Training crash on first validation: Error in processing validate dataset path

[thanhminhmr]

The tool crash while training from scratch, the trace point to this line in test.py.

Traceback (most recent call last):
  File "train.py", line 541, in <module>
    train(hyp, opt, device, tb_writer)
  File "train.py", line 367, in train
    compute_loss=compute_loss)
  File "/usr/local/lib/python3.7/dist-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/content/yolov5/test.py", line 81, in test
    is_coco = data['val'].endswith('coco/val2017.txt')  # COCO dataset
AttributeError: 'list' object has no attribute 'endswith'

yolov5/test.py

Line 81 in d808855

is_coco = data['val'].endswith('coco/val2017.txt') # COCO dataset

This is most likely an oversight in the code:
While the dataset file allows list of train/validation data sources (for example in coco128.yaml), the portion of code from above doesn't accept list.

yolov5/data/coco128.yaml

Line 12 in d808855

# train and val data as 1) directory: path/images/, 2) file: path/images.txt, or 3) list: [path1/images/, path2/images/]

This is the related part of the dataset.yaml.

train: [/train/images/1/, /train/images/2/]
val: [/val/images/1/]

I'm unfamiliar with python so I cannot create a patch, but this should be a simple fix. (By adding type check before the endswith call)

[github-actions]

👋 Hello @thanhminhmr, 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]

@thanhminhmr thanks for the bug report! Yes this looks like a problem. This should be fixable by updating this line to:

is_coco = type(data['val']) is str and data['val'].endswith('coco/val2017.txt')  # COCO dataset

If this fix works well in your use case can you please submit a PR with it to help everyone else in the future? Thank you!

[glenn-jocher]

@thanhminhmr good news 😃! Your original issue may now be fixed ✅ in PR #3646 and #5521. 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 🚀!