validation with .pt is validated by rectangular?

[yjseok]

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Question

as title,

in val.py, if I use .pt file as a model to validate,
input resolution is changed like rectangular training?? even though I trained with not rectangular training.

below is code which I'm curious,

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[github-actions]

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[glenn-jocher]

@yjseok hello,

Thank you for reaching out and for providing a clear question. To address your concern:

When you validate a model using val.py with a .pt file, the input resolution can indeed be adjusted to rectangular shapes if the rect parameter is set to True. This behavior is independent of whether the model was trained with rectangular training or not. The rect parameter in val.py is used to enable rectangular inference, which can improve speed and memory efficiency by minimizing padding.

Here's a snippet from val.py that shows how the rect parameter is used:

parser.add_argument('--rect', action='store_true', help='rectangular inference')

If you want to ensure that the validation uses square images (i.e., no rectangular inference), you should run val.py without the --rect flag:

python val.py --weights your_model.pt --data your_data.yaml --rect False

If you continue to experience issues or if this does not resolve your concern, please ensure you are using the latest versions of torch and YOLOv5. You can update your packages with the following commands:

pip install --upgrade torch
pip install --upgrade git+https://github.com/ultralytics/yolov5.git

If the issue persists, please provide a minimum reproducible example so we can investigate further. You can find guidance on creating a minimum reproducible example here.

Thank you for your cooperation, and we look forward to assisting you further!