corrupt JPEG data

[thx13]

Excuse me.When i was training my data, the cmd would show this problem: 'corrupt JPEG data:Premature end of data segment'. Would it influence the result? My train data adds some background images.

[github-actions[bot]]

👋 Hello @thx13, 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]

@thx13 this is a low level C error caused by corrupt or incomplete jpeg images in your dataset, it is not easy to detect in python. See https://stackoverflow.com/questions/33548956/detect-avoid-premature-end-of-jpeg-in-cv2-python

[github-actions[bot]]

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]

@thx13 good news 😃! Your original issue may now be fixed ✅ in PR #3638. 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 🚀!

[glenn-jocher]

@thx13 good news 😃! Your original issue may now be fixed ✅ in PR #4548. This PR automatically restores and saves corrupted JPEGs before training starts, and all images are now used for training, including the restored JPEGs.

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 🚀!

[KKhaledZen13]

@glenn-jocher Hello, I believe the same issue is present using yolov8 if you run it through the proposed tiger pose dataset. Though i will mention... i didnt install ultralytics lib instead i took the "bin" file yolo from the bin folder and i use it on the ultralytics folder.

[glenn-jocher]

Hello @KKhaledZen13! It appears there might be a mix-up in your setup process. For optimum performance and compatibility with our datasets, including the "tiger pose" dataset, it's recommended to fully install the Ultralytics library rather than relying on binaries directly from the "bin" folder. This ensures all dependencies and necessary components are correctly aligned. Could you try installing the library following the provided guidelines and verify if the issue persists? Here's a quick reminder on how to install:

pip install ultralytics

If the problem continues even after installation, please let us know. We're here to help! 🚀