.04.4 LTS

Minimal Reproducible Example

python .../segment/train.py --data coco128-seg.yaml --weights '' --cfg yolov5s-seg.yaml --img 640 --evolve --epochs 2 --batch-size 3

Additional

Hi,

variable keys (see below) in print_mutation needs to be updated to correspond to the output of train in .../segment/train.py when --evolve is used.

keys = ('metrics/precision', 'metrics/recall', 'metrics/mAP_0.5', 'metrics/mAP_0.5:0.95', 'val/box_loss',
'val/obj_loss', 'val/cls_loss') + tuple(hyp.keys()) # [results + hyps]

thank you!

cheers,
Adrian

Are you willing to submit a PR?

• Yes I'd like to help by submitting a PR!

[github-actions]

👋 Hello @AdrianStkr, 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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[glenn-jocher]

@AdrianStkr hi Adrian 👋,

Thanks for reporting this issue and providing the context! We value your input and I'll make sure to look into updating the variable keys in print_mutation to correspond to the output of train in .../segment/train.py when --evolve is used.

I appreciate your willingness to contribute and will keep you in the loop as we work on resolving this. Your support means a lot to the YOLOv5 community and the Ultralytics team.

Cheers!