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validation with .pt is validated by rectangular? #13109
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👋 Hello @yjseok, 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. If this is a 🐛 Bug Report, please provide a minimum reproducible example to help us debug it. If this is a custom training ❓ Question, please provide as much information as possible, including dataset image examples and training logs, and verify you are following our Tips for Best Training Results. RequirementsPython>=3.8.0 with all requirements.txt installed including PyTorch>=1.8. To get started: git clone https://github.com/ultralytics/yolov5 # clone
cd yolov5
pip install -r requirements.txt # install EnvironmentsYOLOv5 may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):
StatusIf this badge is green, all YOLOv5 GitHub Actions Continuous Integration (CI) tests are currently passing. CI tests verify correct operation of YOLOv5 training, validation, inference, export and benchmarks on macOS, Windows, and Ubuntu every 24 hours and on every commit. Introducing YOLOv8 🚀We're excited to announce the launch of our latest state-of-the-art (SOTA) object detection model for 2023 - YOLOv8 🚀! Designed to be fast, accurate, and easy to use, YOLOv8 is an ideal choice for a wide range of object detection, image segmentation and image classification tasks. With YOLOv8, you'll be able to quickly and accurately detect objects in real-time, streamline your workflows, and achieve new levels of accuracy in your projects. Check out our YOLOv8 Docs for details and get started with: pip install ultralytics |
@yjseok hello, Thank you for reaching out and for providing a clear question. To address your concern: When you validate a model using Here's a snippet from 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 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 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! |
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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,
Additional
No response
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