yolov8 docs update #69
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Important Review skippedAuto incremental reviews are disabled on this repository. Please check the settings in the CodeRabbit UI or the You can disable this status message by setting the WalkthroughThe pull request updates the YOLOv8 documentation in Datumaro to clarify dataset import capabilities. Specifically, the change adds a note explaining that Datumaro can now handle dataset imports with flexible folder structures, particularly when datasets are exported to the Ultralytics YOLO format. The documentation update provides an example of a supported directory structure to help users understand the import flexibility. Changes
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🧹 Nitpick comments (2)
site/content/en/docs/formats/yolo_v8.md (2)
182-196: LGTM! Clear explanation of flexible folder structure support.The added section effectively documents Datumaro's ability to handle alternative folder structures, with a good practical example referencing Roboflow. This helps users understand the flexibility in dataset organization.
Consider these minor enhancements to make the documentation even clearer:
Since some tools (e.g. [roboflow](https://roboflow.com/formats/yolov8-pytorch-txt)) have the folders order switched when exporting to Ultralytics YOLO format, -datumaro can also import dataset with folders like that: +datumaro can also import datasets with an alternative folder structure:Also, consider adding a note that this is particularly useful when working with datasets exported from various annotation tools, not just Roboflow.
182-182: Consider adding issue references for better traceability.Since this change addresses specific issues (openvinotoolkit#111 and openvinotoolkit#222), consider adding a note referencing these issues in a comment or in the section introduction. This helps maintain the connection between the documentation and the problems it solves.
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