Comments (6)
π Hello @Pikus16, thank you for your interest in Ultralytics YOLOv8 π! We recommend a visit to the Docs for new users where you can find many Python and CLI usage examples and where many of the most common questions may already be answered.
If this is a π Bug Report, please provide a minimum reproducible example to help us debug it.
If this is a custom training β 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.
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Install
Pip install the ultralytics
package including all requirements in a Python>=3.8 environment with PyTorch>=1.8.
pip install ultralytics
Environments
YOLOv8 may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):
- Notebooks with free GPU:
- Google Cloud Deep Learning VM. See GCP Quickstart Guide
- Amazon Deep Learning AMI. See AWS Quickstart Guide
- Docker Image. See Docker Quickstart Guide
Status
If this badge is green, all Ultralytics CI tests are currently passing. CI tests verify correct operation of all YOLOv8 Modes and Tasks on macOS, Windows, and Ubuntu every 24 hours and on every commit.
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It seems like the error might be occurring due to concurrent modification of the plots
dictionary while it's being iterated over in the W&B callback. This can happen if the training process or another part of the code modifies the plots
dictionary during logging to W&B.
A potential workaround could be to capture a shallow copy of plots.items()
before the loop starts in your callback function. Here's a quick modification you can try:
def _log_plots(plots, step):
items = list(plots.items()) # take a snapshot of items
for name, params in items:
# your logging code here
This change ensures that you're iterating over a static list of items, and any modifications to the original plots
dictionary during iteration won't affect the loop. Although it feels a bit hacky, it is a common practice to avoid such runtime errors and should resolve the issue. Give this a try and see if it stabilizes your training logging!
from ultralytics.
Makes sense, thank you for your response! I submitted a PR with your change in it here: #12779
from ultralytics.
@Pikus16 PR merged, thank you for your contributions!
from ultralytics.
Thank you for all your help!
from ultralytics.
@Pikus16 you're welcome! If you have any more questions or need further assistance down the road, feel free to reach out. Happy coding! π
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Related Issues (20)
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- ModuleNotFoundError: No module named 'ultralytics.nn.modules.conv'; 'ultralytics.nn.modules' is not a package HOT 2
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- YOLOv8 Pose estimation - Adjust label size HOT 3
- How to train YOLOv8 with single class without considering cls loss HOT 1
- Ultralytics Openvino Batch Size HOT 5
- Getting last layer of the network by removing activation function HOT 12
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- Why some of the objects in pose estimation are not getting detected? HOT 1
- What file is required for classification classes weights? HOT 5
- Corrupt JPEG data: 1199 extraneous bytes before marker 0xd4 HOT 3
- The accuracy of yolov8l-obb only reached 55+, which is significantly lower than the 80.7 mentioned in the official documentation. HOT 3
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